News / #reasoning Tag Reasoning 500 articles archived under #reasoning · RSS Sign in to follow arXiv — Machine Learning research 11d ago Metacognitive Reasoning in Energy Based Models using Instance Based Learning Theory arXiv:2610.00399v1 Announce Type: new Abstract: Metacognition involves reasoning about cognitive processes themselves. An example is in resource allocation where we choose how much time and effort to put into a reasoning task before we begin based on our confidence. Current… 35 arXiv — Machine Learning research 11d ago IrekoGPT: Turning Structured Pruning into Post-Hoc Slimmable LLMs arXiv:2610.00426v1 Announce Type: new Abstract: We introduce IrekoGPT, a post-hoc method for converting pretrained LLMs into slimmable models whose width can be adjusted at inference time. Building on SliceGPT, we retain its projection matrices without pruning them, allowing a… 8 arXiv — Machine Learning research 11d ago Exploring More, Reasoning Better: Stepwise Risk-Sensitive GRPO for Diffusion Language Models arXiv:2610.00661v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) generate text by denoising a sequence or successive blocks, allowing several tokens to be revealed in parallel. Reinforcement learning with verifiable rewards (RLVR) reuses terminal feedback… 14 r/LocalLLaMA community 12d ago microsoft/FrogNano-4B-2609 · Hugging Face An agentic model from Microsoft for the GPU poor https://huggingface.co/bartowski/FrogNano-4B-2609-GGUF FrogNano is derived from Qwen/Qwen3.5-4B, a general-purpose post-trained model designed for language, reasoning, coding, agentic, and multimodal tasks. FrogNano inherits… 22 OpenAI official-blog 12d ago A model guide for the GPT-6 family Learn how startups can choose GPT-6 models, tune reasoning effort, improve prompts and skills, coordinate tools, and prepare workflows for production. 7 arXiv — Machine Learning research 12d ago Hermes: Learning Contextual Reasoning Unlocks Test-Time Scaling arXiv:2609.38332v1 Announce Type: new Abstract: Test-time scaling improves model performance by allocating additional compute during inference. Using this compute effectively across multiple context windows requires deciding how to allocate fresh contexts and what information to… 8 arXiv — Machine Learning research 12d ago Activation-Conditioned Self-Distillation arXiv:2609.38342v1 Announce Type: new Abstract: On-policy self-distillation uses a model as its own teacher to provide dense supervision for reasoning, often through reference-solution conditioning. Providing privileged information does not by itself ensure effective token-level… 6 arXiv — Machine Learning research 12d ago Provable Test-Time Scaling for Beam Search in LLM Reasoning arXiv:2609.38672v1 Announce Type: new Abstract: Beam-search-based test-time methods provide an effective way to improve large language model (LLM) performance on long-horizon generation by pruning invalid reasoning paths early, leading to significantly improved reasoning… 11 arXiv — Machine Learning research 12d ago Explicit Trajectory Diversity for RL-Based Post-Training of LLM Agents arXiv:2609.38805v1 Announce Type: new Abstract: LLM agents often admit multiple high-quality solutions to the same task, differing in reasoning structure, tool-use pattern, or interaction trajectory. Yet existing notions of diversity in LLM post-training are mostly implicit,… 31 arXiv — Machine Learning research 12d ago Mitigating the Length-Scaling Tax with Online Distillation arXiv:2609.38854v1 Announce Type: new Abstract: Length scaling during reinforcement-learning (RL) post-training is often viewed as a sign of improved reasoning ability, especially on difficult problems, but may also make responses to already-solved problems unnecessarily… 19 arXiv — Machine Learning research 12d ago Does Learning Protein Folding Generalize to Broader Reasoning? arXiv:2609.38879v1 Announce Type: new Abstract: Large language models rely heavily on human text, which often conveys surface answers rather than the spatial and structural logic behind them. Protein folding is a natural testbed, because one solved structure yields thousands of… 13 arXiv — Machine Learning research 12d ago K2P: Label-Free Knowledge to Prompt Distillation arXiv:2609.38898v1 Announce Type: new Abstract: Knowledge distillation can transfer reasoning from stronger teachers to frozen students through reusable prompts, but avoiding weight updates does not eliminate supervision. Without ground-truth answers, teacher solutions are… 22 arXiv — Machine Learning research 12d ago Adaptive Self-Consistency: From Black-Box Sampling to Distribution-Valued Feedback arXiv:2609.38931v1 Announce Type: new Abstract: Self-consistency samples many reasoning trajectories and aggregates their final answers, treating the LLM as a black box that returns one answer per trajectory. Yet the final answer of each trajectory is sampled from a softmax… 15 r/LocalLLaMA community 13d ago Pi extension: Skip reasoning with local Qwen 27B and proceed to answer right now pi-llama-skip-reasoning is an extension for the Pi.dev harness that forces a local llama.cpp model to stop reasoning and answer / act immediately. When you are deep into the ctx session and ask 27B a simple question about a fact or need a direct action, the model may still feel… 32 The Information — AI news-outlet 13d ago OpenAI Accuses Moonshot of Distillation Campaign OpenAI said it recently identified and mitigated a “coordinated model-distillation campaign” involving individuals associated with Moonshot AI, the Chinese developer of Kimi models. OpenAI said the operators of the campaign tried to extract protected reasoning—the model’s hidden… 5 arXiv — NLP / Computation & Language research 13d ago Prompt2Skill: Unsupervised Skill Optimization From Natural Language Instructions arXiv:2609.38593v1 Announce Type: new Abstract: Skills are external artifacts that Large Language Models (LLMs) consume at inference time to improve their performance on specialized domains by incorporating relevant procedural and domain knowledge. Expert-authored skills are… 25 arXiv — NLP / Computation & Language research 13d ago Breaking Babel: A Self-Evolving Multi-Agent System for Long-Form Subtitle Translation arXiv:2609.38660v1 Announce Type: new Abstract: Long-form subtitle translation requires reasoning over discourse and cultural context spanning episodes or entire series, while maintaining consistent terminology and style. Existing single-LLM methods are largely sentence-level,… 8 arXiv — NLP / Computation & Language research 13d ago StateTree: Enhancing Long-Term Dialogue Reasoning via Reinforcement Learning arXiv:2609.38809v1 Announce Type: new Abstract: Large language models deployed as personalized assistants must reason over long, evolving interaction histories. However, in long-term dialogue reasoning, relevant evidence is scattered across sessions, preferences may be revised… 23 arXiv — NLP / Computation & Language research 13d ago Making LLMs Say What They Think: Measuring and Improving CoT-Interpretability Alignment arXiv:2609.38972v1 Announce Type: new Abstract: Chain-of-thought (CoT) traces often serve as a proxy for how Large Language Models (LLMs) arrive at their answers. However, growing evidence shows that models' CoT often fails to reflect their internal computations and can be… 36 arXiv — NLP / Computation & Language research 13d ago When Clipping Reverses Correction: Failure Dynamics of Pointwise Forward-KL On-Policy Self-Distillation arXiv:2609.38995v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own generated responses using feedback from the same model conditioned on privileged information. On mathematical reasoning, the original OPSD study finds that stylistic… 19 arXiv — NLP / Computation & Language research 13d ago Settle: Learning When to Stop Reasoning arXiv:2609.38997v1 Announce Type: new Abstract: Reasoning models often continue generating after their answers have settled. Settle learns when to stop from answer stability in completed traces. It trains the existing end-of-reasoning token while keeping other predictions close… 36 arXiv — NLP / Computation & Language research 13d ago Structure vs. Chain-of-Thought: Evaluating LLM Criteria Extraction for Depression Severity arXiv:2609.39049v1 Announce Type: new Abstract: A large language model (LLM) can rate depression severity directly from a social media post or mark which clinical criteria the post shows and let code turn the count into a label. The latter is easier to audit because a clinician… 30 arXiv — NLP / Computation & Language research 13d ago CORE: Conflict-Oriented Reasoning Elimination for Verifiable Language-Model Search arXiv:2609.39069v1 Announce Type: new Abstract: Test-time reasoning systems often respond to failure by restarting or revising the latest step, even when an earlier decision caused the error. We introduce CORE, a search controller that requests a certified conflict core from a… 5 arXiv — NLP / Computation & Language research 13d ago Diagnosing On-Policy Self-Distillation for Reasoning Language Models arXiv:2609.39118v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has attracted growing interest as a promising approach to improve the reasoning ability of language models. Without external rewards nor a separate stronger teacher, the self-teacher with… 14 arXiv — NLP / Computation & Language research 13d ago Offline Guidance, Online Reasoning: Reusing LLM Feedback for Small Language Models arXiv:2609.39346v1 Announce Type: new Abstract: Large language models (LLMs) offer strong reasoning capabilities but are often costly to access through commercial APIs, while small language models (SLMs) are easier to deploy locally yet remain weaker in reasoning. This… 34 arXiv — NLP / Computation & Language research 13d ago Is This Evidence Decision-Critical? Learning to Verify Rule-Governed Decisions arXiv:2609.39608v1 Announce Type: new Abstract: Rule-based reasoning, as in eligibility checks and contract reviews, requires language models to assess evidence against individual conditions and combine their judgments under explicit rules. Errors in evidence assessment can… 18 arXiv — NLP / Computation & Language research 13d ago Better Supervision Is Nearby: Neighborhood On-Policy Self-Distillation arXiv:2609.39687v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains mathematical reasoning models using a privileged teacher that sees a reference solution and supervises student-sampled prefixes. Standard OPSD uses one fixed parameter setting at every… 6 arXiv — NLP / Computation & Language research 13d ago LatentHarness: Learning Latent Actions for Memory and Reasoning via Counterfactual Policy Distillation arXiv:2609.39740v1 Announce Type: new Abstract: Long-context reasoning faces two complementary bottlenecks: retaining evidence across long inputs and sustaining computation across many reasoning steps. Existing approaches largely address them separately, with external memory… 12 arXiv — NLP / Computation & Language research 13d ago Explore-on-Graph: Hybrid Embedding-LLM Reasoning for Knowledge Graph Question Answering under Incompleteness arXiv:2609.39786v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly combined with knowledge graphs (KGs) to ground reasoning in structured evidence. However, most LLM-based KGQA methods rely on traversing existing graph edges and become unreliable when… 6 arXiv — NLP / Computation & Language research 13d ago When a Kindergartener Solves Calculus: Measuring Capability Leakage in Role-Prompted Reasoning Models arXiv:2609.39846v1 Announce Type: new Abstract: We investigate the problem of role-capability leakage (RCL), in which a role-prompted reasoning model generates convincing in-role text while continuing to exhibit capabilities on benchmarks that exceed those implied by the… 11 arXiv — NLP / Computation & Language research 13d ago Cognitive Enhancement: Rethinking the Necessity of Role-Playing for Large Language Models arXiv:2609.39853v1 Announce Type: new Abstract: Role-playing prompting has become a popular yet simple technique for improving LLM reasoning and output quality. However, whether it consistently boosts performance across diverse domains remains unclear, as systematic validation… 31 arXiv — NLP / Computation & Language research 13d ago OPSRD: On-Policy Self-Role Distillation arXiv:2609.39884v1 Announce Type: new Abstract: Role prompting elicits specialized behavior from large language models through an expert identity, offering a lightweight way to guide reasoning on demanding tasks. However, evaluating or distilling complete role-prompted answers… 7 arXiv — NLP / Computation & Language research 13d ago The Concrete-Arbitrary Gap: Kinship Reasoning in LLMs Is Not Indifferent to Presentation arXiv:2609.39913v1 Announce Type: new Abstract: We test whether large language models solve formally matched kinship problems equally well when relations are expressed in familiar vocabulary or by explicitly defined nonce predicates. Across 500 paired graphs, concrete accuracy… 16 r/LocalLLaMA community 14d ago Qwen3.8-27B-pi: Effort-Ordered Reasoning for Agentic Coding   submitted by   /u/paf1138 [link]   [comments] 5 OpenAI official-blog 14d ago Disrupting a coordinated model-distillation campaign Learn how OpenAI disrupted a campaign to extract protected model reasoning and is strengthening defenses against adversarial distillation. 27 r/MachineLearning community 14d ago LessThink-Qwen3-4B: the same model, with far less thinking [P] I post-trained Qwen3-4B to spend 44% fewer tokens on reasoning, keeping its knowledge and answer style. The whole pipeline ran on one GPU. folks, you can check it out on : https://5ivatej.com/lessthink/   submitted by   /u/stey1r [link]   [comments] 30 arXiv — Machine Learning research 14d ago Reasoning with Neural Cellular Automata arXiv:2609.36126v1 Announce Type: new Abstract: Modern AI architectures used to solve visual reasoning tasks typically rely heavily on global connectivity and synchronization. As biological systems demonstrate, though, sophisticated computation can be performed in a more… 26 arXiv — Machine Learning research 14d ago In-Context Learning Amplifies a Latent Symbolic Circuit arXiv:2609.36265v1 Announce Type: new Abstract: Large language models can learn abstract rules from just a few in-context examples, but how their internal mechanisms activate as examples accumulate is not well understood. We trace a three-stage symbolic reasoning circuit… 23 arXiv — NLP / Computation & Language research 14d ago Question-Specific Knowledge Graphs for Efficient Visual Reasoning arXiv:2609.35942v1 Announce Type: new Abstract: Recent work in visual question answering has shown that vision-language models can exhibit strong reasoning capabilities by translating visual inputs into textual representations. The effectiveness of this translation depends on… 17 arXiv — NLP / Computation & Language research 14d ago SCOUT: Synergizing Reasoning and Tool-Use for Computer-Use Safety arXiv:2609.36201v1 Announce Type: new Abstract: Computer-use agents (CUAs), while capable of completing computer tasks in everyday and professional workflows, can cause unintended harm even under benign instructions and environments. However, detecting such harm remains… 36 arXiv — NLP / Computation & Language research 14d ago FastGuide: Accelerating Reward Guidance for Diffusion Large Language Models arXiv:2609.36202v1 Announce Type: new Abstract: Gradient-based reward guidance provides a flexible way to use downstream reward models to control masked diffusion language models at inference time. However, its computational cost remains high as each decoding iteration incurs… 5 arXiv — NLP / Computation & Language research 14d ago Can Language Models Learn to Forecast Stock Prices arXiv:2609.36914v1 Announce Type: new Abstract: Post-training has been shown to significantly improve language models' performance on tasks with verifiable outcomes, including mathematical reasoning, software engineering, and computer use. However, whether the same approach can… 16 arXiv — NLP / Computation & Language research 14d ago SRJudge: Empowering Large Language Models with Selective Reasoning for Fine-Grained Knowledge Concept Tagging arXiv:2609.36982v1 Announce Type: new Abstract: Knowledge concept tagging aims to assign specific concept or topic labels to educational content, which is essential for both educators and learners in traditional and online teaching practices. Recent work has explored large… 20 arXiv — NLP / Computation & Language research 14d ago Learning from Think-Mode Advantage via On-Policy Distillation arXiv:2609.37044v1 Announce Type: new Abstract: Explicit intermediate reasoning gives large language models (LLMs) a stronger problem-solving mode. We study learning from this think-mode advantage via on-policy distillation (OPD). OPD preserves student-generated trajectories and… 37 arXiv — NLP / Computation & Language research 14d ago What Does Post-Training Change in Multilingual Reasoning? arXiv:2609.37104v1 Announce Type: new Abstract: Open-source reasoning models provide unequal access to reasoning capability across languages. When a model can solve a problem but cannot deliver a complete solution in the user's language, language becomes an access barrier rather… 30 r/LocalLLaMA community 14d ago SFTMill: Easily [off-policy] distill any existing LLM with an OpenAI Compatible Endpoint. Turn any behavioral goal into a comprehensive dataset. Disclaimer: Any* means any model that exposes its CoT without it being censored. Hey guys - half a tutorial/guide, and half an I built this, so I went for resources. This is something that I created for myself recently when I couldn't find any good existing solution. I wrote… 21 Vercel — AI dev-tools 14d ago Ling 3.1 Flash is now available on AI Gateway Ling 3.1 Flash from InclusionAI is now available on AI Gateway. The model is free to use through October 13, 2026. Ling 3.1 Flash is a hybrid reasoning language model with 560B total parameters and 25B active per token. It has a 262K-token context window on AI Gateway. The model… 30 Hacker News — AI on Front Page community 15d ago Jeeves. Reasoning improves Jev-like decision models Article URL: https://github.com/PostHog/jeeves Comments URL: https://news.ycombinator.com/item?id=49891290 Points: 212 # Comments: 85 13 r/LocalLLaMA community 15d ago IQuestLab/IQuest-Q1 · Hugging Face IQuest-Q1 is a Mixture-of-Experts (MoE) model developed by IQuest for agentic coding, reasoning, and multi-step tool use. It comprises approximately 320B total parameters , with an estimated 15B parameters activated per token .   submitted by   /u/jacek2023 [link]  … 38 arXiv — Machine Learning research 15d ago Strategic Self-Consistency arXiv:2609.30352v1 Announce Type: new Abstract: Self-consistency has become a popular technique for enhancing the reasoning abilities of large language models by generating multiple reasoning paths and selecting the final answer through a majority vote. However, because model… 32 Page 3 of 10 · 500 articles ← Newer Older →
