Archive / 2026-09-06
September 6, 2026
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View all news →Your intellectual fly is open when you use an LLM to author a post (2025)
bcantrill.dtrace.org11 days ago729 ptsView detailsJoin discussion
keepitfree.ai11 days ago628 ptsView detailsJoin discussion
You Don't Have a Right to Safe Drinking Water, US Court Rules
motherjones.com12 days ago232 ptsView detailsJoin discussion
beza1e1.tuxen.de11 days ago162 ptsView detailsJoin discussion
I refused to train the AI that could replace me
restofworld.org11 days ago97 ptsView detailsJoin discussion
Show HN: Engrim – A universal, local-first SQLite memory engine for AI CLIs
github.com11 days ago90 ptsView detailsJoin discussion
Coop – Isolated VM Environments for Running Claude Code and Codex
github.com11 days ago69 ptsView detailsJoin discussion
Has anybody seen my keys? A key-hierarchy strategy for rack-level security
rfd.shared.oxide.computer11 days ago52 ptsView detailsJoin discussion
How we monitor internal coding agents for misalignment
openai.com11 days ago47 ptsView detailsJoin discussion
"We Have to Assume That the Internet Will Go Offline in the Next Few Years"
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Emacs/Wayland Window Manager in pure elisp
github.com11 days ago40 ptsView detailsJoin discussion
xcancel.com11 days ago39 ptsView detailsJoin discussion
Show HN: VODForge – a free local desktop UI for YouTube video/playlist downloads
getvodforge.com11 days ago38 ptsView detailsJoin discussion
I asked astra to make playable 4D chess
4d-chess.pages.dev11 days ago36 ptsView detailsJoin discussion
Four Weeks of a Vegan Diet Alter Signs of Inflammation and Aging
uniklinik-freiburg.de11 days ago29 ptsView detailsJoin discussion
'RAMageddon' hits consumer electronics as AI drains chip supply
ft.com11 days ago28 ptsView detailsJoin discussion
GOP issues stark warning to AI companies
axios.com11 days ago25 ptsView detailsJoin discussion
ripwire: ripgrep of AI context (CLI+MCP) giving coding agents a map of any repo
github.com11 days ago19 ptsView detailsJoin discussion
Germany's far-right AfD projected to win
cnn.com11 days ago19 ptsView detailsJoin discussion
ROCm 10.0: A Decade of Open Compute, Built for the Age of Agentic AI
rocm.blogs.amd.com11 days ago18 ptsView detailsJoin discussion
Far-right AfD wins historic victory in German state election
reuters.com11 days ago18 ptsView detailsJoin discussion
Amazon cargo plane crashes at Miami airport after it overshoots runway
theguardian.com11 days ago15 ptsView detailsJoin discussion
Hard-Chat – A serverless, RAM-only P2P terminal chat
github.com11 days ago14 ptsView detailsJoin discussion
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ceselder.substack.com11 days ago12 ptsView detailsJoin discussion
HPE Gives Oracle Right to Buy 4.2M Shares for 1 Cent Each
forbes.com11 days ago11 ptsView detailsJoin discussion
Cory Doctorow on the Big AI Lie [video]
youtube.com11 days ago11 ptsView detailsJoin discussion
Kenyans Did College Students' Homework for Years. Then A.I. Arrived
nytimes.com11 days ago10 ptsView detailsJoin discussion
Americans are vibe-coding trading algorithms
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LLM representations have implicit symbolic structure
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Supporting independent journalism in Ukraine
OpenAI, AIRPPU and WAN-IFRA launch an AI program to help Ukrainian news organizations strengthen innovation, resilience, and independent journalism.
openai.com11 days agoView details
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Jakub Pachocki reflects on increasingly capable AI and the challenge of keeping it aligned. He calls for stronger safeguards and international coordination.
openai.com12 days agoView details
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Research acceleration: The view inside OpenAI
Inside OpenAI, coding agents are reshaping AI research. Explore early data on agent usage, experiment velocity, task complexity, and research acceleration.
openai.com12 days agoView details
We look at NeoMME, a family of 260M and 800M bidirectional encoders from H Company. Unlike ColPali-style retrievers, it processes multilingual text tokens and raw 32×32 image patches in a single Transformer, with no pretrained vision tower and no causal decoder. We cover the masked discrete-diffusion pretraining objec…
marktechpost.com11 days agoView details
AI research agents can propose far more experiments than they can afford to run. Meta FAIR, Oxford and UCL introduce AI Research Preference Models — frozen LLM judges that rank 15 unexecuted candidates and execute only one. On AIRS-Bench, the average normalized score rises from 0.684 to 0.729, and the baseline's 24-ho…
marktechpost.com11 days agoView details
Training and benchmarking a computer-use agent needs four things — agents, environments, traces, and a framework to evaluate and train them — and all four ship in incompatible formats today. CUA-Lite, from a UC Berkeley led team, puts them behind one action space and one data schema, and replaces OSWorld's per-task vi…
marktechpost.com12 days agoView details
Seattle Times and Newsday sue OpenAI and Microsoft for infringement
The OpenAI logo is displayed on a smartphone screen placed on a reflective surface on which the company's logo is projected in Creteil, France, on September 4, 2026, as OpenAI began rolling out GPT-6 Astra, its most advanced model to date. (Photo by Samuel Boivin/NurPhoto via Getty Images) | NurPhoto via Getty Images…
theverge.com11 days agoView details
My Brief Summer Fling With Siri AI
I was initially enamored with the beta version of Apple’s revamped smartphone assistant. As the full release approaches, I’ve forgotten Siri AI even exists.
wired.com11 days agoView details
Why China Is the Bogeyman Data Center Enthusiasts Just Can’t Quit
Polls show that overwhelming majorities of Americans hate data centers. China makes a perfect scapegoat for tech leaders and their allies—the only problem is a lack of evidence.
wired.com11 days agoView details
The Anatomy of an ASR Hallucination
arXiv:2609.04404v1 Announce Type: new Abstract: ASR systems sometimes produce fluent text that is unrelated to the speech they receive. We view these hallucinations as one possible consequence of a broader grounding failure, in which the transcript is no longer adequately guided by the audio. To understand where this…
arxiv.org11 days agoView details
On Epistemic Diversity in Large Language Models
arXiv:2609.04835v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used not only to retrieve information, but to answer questions, explain, teach, and support inquiry. In such settings, evaluation cannot be exhausted by accuracy or alignment alone. A system may give a correct answer while st…
arxiv.org11 days agoView details
arXiv:2609.04485v1 Announce Type: new Abstract: We evaluate three open-weight LLMs (Gemma3-12B from the USA, Bielik-11B-v3 from Poland, and Qwen3-4B from China) against World Values Survey Wave 7 data for 63 demographic personas across three countries, using normalized Wasserstein distance to quantify distributional m…
arxiv.org11 days agoView details
A Systematic Comparison of Multilingual Interpretability Methods Reveals Anisotropy-Driven Failures
arXiv:2609.04819v1 Announce Type: new Abstract: Multilingual language models develop shared cross-lingual representations, and various interpretability methods claim to quantify this sharing. These methods have been developed largely in isolation, and when they disagree, it is unclear whether the disagreement reflects…
arxiv.org11 days agoView details
Generating Constructive Feedback on Stories via Reinforcement Learning
arXiv:2609.04824v1 Announce Type: new Abstract: Constructive feedback is crucial for creative writers to refine their storytelling abilities. Since receiving feedback from human experts is often costly and time-intensive, large language models (LLMs) offer a scalable and efficient alternative as automatic writing assi…
arxiv.org11 days agoView details
arXiv:2609.04582v1 Announce Type: new Abstract: A 0.6B language model, asked to verify 1,200 logical conclusions (half valid, half corrupted by a single semantic edit), answers YES every time. Judged by behavior it discriminates nothing; linear probes on its hidden states read the correct verdict at 0.96 AUC, transfer…
arxiv.org11 days agoView details
Why Better Models Can Create Riskier Systems: Evidence from LLM Agents in Financial Markets
arXiv:2609.04373v1 Announce Type: new Abstract: Large language models (LLMs) are being deployed at scale in consequential real-world systems, from financial markets to content moderation to hiring. We show that improving individual model capability can degrade rather than improve system-level outcomes. We hypothesize…
arxiv.org11 days agoView details
ConsensusBench: Benchmark of Consensus Nodes for LLM Reasoning via Outcome Reward Densifying
arXiv:2609.04648v1 Announce Type: new Abstract: Reinforcement learning (RL) has become one of the primary paradigms for reasoning enhancement of large language models (LLMs). In particular, Group Relative Policy Optimization (GRPO) and related algorithms have demonstrated strong performance with outcome-level rewards.…
arxiv.org11 days agoView details
Cache-Aware Joint Router Adaptation for Memory-Efficient MoE Inference
arXiv:2609.04895v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models activate only a small subset of experts per token, but the full expert set often exceeds GPU memory, causing repeated weight transfers during decoding. We formulate expert-cache management as a model-side algorithmic problem and propose a…
arxiv.org11 days agoView details
How Do Language Models Represent and Use Phonological Information for Allomorph Selection?
arXiv:2609.04708v1 Announce Type: new Abstract: Language models are trained on tokenized text that obscures the sound structure of words, yet they reliably produce morphemes whose form is phonologically conditioned. It remains unclear whether they rely on item-specific memorization or rule-like generalization and, if…
arxiv.org11 days agoView details
Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models
arXiv:2609.04720v1 Announce Type: new Abstract: Vision-language models (VLMs) are expected to respond helpfully to appropriate requests while withholding compliance with requests that are incorrect, unsafe, infeasible, or unanswerable. However, existing benchmarks predominantly evaluate non-compliance at the level of…
arxiv.org11 days agoView details
Rethinking Indirect Prompt Injection as a Test-Time Search Problem
arXiv:2609.04495v1 Announce Type: new Abstract: We formulate indirect prompt injection as a test-time search over a task-dependent attack surface induced by the environment, user task, and injection task. To operationalize this formulation, we introduce an agentic attacker with a dedicated search harness that performs…
arxiv.org11 days agoView details
arXiv:2609.04753v1 Announce Type: new Abstract: Reasoning in large language models unfolds through diverse functional operations, such as problem formulation, goal decomposition, and deduction. Although these operations are explicitly distinguished in text, little is known about how they are geometrically organized in…
arxiv.org11 days agoView details
MABPD: Multi-Agent Bias Probing & Detection via Structured Argument Debate
arXiv:2609.04841v1 Announce Type: new Abstract: Media bias in news articles operates through subtle linguistic cues---loaded language, selective framing, and strategic omission---that resist single-model detection and have traditionally required large annotated corpora for supervised training. We ask whether structure…
arxiv.org11 days agoView details
arXiv:2609.04239v1 Announce Type: new Abstract: This technical report presents EXAONE Forecast for Finance (EXAONE Finance), a financial time series (TS) foundation model (TSFM) tailored to financial forecasting. Recent TSFMs achieve strong zero-shot performance through large-scale pretraining. However, they are prima…
arxiv.org11 days agoView details
Continual Graph Memory for Adaptive Recommendation under Intent Drift
arXiv:2609.04651v1 Announce Type: new Abstract: This paper studies adaptive recommendation under intent drift, where feedback from each recommendation outcome can reveal whether the relational evidence used for ranking is useful, missing, or misleading. While Knowledge Graphs (KGs) provide essential semantic structure…
arxiv.org11 days agoView details
Can Activation Steering Capture Multidimensional Authorship Style?
arXiv:2609.04792v1 Announce Type: new Abstract: Activation steering has shown promise for controlling LLM generation along well-defined attributes, but it remains unclear whether it can handle the multidimensional and hard-to-define nature of authorship style. We ask whether structured contrastive prompting along rhet…
arxiv.org11 days agoView details
A Removal Based Approach to Improve LLM Faithfulness at Test-Time
arXiv:2609.04343v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for consequential decisions, making their explanations an important tool for auditing model behavior. Unfortunately, these explanations can be unfaithful, failing to reflect the actual reasoning underlying the model's de…
arxiv.org11 days agoView details
A Cost-Aware Agentic Architecture for NL-to-SQL over Nested Enterprise Schemas, with a New Benchmark
arXiv:2609.04641v1 Announce Type: new Abstract: Natural-language-to-SQL systems have ad- vanced rapidly on academic benchmarks, yet production enterprise schemas exhibit graph- like, semi-structured, deeply nested structure that current benchmarks do not measure. We make two complementary contributions. First, we intr…
arxiv.org11 days agoView details
arXiv:2609.04493v1 Announce Type: new Abstract: We present ResLearn-XR, a residual learning framework for predicting eXtended Reality (XR) network traffic and estimating Quality-of-Experience (QoE) risk. ResLearn-XR adopts a two-stage temporal learning structure comprising a base sequence prediction model augmented wi…
arxiv.org11 days agoView details
BioSync: Transformer-Based Cross-Modal Fusion for a Multimodal Physiological Digital Biomarker
arXiv:2609.04504v1 Announce Type: new Abstract: Cardiac, neural, behavioral, and speech measurements from wearable and mobile devices provide partial, noise-sensitive views of physiological state. BioSync combines these measurements into the \textbf{BioSync Index (BSI)}, a continuous composite digital biomarker define…
arxiv.org11 days agoView details
HarvestBench: Measuring Whether LLM Agents Will Pay to Avoid Killing Animals
arXiv:2609.04444v1 Announce Type: new Abstract: Benchmarks for the side effects an agent causes on the way to a goal already exist, but HarvestBench is the first to put a price on avoiding the side effect and to name that side effect as a living creature. It is a farm simulation: LLM sub-agents drive a crew of two tra…
arxiv.org11 days agoView details
What Does Multi-Harness RL Learn? Credit Assignment and Portability in Coding Agents
arXiv:2609.04518v1 Announce Type: new Abstract: Agent reinforcement learning (RL) increasingly runs through full execution harnesses, and a multi-harness recipe mixes two choices: exposing the policy to several harnesses, and comparing their rewards inside one relative-advantage group. We isolate the second choice in…
arxiv.org11 days agoView details
MaxKernel: Agentic Kernel Generation for TPUs
arXiv:2609.04523v1 Announce Type: new Abstract: Designing and authoring high-performance custom kernels for accelerators is a complex task that requires deep hardware-level expertise. Large Language Models (LLM) can be leveraged together with real-time compiler feedback to build agentic systems for kernel generation.…
arxiv.org11 days agoView details
IPGeoAI: Transformer-Based Geolocation with LLM Semantic Fusion
arXiv:2609.04559v1 Announce Type: new Abstract: Accurate city-level IP Geolocation is an important enabler for the modern digital ecosystem, underpinning services ranging from local content delivery and targeting to digital rights enforcement. However, traditional heuristic and database-driven methods often struggle t…
arxiv.org11 days agoView details
Reducing Hallucinated Transcripts in Whisper via Hallucination Space Projection
arXiv:2609.04561v1 Announce Type: new Abstract: Whisper is a widely used foundation model for automatic speech recognition (ASR), but its generative decoder can produce fluent hallucinated transcripts for inputs containing little or no speech. We propose a training-free, inference-time method to reduce these hallucina…
arxiv.org11 days agoView details
Leveraging Imperfect Restoration for Data Availability Attack
arXiv:2609.04627v1 Announce Type: new Abstract: The abundance of online data is at risk of unauthorized usage in training deep learning models. To counter this, various Data Availability Attacks (DAAs) have been devised to make data unlearnable for such models by subtly perturbing the training data. However, existing…
arxiv.org11 days agoView details
SiLR: Structure-Preserving Admission and Process Reward for LLM Tool Agents
arXiv:2609.04629v1 Announce Type: new Abstract: A runtime gate for an LLM tool agent is usually cast as a filter. In a ReAct loop a rejected proposal is followed by another at the same state, so the gate is a search operator over the proposal stream whose admission criterion shapes which trajectories are reachable. We…
arxiv.org11 days agoView details
ERPBench: Evaluating LLM Agents for Enterprise Decision-Making Across Competitive Market Ecologies
arXiv:2609.04667v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly proposed for enterprise workflows, yet existing evaluations rarely test whether business-decision conclusions transfer across competitive market ecologies. We introduce ERPBench, an execution-instrumented benchmark for e…
arxiv.org11 days agoView details
Train What You Deploy:Token-Faithful Post-Training of a Production Coding
arXiv:2609.04678v1 Announce Type: new Abstract: Existing post-training pipelines for coding and terminal agents suffer severe token and control fidelity errors: simplified training environments mismatch production deployments, and offline token reconstruction from agent logs distorts original prompts and conflates pol…
arxiv.org11 days agoView details
arXiv:2609.04693v1 Announce Type: new Abstract: Urban air quality can vary significantly along transit corridors, necessitating high-resolution monitoring. This work introduces a novel mobile-sensing dataset from Surat, Gujarat, India, comprising PM$*{2.5}$ concentrations, meteorological variables (temperature, humidi…
arxiv.org11 days agoView details
Model Retirement Creates Reproducibility Risk in Biomedical AI Publications
arXiv:2609.04699v1 Announce Type: new Abstract: Background. Large language models (LLMs) are being adopted in biomedical research at a rapid and accelerating pace, yet commercial services that host many widely used models operate under deprecation schedules that can complicate scientific reproducibility. Methods. We s…
arxiv.org11 days agoView details
arXiv:2609.04706v1 Announce Type: new Abstract: A merchant's payment processor, ledger, ERP and bank feed are updated by messages that get delayed, duplicated, dropped and reordered, so for minutes at a time the four hold contradictory beliefs about the same order. An agent resolving the exception must decide whether…
arxiv.org11 days agoView details
Shadow Queries for Private Retrieval in Vector Databases
arXiv:2609.04767v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on information retrieval (IR) systems, such as Retrieval-Augmented Generation (RAG), to incorporate domain-specific knowledge without costly re-training. These systems often store pre-computed document embeddings in cloud-ba…
arxiv.org11 days agoView details
arXiv:2609.04409v1 Announce Type: new Abstract: Multilingual language models often produce inconsistent answers to semantically equivalent questions across languages, motivating methods to improve cross-lingual consistency (CLC). However, existing methods are typically evaluated using different models, tasks, and prot…
arxiv.org11 days agoView details
Safety for Whom? Boundary-Aware Self-Distillation for Controlled LLM Safety Refusal
arXiv:2609.04482v1 Announce Type: new Abstract: Safety alignment is usually posed as a topic-level question: is this subject harmful? Deployments ask a narrower one. A civics tutor and a public-sector assistant may share a base model yet need different boundaries inside the same topic, refusing targeted political mani…
arxiv.org11 days agoView details
Scale-QLoRA: Code-Invariant Adapter Merging for Native 4-bit Microscaling LLMs
arXiv:2609.04526v1 Announce Type: new Abstract: Merging a LoRA adapter into its base model is standard deployment practice: it removes the runtime adapter's per-forward overhead and leaves a single standalone checkpoint any serving stack can load. On a native 4-bit microscaling checkpoint (NVFP4, MXFP4) that step stop…
arxiv.org11 days agoView details
A Calibrated Reflection Approach for Enhancing Confidence Estimation in LLMs
arXiv:2609.04539v1 Announce Type: new Abstract: A critical challenge in deploying Large Language Models (LLMs) is developing reliable mechanisms to estimate their confidence, enabling systems to determine when to trust model outputs versus seek human intervention. We present a Calibrated Reflection approach for enhanc…
arxiv.org11 days agoView details
Towards a universal language of concepts: A survey
arXiv:2609.04528v1 Announce Type: new Abstract: Humans can learn and generalize novel concepts from sparse data because they express knowledge in rich structural formats. In this paper, we propose that programs are a strong candidate for universal representation of concepts. We review computational models of concept l…
arxiv.org11 days agoView details
arXiv:2609.04377v1 Announce Type: new Abstract: Enterprise AI deployments fail not from model inadequacy, but because organizations lack a structured substrate encoding how they decide, negotiate, and execute. Generic LLMs carry no firm-specific ontological priors; RAG remains brittle, with no path to executable actio…
arxiv.org11 days agoView details
Extremely Sparse Supervision Incentivizes Reasoning Ability
arXiv:2609.04565v1 Announce Type: new Abstract: Large language models demonstrate increasingly strong reasoning capabilities through effective post-training. Yet, prevailing post-training methods optimize over massive numbers of tokens, implicitly assuming that effective learning must be token-intensive. We revisit th…
arxiv.org11 days agoView details
arXiv:2609.04286v1 Announce Type: new Abstract: Artificial intelligence in recruitment has shifted the object being automated from profile pairs and ranked lists to multi-stage workflows that retrieve evidence, compare candidates, and support or execute actions. This systematized narrative review traces that developme…
arxiv.org11 days agoView details
arXiv:2609.04543v1 Announce Type: new Abstract: A key challenge in reliable LLM deployment is recognizing when uncertainty reflects irreducible variability in the task rather than limitations in the model's knowledge. In language tasks, a central source of such aleatoric uncertainty is input ambiguity or underspecific…
arxiv.org11 days agoView details
arXiv:2609.04714v1 Announce Type: new Abstract: Striking a balance between helpfulness and safety remains a fundamental challenge in aligning large language models. To achieve this balance, models should refuse harmful queries (e.g., "How do I shoot someone?") while remaining responsive to benign inputs, even those su…
arxiv.org11 days agoView details
CAGE: Coherence-Aware Graph Encoding for Retrieval-Augmented Generation
arXiv:2609.04647v1 Announce Type: new Abstract: Traditional Retrieval-Augmented Generation (RAG) systems score each passage independently against the query, assembling context sets that may be individually relevant yet collectively incoherent. We introduce Coherence-Aware Graph Encoding (CAGE), a reranking framework t…
arxiv.org11 days agoView details
Controlling and Assessing Appropriate Persona Use in LLM-based Dialogue Generation
arXiv:2609.04676v1 Announce Type: new Abstract: In persona-based dialogue generation (PDG), LLMs often overuse persona attributes by incorporating them regardless of dialogue context, resulting in unnatural responses. Despite its practical significance, the underlying causes remain unexplored, with no method to mitiga…
arxiv.org11 days agoView details
CC-Mediation: Evaluating Large Language Models for Cross-Cultural Conflict Mediation
arXiv:2609.04855v1 Announce Type: new Abstract: Cross-cultural mediation by large language models (LLMs) requires deciding both when to intervene and how to respond in culturally grounded conflicts. Progress on this problem has been limited by the lack of (1) mediation datasets with measurable downstream effects and (…
arxiv.org11 days agoView details
arXiv:2609.04898v1 Announce Type: new Abstract: Repository-scale refactoring requires coding agents to propagate a single change across many interdependent files without altering program behavior, yet to our knowledge no existing harness isolates the design choices that determine agent success on this task. We present…
arxiv.org11 days agoView details
PetQA: Benchmarking Veterinary Knowledge and Clinical Reasoning
arXiv:2609.04598v1 Announce Type: new Abstract: We introduce PetQA, a Korean long-form question-answering (QA) benchmark for evaluating veterinary knowledge and clinical reasoning in large language models (LLMs) and large vision-language models (LVLMs). PetQA contains 10,076 text-only and 8,751 multimodal QA pairs der…
arxiv.org11 days agoView details
A Structured Debate-Mixture-of-Agents Framework for Complex Clinical Diagnostic Decision Support
arXiv:2609.05069v1 Announce Type: new Abstract: Large language models (LLMs) show potential for medical tasks, but their single-turn question-answer format does not reflect how clinical diagnosis is performed in practice. As a result, they remain limited in complex diagnostic settings. We developed Debate-Mixture-of-A…
arxiv.org11 days agoView details
arXiv:2609.05074v1 Announce Type: new Abstract: We propose an influence score to quantify the contribution of attention heads to classification decisions in Transformer-based models designed for prompt injection detection. The score combines directional influence on the logits with structural contribution within the r…
arxiv.org11 days agoView details
arXiv:2609.05221v1 Announce Type: new Abstract: Large language models (LLMs) show strong reasoning ability, but their explanations can remain inconsistent, weakly grounded, or difficult to verify. We propose a verifier-guided explainable reasoning framework for transparent educational question answering that combines…
arxiv.org11 days agoView details
Harness-agnostic detection and immunization of reward hacking in self-evolving language models
arXiv:2609.04665v1 Announce Type: new Abstract: Self-evolving language models improve by proposing candidate updates and keeping whatever raises a visible score. When that score is an imperfect proxy for the capability one actually wants, sustained selection widens the gap between the two. This is reward hacking. We i…
arxiv.org11 days agoView details
Reinforcement Learning for improving Large Language Models' Catalan text simplification capabilities
arXiv:2609.04823v1 Announce Type: new Abstract: Although automatic text simplification (ATS) is critical for accessibility, its progress has not matched the rapid evolution of broader natural language processing techniques. This paper investigates the application of reinforcement learning (RL) to improve the quality o…
arxiv.org11 days agoView details
Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challenges
arXiv:2609.04778v1 Announce Type: new Abstract: Diffusion language models (DLMs) offer a non-autoregressive alternative for mobile edge agentic artificial intelligence (AI) by refining tokens through iterative denoising rather than left-to-right decoding. Compared with autoregressive Transformer-based large language m…
arxiv.org11 days agoView details
DODR: Deterministic Operator-Driven Reasoning in Latent Space
arXiv:2609.04782v1 Announce Type: new Abstract: Autoregressive (AR) large language models formulate reasoning as token-level probabilistic sampling, which induces three fundamental defects in complex logical reasoning: error accumulation, probability substituting necessity, and the linear-chain information bottleneck.…
arxiv.org11 days agoView details
Whose record is this? Diagnosing and authorizing record use in personalized multimodal models
arXiv:2609.04801v1 Announce Type: new Abstract: Contextualized visual personalization can retrieve a true record yet apply it to the wrong visual subject. We formalize when a record may condition an answer as \emph{record authorization}: subject presence ($P$), record-edge validity ($E$), and answer support ($S$) must…
arxiv.org11 days agoView details
Hierarchical Possession-Aware Graph Pointer Network for Pass Receiver Selection
arXiv:2609.04803v1 Announce Type: new Abstract: Pass receiver selection is a fundamental task in football analytics, aiming to predict the intended receiver under a given game state. This task is challenging with event-centered freeze-frame observations, a broadcast-like setting that provides only partial and variable…
arxiv.org11 days agoView details
MedFlow: Class-Aware Multi-Scale Generation for Medical Time-Series Synthesis
arXiv:2609.04804v1 Announce Type: new Abstract: Synthetic medical time-series generation can alleviate data scarcity and support the development of reliable clinical prediction models. However, existing methods mainly focus on matching the overall distribution and temporal dynamics of real data, which does not necessa…
arxiv.org11 days agoView details
arXiv:2609.04806v1 Announce Type: new Abstract: Financial large language models are increasingly deployed for summarization of reports and disclosures, where numerical hallucination poses significant practical risks. While prior work often attributes such hallucination to insufficient numerical reasoning, this assumpt…
arxiv.org11 days agoView details
MZ-Rain: Moisture-Budget-Guided Zero-Inflated Model for Station-Level Precipitation Nowcasting
arXiv:2609.04864v1 Announce Type: new Abstract: Accurate station-level precipitation nowcasting is critical for agriculture, water resource management, and disaster prevention, which typically is formulated as a time series forecasting problem. However, conventional time-series modeling techniques face two major chall…
arxiv.org11 days agoView details
How Much Does Corpus Choice Change Dependency-Distance Estimates?
arXiv:2609.04223v1 Announce Type: new Abstract: Dependency-distance estimates derived from a single corpus are routinely treated as properties of a language, yet this assumption has not been tested across independently compiled corpora. We compared mean dependency-distance estimates across 38 same-language treebank pa…
arxiv.org11 days agoView details
arXiv:2609.04842v1 Announce Type: new Abstract: Time-series data in clinical settings is crucial for capturing dynamic changes in a patient's health over time, enabling timely diagnosis, personalized treatment, and early detection of critical events. However, the development of clinically reliable and linguistically i…
arxiv.org11 days agoView details
arXiv:2609.04865v1 Announce Type: new Abstract: Skill libraries improve the sample efficiency of agentic reinforcement learning (RL) by enabling large language model (LLM) agents to reuse procedural knowledge. Yet existing paradigms exhibit structural shortcomings: they either decouple skill evolution from policy opti…
arxiv.org11 days agoView details
Memory as transformation: LETHE, a self-referential gan-inspired architecture
arXiv:2609.04289v1 Announce Type: new Abstract: LETHE (Latent-parameter Evolution with Temporal Hierarchical quasi-Equilibrium) is a self-referential sonic-oblivion system implemented in SuperCollider. It adopts the formal vocabulary of Generative Adversarial Networks in a closed configuration without external dataset…
arxiv.org11 days agoView details
When Quantization Breaks Memory: Recurrent-State Write-Back in Low-Precision Temporal Inference
arXiv:2609.04490v1 Announce Type: new Abstract: Quantization is widely used to reduce the computational and memory demands of neural-network inference. In recurrent networks, however, the quantized state is stored and returned at the next time step, so the rule used to store that state can alter subsequent computation…
arxiv.org11 days agoView details
arXiv:2609.04541v1 Announce Type: new Abstract: Digital materials fabricated by multi-material 3D printing are designed as controlled mixtures of stiff and compliant constituents, yielding effective responses that span more than an order of magnitude in apparent stiffness and exhibit strongly nonlinear, composition-de…
arxiv.org11 days agoView details
Data-Optimized Contingency Screening: A Machine Learning Approach to Power System Security
arXiv:2609.04300v1 Announce Type: new Abstract: Ensuring the security of the power system is essential for stability and reliability, especially in the event of disruption. Effective classification of contingency in power systems enables proactive decision-making and mitigates large-scale breakdowns and failures. This…
arxiv.org11 days agoView details
LLM-Assisted Behavioural and Scenario Augmentation for Agent-Based Energy Adoption Models
arXiv:2609.04866v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) create opportunities to enrich simulation-based energy policy analysis, particularly by supporting structured behavioural assumptions and exploratory techno-economic scenarios. However, directly replacing adoption models wi…
arxiv.org11 days agoView details
From Interaction Traces to Persistent Skills: Online Evolution for Computer-Use Agents
arXiv:2609.04869v1 Announce Type: new Abstract: Computer-use agents can execute increasingly complex tasks in graphical interfaces, but their interaction experience is typically transient: procedural knowledge acquired from one rollout is not systematically retained, refined, and reused in later tasks. Existing skill…
arxiv.org11 days agoView details
Recurrence Is Not Enough: Causally Validating Multilingual SAE Translation Features in Gemma 2 and 3
arXiv:2609.04808v1 Announce Type: new Abstract: Sparse autoencoder (SAE) features are increasingly used to explain and steer language-model behavior, but it remains unclear whether a feature found in one language context plays the same causal role when processing prompts in another language. We study this question usi…
arxiv.org11 days agoView details
MARLA: A Conceptual Scaffold for Regulatory Learning under the EU AI Act
arXiv:2609.04877v1 Announce Type: new Abstract: The EU AI Act positions regulation as part of the infrastructure for safe, trustworthy and market-ready innovation. Realising this ambition requires regulatory learning: the evidence generated during implementation must be translated into governance and legal knowledge t…
arxiv.org11 days agoView details
arXiv:2609.04880v1 Announce Type: new Abstract: Designing effective and fiscally sustainable policies for solar photovoltaic (PV) adoption requires balancing adoption gains against public expenditure under uncertainty and heterogeneous decision-making. This study formulates PV policy design as a sequential decision pr…
arxiv.org11 days agoView details
arXiv:2609.04894v1 Announce Type: new Abstract: Large language models become consequential agents when surrounding systems let outputs change external state. Models now call tools, operate interfaces, delegate work, retain state, inhabit generated worlds, and control robots or laboratory equipment. Such advances are o…
arxiv.org11 days agoView details
SQL-Zero: Self-Evolving Text-to-SQL
arXiv:2609.04697v1 Announce Type: new Abstract: Training a competitive Text-to-SQL agent usually depends on human-annotated natural-language/SQL pairs, which are expensive, domain-specific, and a bottleneck for scaling to new databases. We show it is possible to train a competitive solver with zero annotated pairs. We…
arxiv.org11 days agoView details
Vectorizing Classical Tamil: Representation Learning for Verse-Commentary Pairs
arXiv:2609.04755v1 Announce Type: new Abstract: We construct a corpus of 1,262 verse-commentary (urai) pairs from five Classical Tamil source sections, ranging from technical grammatical prose to modern paraphrase, and ask what information representation learning can recover. We train recurrent and Transformer encoder…
arxiv.org11 days agoView details
Iris: Climbing to the Search Frontier
arXiv:2609.04304v1 Announce Type: new Abstract: We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe behind them. Tasks are reverse-constructed from the hyperlink structure of a web corpus: we author multi-hop chains over…
arxiv.org11 days agoView details
ElderBench: Benchmarking Autonomous Mobile Agents for Older Adults
arXiv:2609.04850v1 Announce Type: new Abstract: While autonomous mobile agents hold great potential for assisting older adults with smartphone usage, existing GUI benchmarks mainly rely on explicit, goal-oriented instructions and rarely capture the naturally occurring language patterns of older users, such as indirect…
arxiv.org11 days agoView details
arXiv:2609.04715v1 Announce Type: new Abstract: Personalizing large language models (LLMs) is essential for delivering AI assistance that aligns with individual users' styles, intents, and preferences. While per-user fine-tuning can substantially enhance personalization quality, it introduces significant parameter and…
arxiv.org11 days agoView details
Aplaud: Adaptive Personalized Low-Rank Decomposition for User-Specific LLM
arXiv:2609.04738v1 Announce Type: new Abstract: In this paper, we study the problem of personalized survey response prediction using fine-tuned large language models (LLMs). This task poses unique challenges: limited per-user training data, scalability of model storage, and the need to exploit shared structure across…
arxiv.org11 days agoView details
DCFA: Dual-view Causal-inspired Attribution for Failure Reasoning in LLM-based Multi-agent Systems
arXiv:2609.04749v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems have experienced rapid growth in recent years. Despite their promise, such systems remain fragile, frequently exhibiting reasoning and coordination errors that can lead to system-level failures. Failure attribution in…
arxiv.org11 days agoView details
Discourse Dependency: A Continuous Criterion for Translation Difficulty
arXiv:2609.04959v1 Announce Type: new Abstract: Recent calls for harder machine translation benchmarks have not clarified what difficulty should mean. We argue that one meaningful and currently unmeasured axis is referential reach, the distance a segment must look back into its document to resolve the entities and pro…
arxiv.org11 days agoView details
Rhythms of Work: Multi-Scale Interpretation of Human Behavioral Traces for Workplace Agents
arXiv:2609.04556v1 Announce Type: new Abstract: Runtime traces are becoming a central substrate for understanding agentic systems, yet interpretation has focused largely on what the agent did. Workplace agents face the complementary problem: interpreting the human activity that surrounds them. Hours of low-level event…
arxiv.org11 days agoView details
Evaluation of Phonetic Encoding Algorithms on Transcription Datasets
arXiv:2609.04391v1 Announce Type: new Abstract: In this work, a novel evaluation scheme built on a generalized variant of the Rand Index measure, namely, the H\"ullermeier-Rifqi Index, is proposed in order to assess how well phonetic encoding algorithms conform to word-based transcriptions in IPA (International Phonet…
arxiv.org11 days agoView details
Tracing Audio Grounding and Answer Selection in Audio LLMs
arXiv:2609.04637v1 Announce Type: new Abstract: Audio Large Language Models (Audio LLMs) have advanced in audio understanding, yet they can still predict the answer by reasoning from textual cues or linguistic priors rather than the provided audio. A common remedy is to train models on data whose answers cannot be inf…
arxiv.org11 days agoView details
AutoLR: Automating the Path from Research to Launch Review in Industrial Recommender Systems
arXiv:2609.04871v1 Announce Type: new Abstract: Improving an industrial recommender is an iterative research-and-engineering process rather than a direct path from idea to deployment. In \textbf{DASHEN, NetEase's gaming-community app}, algorithm engineers typically identify promising directions from research papers, t…
arxiv.org11 days agoView details
arXiv:2609.04999v1 Announce Type: new Abstract: This paper describes the participation of the BIT.UA team from the University of Aveiro in the 14th edition of the BioASQ Task B challenge on biomedical question answering. Building on our previous submissions, we introduced a substantially refactored and modular codebas…
arxiv.org11 days agoView details
arXiv:2609.05022v1 Announce Type: new Abstract: This paper presents new tokenization resources for Irish and evaluation measures of alignment with the morphological boundaries of the language. We present MoirfEolas, a dataset of over 35,000 Irish words mapped to their respective eclipses, prefixes and suffixes as well…
arxiv.org11 days agoView details
LentEx: Generalizable Latent Entity Extraction via Synthetic Data and Instruction-Tuned LLMs
arXiv:2609.04511v1 Announce Type: new Abstract: Latent entity extraction (LEE) tackles the challenge of identifying implicit, contextually inferred entities within free text-an area where traditional entity extraction methods fall short. In this paper, we introduce LentEx, a novel framework for latent entity extractio…
arxiv.org11 days agoView details
Leveraging Low-Level Symbolic Competences for Unsupervised Grounding in Hallucination Detection
arXiv:2609.05025v1 Announce Type: new Abstract: Hallucination-where a language model generates outputs that are factually incorrect or unsupported by the source-is a major challenge for both prompted and fine-tuned language models. Detecting hallucinations is difficult due to the opaque reasoning processes of LLMs, wh…
arxiv.org11 days agoView details
arXiv:2609.05037v1 Announce Type: new Abstract: As LLMs take on roles requiring moral advice, understanding how they attribute moral agency becomes critical. Humans possess moral agency, the capacity to make ethically guided decisions and bear responsibility for their consequences, a well-established construct in mora…
arxiv.org11 days agoView details
arXiv:2609.04579v1 Announce Type: new Abstract: Grounded language-model pipelines can be divided into three stages: selecting an object, retrieving passages for it, and using that evidence to answer. If the selected object must reach the reader, losing it breaks the handoff. Benchmark recall checks the dataset-linked…
arxiv.org11 days agoView details
arXiv:2609.04859v1 Announce Type: new Abstract: As vision-language models (VLMs) rapidly advance in image understanding, cross-modal reasoning, and complex instruction execution, instruction-following capability has become a key indicator of their reliability and practicality. However, existing multimodal instruction-…
arxiv.org11 days agoView details
EuroAlpaca: Task-Preserving Localisation of Instruction Data for European Languages
arXiv:2609.05043v1 Announce Type: new Abstract: Machine translation (MT) offers a scalable way to extend English instruction-tuning data to multiple languages, but it can distort task-critical constraints and required outputs, creating corrupted training examples and degrading models trained on such data. We introduce…
arxiv.org11 days agoView details
CHAMP: Cross-domain Hybrid Architecture for Matchmaking and Prediction in Online Multi-Player Games
arXiv:2609.04870v1 Announce Type: new Abstract: Multiplayer Online Battle Arena (MOBA) games rely on matchmaking to maintain competitive balance. Our prior work, CUPID, framed matchmaking as an assignment re-optimization problem and showed that a single-mode win-rate predictor can meaningfully rebalance teams. However…
arxiv.org11 days agoView details
NS-ST-GraphRAG: Neuro-Symbolic Spatio-Temporal GraphRAG for Literary Knowledge Processing
arXiv:2609.05139v1 Announce Type: new Abstract: Long-form literary narratives pose a distinctive information-processing challenge for retrieval-augmented generation: relevant evidence is distributed across chapters, relations evolve over narrative time, and correct answers may depend jointly on temporal, spatial, and…
arxiv.org11 days agoView details
A Human-in-the-Loop Framework for AI-Assisted Scoring in Large-Scale Writing Assessment
arXiv:2609.05143v1 Announce Type: new Abstract: The integration of artificial intelligence (AI), particularly large language models (LLMs), into educational assessment has opened new opportunities to enhance the efficiency and scalability of grading processes. This study presents the design and validation of an AI-ass…
arxiv.org11 days agoView details
From Vision to Language: Investigating Causal Information Flow in Multimodal Decision-Making
arXiv:2609.05149v1 Announce Type: new Abstract: Vision-Language Models are commonly evaluated through their final predictions, but understanding whether these decisions are grounded in visual evidence requires tracing how visual information contributes to language-based decisions. With this purpose in mind, we investi…
arxiv.org11 days agoView details
Compression Beyond the Uncompressed: A Two-Stage Training Recipe for Soft Context Compression in RAG
arXiv:2609.05152v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances language models with external knowledge, but the lengthy retrieved context inflates the input and degrades inference efficiency. Soft context compression encodes each document into a substantially shorter embedding sequence.…
arxiv.org11 days agoView details
PerfReasoning: How Well Do LLMs Reason on Hardware Performance?
arXiv:2609.04476v1 Announce Type: new Abstract: Performance modeling is central to hardware design and software optimization, yet constructing these models requires structured reasoning about computation, data reuse, storage, and movement. We introduce PerfReasoning, a benchmark that evaluates LLMs both as direct perf…
arxiv.org11 days agoView details
arXiv:2609.05189v1 Announce Type: new Abstract: Assessing the impacts of social policy changes is a widely acknowledged challenge for policymakers. Econometric methods can be unreliable when extrapolating to hypothetical scenarios, while field pilot programs are highly costly. In this paper, we propose using large lan…
arxiv.org11 days agoView details
$\tau^\tau$-Bench: An Environment for End-To-End, Realistic Agent Construction
arXiv:2609.04611v1 Announce Type: new Abstract: LLM agents are rapidly becoming production software, deployed to handle customer service, adjudicate disputes, and operate internal systems. Notably, the work of building them is increasingly handed to coding agents, yet existing benchmarks say little about whether an AI…
arxiv.org11 days agoView details
arXiv:2609.04298v1 Announce Type: new Abstract: Evaluating agents on the growing number of agentic benchmarks is challenging because they often require complex environments and agent integrations. We introduce Harbor Adapters, a unified evaluation infrastructure for agentic benchmarks. Our work makes three contributio…
arxiv.org11 days agoView details
La Agente \'Optima: Towards Agentic Self-Driving Laboratories
arXiv:2609.04564v1 Announce Type: new Abstract: Self-driving laboratories (SDLs) combine automated experimentation with adaptive decision-making to accelerate scientific discovery. Their operation nevertheless often depends on human specialists who translate scientific objectives into executable closed-loop campaigns.…
arxiv.org11 days agoView details
What Attention Recalls and Recurrence Controls in Hybrid Language Models
arXiv:2609.04434v1 Announce Type: new Abstract: Hybrid language models combine attention with a fixed-size recurrent state, but the role of each channel remains unclear. We introduce two cache-level interventions. Split-prefill keeps only the KV cache or only the recurrent state from a prefilled context, then generate…
arxiv.org11 days agoView details
Improving Language Identification for Code-Switched Utterances with Integer Linear Programming
arXiv:2609.05099v1 Announce Type: new Abstract: Automatic identification of code-switched (CS) utterances remains a challenge for language identification (LID) systems, causing such texts to be underrepresented in the training data of Large Language Models. In this paper, we revisit MaskLID, a state-of-the art approac…
arxiv.org11 days agoView details
ProtLingo: Efficient Protein Language Modeling via Conditional Memory and Expert Routing
arXiv:2609.04793v1 Announce Type: new Abstract: Proteins perform diverse cellular functions, and even single amino-acid substitutions can alter stability, activity, or molecular interactions. Protein language models (PLMs) provide a scalable approach for modeling such sequence--function relationships from unlabeled se…
arxiv.org11 days agoView details
Choosing the Right Language Mode at Inference Time for Multilingual Reliability
arXiv:2609.04653v1 Announce Type: new Abstract: Multilingual large language models often struggle to reason in low- to mid-resource languages. Prior work has shown that translation can improve multilingual reasoning by helping models access stronger English-centric representations. This raises a central question: How…
arxiv.org11 days agoView details
CPR-IE:A Compression-Prediction-Resource Intelligence Efficiency Metric
arXiv:2609.04809v1 Announce Type: new Abstract: Comparing intelligent systems under deployment constraints requires more than predictiveaccuracy.This paper develops Compression-Prediction-Resource Intelligence Efficiency (CPR-IE) as a protocol-relative ordering by representational economy, predictive quality, and reso…
arxiv.org11 days agoView details
Long Horizon Transformer Quantile Fault Prediction for Multi Site Industrial Predictive Maintenance
arXiv:2609.04840v1 Announce Type: new Abstract: Long-horizon predictive maintenance requires models to distinguish slowly evolving degradation from normal operating-regime variation over planning windows measured in days rather than hours. This paper evaluates whether an explicit conditional-quantile representation pr…
arxiv.org11 days agoView details
Towards Understanding Pause Token Fine-Tuning Dynamics: A Mode Retention Perspective
arXiv:2609.04489v1 Announce Type: new Abstract: Pause-token methods improve LLM reasoning by inserting special tokens into sequences. Prior work explains these gains through computational expressivity. However, there is relatively little investigation into the training dynamics of pause tokens. We explore how pause to…
arxiv.org11 days agoView details
Evidence Integration in Large Language Models
arXiv:2609.04290v1 Announce Type: new Abstract: Despite increasing reliance on LLMs that reason with external evidence supplied by tools, retrieval-augmented generation, other agents, and users, how LLMs integrate such evidence into decisions they have already begun to form remains largely unclear. We present a distri…
arxiv.org11 days agoView details
arXiv:2609.04350v1 Announce Type: new Abstract: How do people learn to become better conversationalists? This question is especially important in the context of mental-health counseling, where conversational skills are essential, yet volunteer counselors often have limited access to supervision and structured feedback…
arxiv.org11 days agoView details
MedProb: Probing Internal Representations of Vision-Language Models for Medical Question Answering
arXiv:2609.04336v1 Announce Type: new Abstract: Medical visual question answering (Med-VQA) is often assumed to require medical fine-tuning, large models, or complex multi-agent pipelines. We revisit this assumption with \textbf{MedProb}, a lightweight probing framework that predicts multiple-choice Med-VQA answers fr…
arxiv.org11 days agoView details
GRACE: Graph-Grounded Reflective Agent Copilot Engine for Expert-in-the-Loop Knowledge Expansion
arXiv:2609.04442v1 Announce Type: new Abstract: Large language models deployed in high-stakes settings frequently generate plausible but ungrounded claims. Standard retrieval-augmented generation (RAG) pipelines offer limited remedy, since they retrieve isolated passages without tracking cross-document evidence relati…
arxiv.org11 days agoView details
TRILOGUE: A Trilingual Spoken Dialogue Fact-Checking Benchmark with Evidence and Paired Audio
arXiv:2609.04452v1 Announce Type: new Abstract: Modern misinformation is often heard before it is read, yet fact-checking systems are still evaluated mainly on clean written claims. Spoken dialogue remains different even when systems operate on transcripts: claims may be distributed across speakers and turns, depend o…
arxiv.org11 days agoView details
Shared circuits predict whether LLMs generalize across formats in arithmetic reasoning
arXiv:2609.04463v1 Announce Type: new Abstract: In many forms of reasoning, including arithmetic reasoning, generalizing across superficial changes in input format is effortless for humans: anyone who can solve 2+5 can also solve 'two plus five'. In contrast, LLMs are more brittle to surface variations of the prompts:…
arxiv.org11 days agoView details
arXiv:2609.04484v1 Announce Type: new Abstract: This paper investigates structural priming in language model (LM) production, examining how preceding structural context influences sentence completion. While prior work has demonstrated priming effects in comprehension of structural alternations, it remained unclear whe…
arxiv.org11 days agoView details
arXiv:2609.04366v1 Announce Type: new Abstract: Early-onset colorectal cancer is increasing among younger adults, yet red-flag symptoms in this age group have no evidence-based guidelines for follow-up testing, and structured encounter data do not capture the detail needed to support early detection and inform follow-…
arxiv.org11 days agoView details
arXiv:2609.04384v1 Announce Type: new Abstract: Chinese online comments often convey social meaning through indirect and playful language that is hard to interpret without context. Existing evaluations largely organize items around predefined phenomena or controlled pragmatic categories, leaving open whether models ca…
arxiv.org11 days agoView details
Models
View all models →jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4
text-generation · llama.cpp · gguf · qwen
huggingface.co12 days ago11 ptsView details
gguf · dataset:rahul7star/gemma4-opus-reasoning-12k · base_model:google/gemma-4-12B-it
huggingface.co12 days ago2 ptsView details
text-generation · litert-lm · litert · litertlm
huggingface.co12 days ago1 ptsView details
AbhishekG711/Qwen3-0.6B-Insight-Extractor
text-generation · transformers · safetensors · qwen3
huggingface.co12 days agoView details
text-generation · transformers · safetensors · qwen2_5_omni
huggingface.co12 days agoView details
text-generation · transformers · safetensors · malayalam_moe
huggingface.co12 days agoView details
text-generation · transformers · safetensors · gpt2
huggingface.co12 days agoView details
Wondernutts/Chimera-X-26B-A4B-int4-ov
image-text-to-text · openvino · gemma4 · int4
huggingface.co12 days agoView details