News / #reasoning Tag Reasoning 500 articles archived under #reasoning · RSS Sign in to follow Hugging Face Daily Papers research 27d ago Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents Abstract Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that an output is correct decides what to ship, what to escalate, and what to retry. Existing confidence estimators,… 16 arXiv — Machine Learning research 27d ago When the Gradient Sees Rank: Provable Necessity, Causal Recruitment, and Composition in Trained Matrix Memories arXiv:2609.17594v1 Announce Type: new Abstract: Can gradient-based training learn the rank needed to store and compose associations in a matrix memory? In our earlier study, we used a matrix-augmented reasoner on a task that admits a rank-1 solution, leaving this question open.… 9 arXiv — NLP / Computation & Language research 27d ago The Missing "I Don't Know": Why Three Reasoning-Reliability Findings Converge on Calibrated Abstention arXiv:2609.17686v1 Announce Type: cross Abstract: Three recent results describe what look like unrelated LLM reliability problems. Yin et al. (2026) show reasoning RL collapses tool-reliability representations. Suleymanov et al. (2026) show that under safety-constrained… 25 arXiv — Machine Learning research 27d ago Bias Amplification in Multi-Agent Network: How Biased Agents Shape Opinions and Rhetoric arXiv:2609.18306v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in applications involving interaction between agents, where their output plays a role in collective reasoning and decision-making processes. Despite significant research into… 16 arXiv — Machine Learning research 27d ago Label-free steering: Compressing test-time reinforcement learning into bias-only subspaces arXiv:2609.18587v1 Announce Type: new Abstract: Test-time reinforcement learning (TTRL) enables models to improve their reasoning without relying on labeled training data, but existing approaches typically optimize a large fraction of the model parameters. This raises a natural… 12 arXiv — NLP / Computation & Language research 27d ago Does Moral Reasoning Training Help or Hurt? Red-Teaming RL-Trained Ethical Agents with Persona Attacks arXiv:2609.17552v1 Announce Type: new Abstract: Moral-reward RL can make language-model agents more cooperative, but whether that alignment survives adversarial persona pressure is unknown. Such attacks are realistic: retrieved context, tool outputs, or multi-turn framing can… 10 arXiv — NLP / Computation & Language research 27d ago Confidence Comes from Experience: Experiential Confidence Estimation from Reasoning to Agents arXiv:2609.17708v1 Announce Type: new Abstract: Reliable confidence estimation is increasingly central to the trustworthy deployment of language models: a calibrated estimate of the probability that an output is correct decides what to ship, what to escalate, and what to retry.… 35 arXiv — NLP / Computation & Language research 27d ago Attention Dispersion as a Diagnostic Signal for Hallucination in Large Language Models arXiv:2609.18320v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit hallucinations, presenting a major barrier to reliability in complex reasoning tasks. While traditional detection methods rely on output-based confidence metrics, these logits are… 35 arXiv — NLP / Computation & Language research 27d ago Voice of Reason: Reinforcement Learning for Spoken Math arXiv:2609.18677v1 Announce Type: new Abstract: Speech language models enable richer spoken interactions between humans and machines than cascaded systems, allowing access to paralinguistic information and lower latency. However, their accuracy on mathematical reasoning… 16 arXiv — NLP / Computation & Language research 27d ago WordPolo: Evaluating Language Models Through Iterative Semantic Feedback arXiv:2609.19006v1 Announce Type: new Abstract: Large Language Models (LLMs) and Large Reasoning Models (LRMs) are typically evaluated on challenging benchmarks through dataset accuracy alone, providing no insight into the quality or faithfulness of their reasoning processes. We… 23 r/MachineLearning community 28d ago GoBench: Evaluating LLMs on the game of Go [R] GoBench evaluates LLMs on 9x9 Go games against a ladder of KataGo opponents, from random to superhuman. It measures general reasoning ability, strongly correlates with ARC-AGI 2 (r=0.83 correlation), and remains highly unsaturated. GPT-6 Astra max achieves 2500 Elo, much lower… 7 llama.cpp releases dev-tools 28d ago b10996 chat : force \n</think> on reasoning budget end for qwen3-coder ( #28869 ) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/47858837 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS… 29 arXiv — Machine Learning research 28d ago Distilling Foundation Models for Agentic What-If Reasoning:Cost, Latency, and Governance in a Hybrid LLM+SLM Architecture arXiv:2609.16091v1 Announce Type: new Abstract: Tabular foundation models deliver strong zero-training predictive performance via in-context learning, but their high inference latency makes them impractical as hot-path decision backends in interactive agentic loops. We distill a… 34 arXiv — Machine Learning research 28d ago Efficient Reasoning Distillation: Small Video-Language Models via Synthetic CoT and Difficulty-Aware Fine-Tuning arXiv:2609.16255v1 Announce Type: new Abstract: We present an efficient method to distill reasoning capabilities into compact video-language models (VLMs) for video question answering (VideoQA). Our approach fine-tunes a 2B-parameter model using only $\sim$900… 21 arXiv — Machine Learning research 28d ago OPD-Aha: From Linguistic Momentum to Visual Reflection in Multimodal On-Policy Distillation arXiv:2609.16459v1 Announce Type: new Abstract: Privileged on-policy distillation improves multimodal reasoning by allowing a teacher to evaluate student trajectories using rich, training-only visual evidence. Both models score these trajectories while conditioning on the same… 26 arXiv — Machine Learning research 28d ago Right Direction, Wrong Step: Geometric Analysis of Finite-Step Failure in Looped Transformers arXiv:2609.16665v1 Announce Type: new Abstract: Looped Transformers offer a parameter-efficient route to test-time scaling by reusing shared layers for iterative latent reasoning. However, additional iterations can reduce support for a reference answer, leaving unclear whether… 10 arXiv — NLP / Computation & Language research 28d ago State of Thought Enables Endogenous Reasoning arXiv:2609.16055v1 Announce Type: new Abstract: Test-time compute has emerged as a major approach to improving the capabilities of Large Language Models (LLMs). However, existing test-time reasoning paradigms rely heavily on externally imposed control, either through fixed… 10 arXiv — NLP / Computation & Language research 28d ago Efficient Multimodal Generative Recommendation with Latent Narrative Reasoning arXiv:2609.16070v1 Announce Type: new Abstract: Generative recommendation reformulates item prediction as semantic identifier generation, yet episodic content introduces a fundamentally different setting where the target is determined by narrative evolution rather than user… 4 arXiv — NLP / Computation & Language research 28d ago The Imitation Game: When LLMs Learn to Reason Like Programs via Code-Centric Reasoning Data Synthesis arXiv:2609.16076v1 Announce Type: new Abstract: Large Language Models (LLMs) excel at programming tasks but frequently fail at deterministic, fine-grained reasoning in natural language, relying heavily on semantic approximations rather than robust symbolic execution. To bridge… 19 arXiv — NLP / Computation & Language research 28d ago Spurious Tool Use: When RL Agents Learn the Wrong Reason to Act arXiv:2609.16268v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly interleave natural language reasoning with external tools such as web search and code execution. These tool-use policies are often optimized via reinforcement learning (RL), which can… 18 arXiv — NLP / Computation & Language research 28d ago Register Tokens for Bounded-State Reasoning in Diffusion Language Models arXiv:2609.16372v1 Announce Type: new Abstract: Masked diffusion language models (dLLMs) generate text by iteratively denoising masked tokens with bidirectional attention. Extending reasoning across generation chunks normally requires keeping earlier generated text in context.… 9 arXiv — NLP / Computation & Language research 28d ago PunGraph: Retrieval-Enhanced Phonetic-Semantic Graph Reasoning for Pun Understanding arXiv:2609.16557v1 Announce Type: new Abstract: Puns are a challenging form of figurative language that exploit phonetic similarity and semantic ambiguity to convey multiple meanings. Although large language models (LLMs) demonstrate strong language understanding capabilities,… 6 arXiv — NLP / Computation & Language research 28d ago Rewarding Reasoning, Not Answers: Fixing and Bounding Test-Time Reinforcement Learning on Medical QA arXiv:2609.16660v1 Announce Type: new Abstract: Test-time reinforcement learning adapts a model on its own unlabeled test set using majority-vote pseudo-labels and has shown strong results in mathematics. We show that this recipe collapses on medical multiple-choice QA: accuracy… 7 arXiv — NLP / Computation & Language research 28d ago Deconstructing Stereotypes: Scope-Conditioned Generation for Effective Multilingual Counterspeech arXiv:2609.16906v1 Announce Type: new Abstract: Counterspeech (CS) - direct responses that counter online Hate Speech (HS) using reasoning and alternative viewpoints - has emerged as an alternative to content removal. Current automatic CS generation methods, however, frequently… 37 Google DeepMind official-blog 29d ago Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking Introducing Gemini 3.8 Live and 3.8 Live Extended Thinking Sep 15, 2026 | x.com Facebook LinkedIn Mail Gemini 3.8 Live and Gemini 3.8 Live Extended Thinking are our most advanced live dialogue models yet. Major upgrades in intelligence and parallel reasoning make them more… 20 r/LocalLLaMA community 29d ago Cut Qwen3.8-27B Reasoning Tokens by 40% -- 3.8 'ThinkingCap' benchmarked! I doubt I'm in the minority here when I say I love Qwen models, but the overthinking is a major timekiller. It was bad in 3.6-27B, and it's worse in 3.8. I know there are some who say, "well that's how it achieves such a good performance/size ratio"... But now there's some… 36 TechCrunch — AI news-outlet 29d ago Salesforce and Nvidia’s new reasoning model is everything the AI labs should fear Salesforce Koa is built on Nvidia's open-weight Nemotron model and is trained to do sales, marketing and customer-support tasks. 14 arXiv — Machine Learning research 29d ago Training Specialist Models without Reasoning Trajectories for Domain Expert Distillation arXiv:2609.13770v1 Announce Type: new Abstract: Specialist distillation effectively transfers domain expertise to student models via teacher-generated reasoning trajectories. However, when these specialists are trained solely on question--answer pairs without explicit reasoning… 34 arXiv — Machine Learning research 29d ago Does Reasoning Improve Psychological Depth in Large Language Models? It Depends on Who's Judging arXiv:2609.13773v1 Announce Type: new Abstract: LLM-as-a-Judge evaluators are increasingly used to score open-ended generation, yet a judge's correlation with human ratings on its development set may not guarantee valid measurement when outputs are closely matched and human… 38 arXiv — NLP / Computation & Language research 29d ago PhysMent: An Interactive Approach For LLM Reasoning In Physics Problems arXiv:2609.13152v1 Announce Type: new Abstract: Large language models (LLMs) perform strongly on static science benchmarks, yet their ability to reason about the physical world through active experimentation remains poorly understood. We introduce PhysMent, a benchmark that… 18 arXiv — NLP / Computation & Language research 29d ago Lexical Prompt Compression for Large Language Models: A Training-Free, Deterministic Pipeline with Empirical Pareto Analysis Across Eleven Task Categories arXiv:2609.13154v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have made prompts increasingly large and complex. Techniques such as chain-of-thought reasoning (Wei et al., 2022) and in-context learning (Brown et al., 2020) frequently push… 36 arXiv — NLP / Computation & Language research 29d ago TestHallVQA: Exploring LVLMs' Document-Level Reasoning under Redundant Contexts from Scientific Exams arXiv:2609.13158v1 Announce Type: new Abstract: Large Vision--Language Models (LVLMs) are increasingly expected to perform visual question answering (VQA) over planar media. However, existing planar VQA benchmarks typically emphasize isolated challenges: some emphasize… 13 arXiv — NLP / Computation & Language research 29d ago Clinical Reasoning Under a Partially Observed Objective in Cone Beam CT Report Generation arXiv:2609.13238v1 Announce Type: new Abstract: Maxillofacial report generation from cone beam computed tomography is scored here by a composite objective placing 80% of its weight on a large language model judgement of factual entailment and 20% on lexical overlap, of which… 20 arXiv — NLP / Computation & Language research 29d ago RFCLLM: Evaluating LLMs' Reasoning Ability of Network Protocol State Machines arXiv:2609.13389v1 Announce Type: new Abstract: Mapping textual specifications into formal representations is essential for ensuring the correctness of protocol designs and implementations. LLM-generated mappings, used for networking security or testing, are assumed to capture a… 13 arXiv — NLP / Computation & Language research 29d ago Hindsight Bias in Clinical Temporal Reasoning: How Future Data Exposure Affects Large Language Model Judgment arXiv:2609.13454v1 Announce Type: new Abstract: Clinical decisions are prospective, but clinical language models are often evaluated on retrospective records that reveal the final diagnosis, treatment response, and outcome. Such evaluations may reward the use of future… 19 arXiv — NLP / Computation & Language research 29d ago From Token Probabilities to Semantic Constraints: Towards Declarative Probabilistic Evaluation of Language Models arXiv:2609.13520v1 Announce Type: new Abstract: While Large Language Models have improved rapidly, many fundamental questions remain about how to evaluate the knowledge and reasoning abilities they acquire, and how such evaluations relate to the learning signals used in… 31 arXiv — NLP / Computation & Language research 29d ago SyRHM: Symbolic-Language-Enhanced Reasoning with Associative Retrieval for Zero-shot Harmful Meme Detection arXiv:2609.13794v1 Announce Type: new Abstract: Detecting harmful memes is critical for maintaining safe online communities. However, harmful intent is often implicit, arising from visual-textual incongruity and cultural stereotypes, which challenges existing multimodal… 15 arXiv — NLP / Computation & Language research 29d ago DARE: Dialectical Agentic Reasoning for Structured Knowledge Fact Checking arXiv:2609.13808v1 Announce Type: new Abstract: Structured knowledge fact checking aims to determine the truthfulness of natural language claims by reasoning over structured evidence. Recent program-generation approaches leverage large language models (LLMs) to generate… 34 arXiv — NLP / Computation & Language research 29d ago Thought without systematicity? Evaluating reasoning models on rule induction tasks arXiv:2609.13948v1 Announce Type: new Abstract: A central tenet of human cognition is systematicity, the principle that understanding one concept is inherently tied to understanding close variations of that concept. Do reasoning models robustly exhibit such systematicity? If so,… 6 arXiv — NLP / Computation & Language research 29d ago Unlocking the Unsolvable: Teacher-Guided Curriculum for Data-Efficient RLVR arXiv:2609.13997v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has shown remarkable success in improving the mathematical reasoning of large language models. Yet problems beyond the model's current capability, where rollouts uniformly fail… 25 arXiv — NLP / Computation & Language research 29d ago GraMRAG: Orchestrating Multi-Agent Multi-Step Reasoning via Graph Memory with Reinforcement Learning arXiv:2609.14066v1 Announce Type: new Abstract: Although existing multi-agent Retrieval-Augmented Generation (RAG) systems have demonstrated promise on complex multimodal reasoning tasks, they remain fundamentally limited in reasoning depth and memory structure, suffering from… 32 arXiv — NLP / Computation & Language research 29d ago E2A-Bench: Benchmarking Evidence-to-Action Reliability in Financial Chart Reasoning arXiv:2609.14302v1 Announce Type: new Abstract: Can financial vision-language models (VLMs) turn chart evidence into reliable action recommendations? Existing hallucination evaluations are mostly claim-centric; they assess whether generated statements are supported, but not… 6 arXiv — NLP / Computation & Language research 29d ago Building Legal Reward Models for Grounding and Abstention arXiv:2609.14739v1 Announce Type: new Abstract: Large language models are increasingly used in high-stakes domains such as law, where systems must ground their reasoning in retrieved evidence and abstain when that evidence is insufficient. However, existing reward models are… 29 arXiv — NLP / Computation & Language research 29d ago Func-R1: Incentivizing Mathematical Function Reasoning in Multimodal Large Language Models arXiv:2609.14779v1 Announce Type: new Abstract: Performing deliberate mathematical reasoning in visual contexts is a hallmark of advanced Multimodal Large Language Models (MLLMs) and requires a sophisticated synthesis of perceptual grounding and symbolic logic. However, in the… 30 arXiv — NLP / Computation & Language research 29d ago MedTRACE: Tool-Augmented Multimodal Clinical Reasoning Agents for Evidence-Grounded Decision-Making arXiv:2609.14823v1 Announce Type: new Abstract: Multimodal clinical decision-making requires reliable reasoning over heterogeneous evidence from electronic health records, medical images, and physiological signals. Existing models typically map these inputs directly to diagnoses… 30 arXiv — NLP / Computation & Language research 29d ago Forty Shades of Blue: Quality-Diversity Alignment via Mode-Conditioned Reinforcement Learning arXiv:2609.14896v1 Announce Type: new Abstract: A notable byproduct of LLM alignment training is mode collapse: the progressive loss of output diversity that narrows a model's expressivity at inference time. This degradation is especially limiting for applications requiring… 27 arXiv — NLP / Computation & Language research 29d ago Beyond Depth and Width: The Information-Slack Dilemma in Streaming Test-Time Compute arXiv:2609.14995v1 Announce Type: new Abstract: The same task and compute budget can require different reasoning policies when evidence arrives in a different order. Early computation has more time to finish but rests on incomplete or revisable evidence; waiting improves… 37 arXiv — NLP / Computation & Language research 29d ago ABSOL: Aggregated Bayesian Subsampling Orchestrated with LLMs arXiv:2609.15007v1 Announce Type: new Abstract: Large language models are increasingly used as natural-language interfaces to structured data, yet they remain unreliable when answers require consistent evidence conditioning, dependency-aware reasoning, and uncertainty… 24 arXiv — NLP / Computation & Language research 29d ago Improving Mathematical Reasoning Capabilities in Large Language Models via Reasoning Process Error Classification arXiv:2609.15145v1 Announce Type: new Abstract: The reasoning ability of large language models (LLMs) is a critical factor for practical LLM-based applications. To investigate the current reasoning capability of LLMs, we clarify the types of errors that arise in LLMs' reasoning… 18 arXiv — NLP / Computation & Language research 29d ago EMR: Self-Evolving Medical Multi-Agent System via Experience Mining and Reuse arXiv:2609.15161v1 Announce Type: new Abstract: Large language model (LLM) driven multi-agent systems have shown promise in complex clinical reasoning, yet existing approaches rely on static strategies and lack persistent clinical memory, preventing self-evolving from prior… 27 Page 6 of 10 · 500 articles ← Newer Older →
