News / #reasoning Tag Reasoning 500 articles archived under #reasoning · RSS Sign in to follow r/LocalLLaMA community 1d ago LiquidAI/LFM2.5-24B-A2B Gguf's: https://huggingface.co/LiquidAI/LFM2.5-24B-A2B-GGUF Free Demo: https://playground.liquid.ai "LFM2.5-24B-A2B is a 24B-parameter reasoning model with only 2B active parameters, built for fast, private agents on-device . It is the largest and final model in the LFM2.5… 24 Google DeepMind official-blog 1d ago Gemini 4 Argon for Robotics Gemini 4 Argon marks a step change in physical understanding, code generation, and visual-semantic reasoning—unlocking new workflows across the robotics stack and accelerating progress toward physical AGI. You can see this leap in capability on the Embodied Reasoning (ERQA)… 21 Vercel — AI dev-tools 1d ago Gemini 4 Argon now available on AI Gateway Gemini 4 Argon from Google is now available on AI Gateway . Gemini 4 Argon is built for coding, agentic work, and complex reasoning. It has a 1M token context window, accepts text, image, PDF, and video input, and supports tool calling. On coding tasks, Gemini 4 Argon builds… 4 r/MachineLearning community 2d ago U-Space: Uncovering When and Why Uncertainty Arises in Language Models [R][D] If you build on open-weight reasoning models, you have probably wanted a "how sure is the model about this answer?" signal that does not cost 5x sampling, a judge model, or a labeled dataset. Hence, we built the U-Lens. In one line: score = (how strongly the hidden state points… 5 arXiv — NLP / Computation & Language research 2d ago REDaCT: Collapse-Free Unlearning in Large Reasoning Models arXiv:2610.12769v1 Announce Type: cross Abstract: Unlearning in large reasoning models (LRMs) requires removing forget-set information from both the reasoning trace and the final answer. Existing approaches achieve this objective at the cost of reasoning collapse, where the… 18 arXiv — Machine Learning research 2d ago Cross-Behavior Policy Optimization: Unified Learning from Offline Demonstrations and On- and Off-Policy Rollouts via a Shared Regression Target arXiv:2610.12830v1 Announce Type: new Abstract: Reasoning post-training draws on offline demonstrations and policy-generated rollouts, yet conventional supervised fine-tuning (SFT) followed by reinforcement learning (RL) separates their objectives and limits continued reuse of… 20 arXiv — Machine Learning research 2d ago Generalized Proximal Policy Optimization: Unifying LLM RL Algorithms from the Perspective of Divergence arXiv:2610.13015v1 Announce Type: new Abstract: Reinforcement learning has become the foundational paradigm for enhancing the reasoning capabilities of LLMs. Yet the dominant approach, Proximal Policy Optimization (PPO), relies on a geometrically degenerate clipping proxy that… 22 arXiv — Machine Learning research 2d ago Trajectory-Aware Policy Optimization: Closing the State Distribution Gap in Long-Horizon LLM RL arXiv:2610.13020v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a dominant paradigm for enhancing LLMs' reasoning capabilities. Yet long-horizon autoregressive rollouts introduce a fundamental limitation: local policy mismatch can compound into severe… 16 arXiv — Machine Learning research 2d ago How Much Computation Does Every Forecast Need? Structured Block Skipping in Two Time-Series Foundation Models arXiv:2610.13208v1 Announce Type: new Abstract: Time-series foundation models use the same network depth for every input, although forecasting windows differ in structure and difficulty. We test whether whole Transformer blocks can be removed at inference time in two pretrained… 19 arXiv — Machine Learning research 2d ago State-OPD: State-Grounded On-Policy Distillation for Multi-Turn Agents arXiv:2610.13238v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has emerged as a powerful paradigm for transferring reasoning capabilities from frontier models to smaller models, while extending its success to multi-turn agentic environments remains challenging. We… 17 arXiv — NLP / Computation & Language research 2d ago AutoIndexer: Flexible-Order Decoding by Training Causal Models on Chains of Edits arXiv:2610.12545v1 Announce Type: new Abstract: Autoregressive decoding is less suited to non-causally ordered data, e.g., cross-references or future dependencies, since their outputs cannot be revised post hoc, unlike iterative human reasoning. Diffusion LLMs partially mitigate… 33 arXiv — NLP / Computation & Language research 2d ago SEEDS: Preview-Guided Evidence Admission for Search Agents arXiv:2610.12932v1 Announce Type: new Abstract: Search agents extend large reasoning models with multi-round access to external knowledge, yet most existing systems largely conflate retrieving evidence with consuming it. Retrieved documents are commonly incorporated according to… 37 arXiv — NLP / Computation & Language research 2d ago What Should SFT Learn? Conditional Information Gain for Generalizable Post-Training arXiv:2610.12995v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) remains a widely used approach for post-training large language models, because fixed demonstrations can directly introduce desired reasoning strategies and behavioral patterns. Yet forcing a model to… 31 arXiv — NLP / Computation & Language research 2d ago RAMP: Recurrent Adaptive Mixed Precision for Efficient Prefill in Recurrent-Depth Language Models arXiv:2610.13041v1 Announce Type: new Abstract: Recurrent-depth language models improve inference-time reasoning by repeatedly applying a shared network to refine internal representations, but the additional recurrent computation also increases inference cost. This overhead is… 33 arXiv — NLP / Computation & Language research 2d ago CliQ-RRG: Clinical-Knowledge Guided Disease-aware Visual-Textual Alignment for QA-Style Radiology Report Generation arXiv:2610.13059v1 Announce Type: new Abstract: Radiology reports are essential for diagnostic reasoning and patient care, yet their manual preparation is time-consuming and cognitively demanding. Automatic radiology report generation (RRG) offers a scalable alternative, but… 15 arXiv — NLP / Computation & Language research 2d ago PreSTO: Predictive Subtree Prefetching for Fast LLM Power Sampling arXiv:2610.13171v1 Announce Type: new Abstract: Power sampling improves large language model (LLM) reasoning at test time by sampling from a sharpened version of the base model's distribution. Its sampler, PowerMH, is slow because its Metropolis--Hastings (MH) updates are… 14 arXiv — NLP / Computation & Language research 2d ago zip2zip++: Towards Inference-Time Token Compression with Minimal Quality Loss arXiv:2610.13605v1 Announce Type: new Abstract: Dynamic vocabularies built on-the-fly via Lempel-Ziv-Welch (LZW) compression let a language model represent the same text in fewer tokens, but prior work shows that this efficiency comes at a cost to reasoning and perplexity. We… 27 arXiv — NLP / Computation & Language research 2d ago Inject a Turn, Not a Token: Learning Where to Redirect LLM Reasoning for Self-Correction arXiv:2610.13672v1 Announce Type: new Abstract: Large language models struggle to reliably identify and correct errors in their own reasoning. Unlike prior training-based approaches that fine-tune an LLM to generate revisions or feedback, we learn where to intervene in failed… 19 arXiv — NLP / Computation & Language research 2d ago Verifiable Retrieval for Legal Reasoning through Structure-driven Knowledge Graph arXiv:2610.13695v1 Announce Type: new Abstract: Any automation within reliability-critical contexts such as medicine or law has to be transparent and verifiable. Despite their advantages, current LLM-based systems do not meet these requirements due to their inherent black-box… 32 arXiv — NLP / Computation & Language research 2d ago Enhancing Legal Reasoning in Pre-trained Language Models via Knowledge Graph-Guided Multi-Task Pre-training arXiv:2610.13722v1 Announce Type: new Abstract: Legal language understanding requires reasoning over semi-structured regulatory documents, yet standard pre-training objectives do not explicitly target this structural capability. Because current legal language models rely solely… 8 arXiv — NLP / Computation & Language research 2d ago When VLMs Destroy What They Know: Spatial Representations Fall Below Lexical Priors arXiv:2610.13910v1 Announce Type: new Abstract: Vision-Language Models (VLMs) increasingly analyze and reason about images, yet it remains unclear whether their internal representations faithfully encode the structured relations required for such reasoning. We introduce EICS… 21 arXiv — NLP / Computation & Language research 2d ago SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire arXiv:2610.12596v1 Announce Type: cross Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short and episodic, and performance on long tasks is hard to dissect into stored… 25 arXiv — NLP / Computation & Language research 2d ago MVGraph: Benchmarking LVLMs on Evidence Composition across Multi-View Visual Graph arXiv:2610.12961v1 Announce Type: cross Abstract: We introduce MVGraph, a benchmark for evaluating large vision-language models (LVLMs) on multi-graph reasoning where the evidence required by a query is distributed across multiple interrelated visual graph views. Although such… 31 arXiv — NLP / Computation & Language research 2d ago BoundaryEvo: Data-Model Co-Evolution at the Capability Boundary for Long-Chain Reasoning Distillation arXiv:2610.13285v1 Announce Type: cross Abstract: Distilling long-chain reasoning trajectories from large teacher models provides an effective way to improve the reasoning ability of small language models. However, existing methods typically select a fixed training set before… 16 r/LocalLLaMA community 2d ago I ran Qwen 3.8 Flash-Next on my AMD 7900 XTX at 500k context. All local and what a shift it has been. I was running Qwen3.8-Flash-Next (base and later Swift-1.5 NVFP4) on a paid pod seat for about a month, and it started answering with short strings that echoed its own earlier reasoning. I assumed the context was getting too big for it. But it wasn't. Across almost 13,000 turns… 13 r/LocalLLaMA community 3d ago Now you can grow Bonsai on your potato No more excuses for GPU-poor folks not to start LLMing! Full 27B-class reasoning in ternary transformer weights, for llama.cpp (CUDA, Metal, CPU) ~9.3x smaller than FP16 (ideal) | 98.2% of FP16 intelligence retained | ~47 tok/s on an Apple M5 Max laptop Highlights ~5.9 GB… 6 arXiv — NLP / Computation & Language research 5d ago Recurrent Self-Improvement: Dynamic Cross-Loop On-Policy Distillation for Looped Language Models arXiv:2610.10623v1 Announce Type: cross Abstract: Looped Language Models (LoopLMs) offer a parameter efficient approach to scaling reasoning by reusing shared parameters across recurrent computation steps. Despite their promise, effective post-training of LoopLMs remains… 14 arXiv — Machine Learning research 5d ago Visible Reasoning Is Not a Universal Optimizer: Persona- and Thinking-Dependent Effects in Analytics Code Generation arXiv:2610.10639v1 Announce Type: new Abstract: Visible Chain-of-Thought (CoT) is often treated as a broadly useful reasoning instruction, yet analytics code generation combines natural-language ambiguity, schema grounding, target-language constraints, and model-specific… 25 arXiv — Machine Learning research 5d ago Coverage-Aware Reasoning with Medical Tokens for Diagnosis Prediction arXiv:2610.10641v1 Announce Type: new Abstract: Large language models (LLMs) offer promising potential for next-visit diagnosis prediction, owing to their ability to integrate longitudinal clinical evidence and reason over it in natural language. However, reinforcement learning… 11 arXiv — Machine Learning research 5d ago Invariant-Measure Reasoners: Stable Representations for Latent Reasoning arXiv:2610.10996v1 Announce Type: new Abstract: Latent reasoning models repeatedly update a latent state using the same recurrent block. As the recurrent depth increases, the sequence of latent states may converge to a compact subset of the state space without necessarily… 18 arXiv — Machine Learning research 5d ago Do LLMs Learn from Rewards in Context? : Rethinking the role of reward in In-Context Reinforcement Learning arXiv:2610.11152v1 Announce Type: new Abstract: LLM agents increasingly improve at inference time by accumulating experience in context rather than by updating parameters. This process is often described as in-context reinforcement learning (ICRL). Whether in-context learning… 23 arXiv — Machine Learning research 5d ago Why On-Policy Distillation Sometimes Fails: Vanishing Learning Signals arXiv:2610.11247v1 Announce Type: new Abstract: On-policy distillation (OPD) enables effective capability transfer between language models, yet the mechanisms underlying its failures are not fully understood. Across code generation and mathematical reasoning, OPD with… 21 arXiv — Machine Learning research 5d ago SpatialOPSD: Self-Distilling Spatial Intelligence from Verified Coding Agent Traces arXiv:2610.11366v1 Announce Type: new Abstract: Spatial coding agents significantly improve spatial reasoning in Multimodal Large Language Models (MLLMs) by using external tools to generate verified execution traces. However, this paradigm inherently suffers from prohibitive… 31 arXiv — Machine Learning research 5d ago Rare Gate Disagreements Can Limit Plasticity: When Gradient Flow Mispredicts Finite-Batch SGD arXiv:2610.11475v1 Announce Type: new Abstract: Population gradient flow is a common tool for reasoning about how neural networks adapt, including after pretraining. We show that it can mispredict finite-batch stochastic gradient descent (SGD) qualitatively, and we trace the… 32 arXiv — NLP / Computation & Language research 5d ago Lapras: Latent Reasoning for Time Series Language Models arXiv:2610.11111v1 Announce Type: new Abstract: Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural language answers and explanations. A common approach is Chain-of-Thought (CoT),… 17 arXiv — NLP / Computation & Language research 5d ago From Retrieval to Reconstruction: Constructing Evolvable Cognitive Memory for Long-Term Dialogue arXiv:2610.11314v1 Announce Type: new Abstract: Large Language Models (LLMs) serving as long-term dialogue agents require memory systems that support reliable reasoning over extended interactions. However, existing Retrieval-Augmented Generation (RAG) frameworks typically treat… 29 arXiv — NLP / Computation & Language research 5d ago ReCal: Calibrating Structured Pruning for On-Policy Distillation Recovery arXiv:2610.11332v1 Announce Type: new Abstract: Structured pruning reduces the deployment cost of reasoning language models, but the resulting capability degradation can hinder subsequent on-policy distillation (OPD) recovery. Because OPD relies on student-generated… 12 arXiv — NLP / Computation & Language research 5d ago Residual Advantage: Student-Relative Teacher Guidance for RL with Verifiable Rewards arXiv:2610.11519v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) and on-policy distillation (OPD) have become two main paradigms for post-training reasoning models. RLVR gives each response a single outcome label, leaving the steps inside it… 6 arXiv — NLP / Computation & Language research 5d ago Measuring Cultural Alignment Beyond the Average: A Framework for Evaluating Maternal-Health LLM Interactions in Indian Contexts arXiv:2610.11586v1 Announce Type: new Abstract: Existing evaluation methods for healthcare LLMs primarily assess factual correctness,safety, and fluency, while providing limited insight into whether generated interactions reflect culturally situated healthcare reasoning. This… 23 arXiv — NLP / Computation & Language research 5d ago Probing for Long-Horizon Deductive Reasoning Capabilities in Language Models with Prolog arXiv:2610.11592v1 Announce Type: new Abstract: Current frontier LLMs can theoretically process long contexts with 1M tokens or more. But to what extent can they go beyond simple retrieval and perform deeper reasoning over such long contexts? We empirically investigate… 27 arXiv — NLP / Computation & Language research 5d ago Specialized Decision Models vs. General-Purpose LLMs: Benchmarking Jev Across Knowledge, Reasoning, and Multilingual Tasks arXiv:2610.11978v1 Announce Type: new Abstract: Jev is a "System One" model that returns a choice among given options instead of generating text. We study how such a specialized decision model compares with general-purpose large language models (LLMs). We evaluate Jev on 13… 20 arXiv — NLP / Computation & Language research 5d ago Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology arXiv:2610.12022v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external events to the causes and reasons of agents' social behaviors, plays a critical… 35 arXiv — NLP / Computation & Language research 5d ago NavGPT-3: Harnessing Context in a Hierarchical Navigation Runtime arXiv:2610.10787v1 Announce Type: cross Abstract: Language models trained with long-horizon agentic reinforcement learning can generalize knowledge through reasoning, express precise actions, and pursue goals over many steps, raising the ceiling on what an embodied agent can… 13 arXiv — NLP / Computation & Language research 5d ago GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentary arXiv:2610.11129v1 Announce Type: cross Abstract: Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge. Existing AI-Generated Game Commentary (AI-GGC) studies remain fragmented across games, modalities,… 29 arXiv — Machine Learning research 6d ago Bounded Autonomy and Verifiable Safety for Agentic AI Enabled Automation arXiv:2610.08815v1 Announce Type: new Abstract: Agentic AI-enabled automation cannot be safely deployed in high-stakes environments on probabilistic reasoning alone. A recurring risk is epistemic drift: as reasoning deepens, system behavior may move away from… 20 arXiv — Machine Learning research 6d ago Algorithmic Scratchpads and Curriculum Staging for Arithmetic Reasoning in Tiny Transformers arXiv:2610.09003v1 Announce Type: new Abstract: Autoregressive Large Language Models (LLMs) frequently struggle with deterministic multi-step algorithmic tasks such as multi-digit multiplication and long division. In this paper, we investigate the mechanics of multi-step… 7 arXiv — Machine Learning research 6d ago The Dichotomy Between Pattern Recognition and Step-by-Step Reasoning arXiv:2610.09186v1 Announce Type: new Abstract: We argue that pattern recognition and step-by-step reasoning are two ends of a spectrum. A large language model (LLM) learns to reason step-by-step when data is structured such that the next token depends on a small amount of… 14 arXiv — NLP / Computation & Language research 6d ago Collaborative Reasoning Distillation via Cross-Feedback and Coherent Curation arXiv:2610.09587v1 Announce Type: cross Abstract: Reasoning capabilities are critical for advancing Large Language Models, yet current approaches either require massive computational budgets or struggle to effectively distill reasoning to smaller models. Standard distillation… 38 arXiv — NLP / Computation & Language research 6d ago Emo-Jev: Probabilistic Reasoning for Emotion Classification with Jev arXiv:2610.08829v1 Announce Type: new Abstract: Jev offers an alternative interface for language understanding: given an input and predefined questions, it returns probabilistic decisions rather than free-form responses. Whether this interface can support effective reasoning for… 4 arXiv — NLP / Computation & Language research 6d ago Which Language Should a Skeleton Speak? Language Choices in Multilingual Reasoning arXiv:2610.09607v1 Announce Type: new Abstract: Skeleton-based reasoning prompting is a promising training-free approach for structuring LLM reasoning, but prior work largely assumes an English-centric setting. We propose the Language-Aware Skeleton Exploration Framework (LASEF)… 17 Page 1 of 10 · 500 articles Older →
