News / #reasoning Tag Reasoning 500 articles archived under #reasoning · RSS Sign in to follow Hugging Face Daily Papers research 24d ago OPD-V: Visual On-Policy Self-Distillation with Modality Balance Abstract On-Policy Self-Distillation (OPSD) has become a standard post-training approach for improving visual reasoning in multimodal large language models (MLLMs). Existing methods draw privileged information from diverse input sources to guide self-distillation. Yet these… 22 Hugging Face Daily Papers research 24d ago ToolArtist: Tool-Using Unified Multimodal Models for Agentic Image Generation Abstract Text-to-image (T2I) models can produce visually compelling images, yet they remain limited on open-world tasks that require complex semantic understanding, multi-step reasoning, and the integration of external world knowledge. Existing efforts introduce agent… 36 arXiv — Machine Learning research 24d ago Elbow-Based MoE Routing: A Training-Free Inference Time Plugin for Expert Selection arXiv:2608.04401v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable model scaling while maintaining low inference-time compute by activating only a subset of experts per token. However, conventional routing relies on a fixed top-k selection, forcing the model… 4 arXiv — Machine Learning research 24d ago SVI-DAG: A Structured Variational Inference Approach to Bayesian Causal Discovery arXiv:2608.04930v1 Announce Type: new Abstract: Bayesian causal discovery seeks to determine the posterior distribution of causal theories, which are interpreted as directed acyclic graphs (DAGs) that explain the observed data. The resulting posterior allows systematic reasoning… 10 arXiv — Machine Learning research 24d ago SpecRoll: Fast-Slow Verifier-Feedback Adaptation for Speculative Reinforcement Learning Rollouts arXiv:2608.04962v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training improves the reasoning capabilities of large language models, but autoregressive rollout generation remains a major efficiency bottleneck. Speculative decoding can accelerate generation,… 22 arXiv — NLP / Computation & Language research 24d ago Mind the Cap: Output-Budget Regimes Change the Measured Multilingual Reasoning Gap arXiv:2608.04160v1 Announce Type: new Abstract: Multilingual evaluations report accuracy at a single output-token cap, but languages need different numbers of tokens to express the same content, so the cap is a hidden experimental variable. We test whether the… 34 arXiv — NLP / Computation & Language research 24d ago Towards End-to-End Multilingual Metaphor Processing: Integrating Detection, Translation, and Evaluation arXiv:2608.04260v1 Announce Type: new Abstract: Metaphorical language remains a major challenge for multilingual natural language processing because successful interpretation and translation require reasoning beyond literal lexical meaning. Existing research has largely… 14 arXiv — NLP / Computation & Language research 24d ago The Calibration Floor: Format Repair Can Masquerade as Self-Correction at Small-to-Mid Scale arXiv:2608.04355v1 Announce Type: new Abstract: Accuracy changes after language-model self-revision are usually interpreted as changes in reasoning. We show this can fail at the answer-extraction boundary, and test the failure causally rather than only observationally. Across… 11 arXiv — NLP / Computation & Language research 24d ago D$^2$F-ReAG: Dynamic Decomposition and Filtering for Multi-Hop Reasoning-Augmented Generation arXiv:2608.04444v1 Announce Type: new Abstract: Large language models (LLMs) often generate inaccurate answers due to their reliance on static internal knowledge. Retrieval-augmented generation (RAG) addresses this limitation by integrating external knowledge and excelling at… 29 arXiv — NLP / Computation & Language research 24d ago ODRA: Synthesizing Cognitive Behavioral Therapy Sessions with Structured Chain-Of-Thought and Dynamic Patient Resistance arXiv:2608.04524v1 Announce Type: new Abstract: Synthetic generation of Cognitive Behavioral Therapy (CBT) sessions is challenged by two competing demands: adhering to strict therapeutic structure while modeling the resistant, unpredictable behavior of real patients. Existing… 15 arXiv — NLP / Computation & Language research 24d ago STRIVE: Probing Reasoning Limits in Graded Plausibility Generation and Evaluation arXiv:2608.04567v1 Announce Type: new Abstract: Event knowledge concerns who does what to whom. Psycholinguists use event-plausibility judgments to examine how this knowledge supports human language processing. To isolate plausibility effects, these studies require controlled… 21 arXiv — NLP / Computation & Language research 24d ago When Absence Is Evidence: Evaluating Completeness-Sensitive Negative Reasoning in Large Language Models arXiv:2608.04591v1 Announce Type: new Abstract: Large language models (LLMs) are often asked whether something is absent from a record, list, or retrieved context. Yet non-observation licenses a negative answer only when evidence completely covers the query scope; otherwise, the… 34 arXiv — NLP / Computation & Language research 24d ago Evaluating Theory of Mind in Reasoning Models: Robustness over Reasoning arXiv:2608.04646v1 Announce Type: new Abstract: Large language models (LLMs) have recently shown strong performance on Theory of Mind (ToM) tests, prompting debate about the nature and validity of the underlying capabilities. At the same time, reasoning-oriented LLMs trained via… 10 arXiv — NLP / Computation & Language research 24d ago Does Out-of-Sight Equal Out-of-Mind in CoT Monitorability? arXiv:2608.04928v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning offers a window into the decision-making of large language models (LLMs), which can be monitored for target behaviors by reading the reasoning trace, motivating work on CoT monitorability. Latent… 26 arXiv — NLP / Computation & Language research 24d ago Protoreasoning in Tiny Transformers arXiv:2608.04980v1 Announce Type: new Abstract: We show that tiny transformers can profitably employ a simple form of Chain of Thought, which we call protoreasoning, allowing us to study step-by-step reasoning on ~1M-parameter models and opening up opportunities for much more… 33 arXiv — NLP / Computation & Language research 24d ago Same Formulas, Different Semantics: Do Language Models Follow Modal Logic Specifications? arXiv:2608.05097v1 Announce Type: new Abstract: Reasoning about necessity and possibility depends on assumptions about accessibility between worlds and about which objects exist at each one. The same inference may therefore hold under one modal system and fail under another.… 21 arXiv — NLP / Computation & Language research 24d ago Chained Recursive Language Models for Multi-Iteration Reasoning arXiv:2608.05124v1 Announce Type: new Abstract: Long context reasoning in large language models (LLMs) is usually constrained by the fact that a single inference trajectory has to simultaneously explore the context, store intermediate state, verify evidence, and produce the… 20 arXiv — NLP / Computation & Language research 24d ago Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning arXiv:2608.05139v1 Announce Type: new Abstract: Long-horizon reasoning in recent LLMs demands that the model switch between distinct skills inside a reasoning chain, such as first doing a math derivation, then using the result to plan a schedule. We call such problems… 17 arXiv — NLP / Computation & Language research 24d ago Reasoning Core: Designing Broad Procedural Data for Completion-Supervised Reasoning Training arXiv:2608.05148v1 Announce Type: new Abstract: Procedural generators produce useful verifiable reasoning problems at scale, but have received less attention as data for completion-supervised fine-tuning. We introduce Reasoning Core, a collection of 50 generators spanning… 37 arXiv — NLP / Computation & Language research 24d ago Q-CueGraph: Query-Conditioned Visual Evidence Graphs for Multimodal Reasoning arXiv:2608.04452v1 Announce Type: cross Abstract: High-resolution pixels and crop or zoom tools give multimodal large language models the ability to inspect an image, but they do not provide a reliable task-conditioned policy for deciding where to inspect. Q-CueGraph makes this… 23 arXiv — NLP / Computation & Language research 24d ago Leak-Resistant Unlearning: A New Benchmark for Evaluating Multi-Hop Reasoning Consistency and Recovery Robustness arXiv:2608.04519v1 Announce Type: cross Abstract: Benchmarking machine unlearning methods is critical to understand whether sensitive knowledge is removed from large language models (LLMs) or not. Current unlearning benchmarks include mainly single-hop questions and a narrow set… 31 arXiv — NLP / Computation & Language research 24d ago Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs arXiv:2608.04759v1 Announce Type: cross Abstract: Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inconsistent with the input image, allowing errors to propagate through the… 9 Hugging Face Daily Papers research 24d ago Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning Abstract Long-horizon reasoning in recent LLMs demands that the model switch between distinct skills inside a reasoning chain, such as first doing a math derivation, then using the result to plan a schedule. We call such problems cross-skill long-horizon tasks: multi-step tasks… 30 Hugging Face Daily Papers research 25d ago ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning Abstract On-policy training has emerged as a powerful post-training paradigm for improving the reasoning capabilities of large language models, and is often enhanced by golden trajectories from stronger expert models. However, when the expert fails on harder problems, existing… 9 Hugging Face Daily Papers research 25d ago CURV: Enhancing Chart Understanding Through Curriculum Visual Grounded Reasoning Abstract Chart question answering (CQA) requires multimodal large language models (MLLMs) to integrate visual comprehension with logical reasoning, yet current models struggle with accurate visual grounding and coherent reasoning chains. While extrinsic chain-of-thought… 11 Hugging Face Daily Papers research 25d ago Are the Financial Reasoning from LLMs Credible? A Real World Test over Long-Horizon Statements Abstract Do Large Language Models (LLMs) possess genuine structural reasoning, or merely rely on surface-level pattern matching? The financial domain, demanding numerical precision and multi-step logic over long contexts, is an ideal testbed. Existing benchmarks fail to capture… 10 arXiv — Machine Learning research 25d ago GoT-CD: Graph-of-Thoughts Causal Discovery and the Fragility of Post-hoc Path-Specific Fairness Audits arXiv:2608.02877v1 Announce Type: new Abstract: Causal discovery recovers directed structure from observational data and is increasingly used in clinical settings to support mechanism reasoning and fairness audits of predictive models. Path-specific counterfactual fairness asks… 8 arXiv — Machine Learning research 25d ago The Ignition Is Real, and It Lives at the Readout: Latent composition, difficulty-clocked ignition, and the interface-constituted commit in a recurrent-depth reasoner arXiv:2608.03263v1 Announce Type: new Abstract: We test whether the "compositional ignition" reported in latent-reasoning models is real computation, an instrument artifact, or inherited from verbal training data. We grow an independent realization of a published 30M-parameter… 33 arXiv — Machine Learning research 25d ago The Tell-Tale Trace: Detecting Reasoning Failures in LLMs Using Chain-of-Thought Dynamics arXiv:2608.03291v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning improves large language model (LLM) performance while also providing an observable interface to the model's reasoning process. Existing approaches that leverage verbalized CoTs to monitor reasoning… 6 arXiv — Machine Learning research 25d ago Shorter Reasoning, Earlier Answers? An Evaluation of Reasoning Interfaces arXiv:2608.03401v1 Announce Type: new Abstract: Large language models often reason at length before answering, increasing cost and latency. Prompts and trained settings can shorten this reasoning, but a shorter trace may only show that the model stopped sooner. Here, we evaluate… 28 arXiv — Machine Learning research 25d ago CausalOPD: First-Wrong-Step Supervision for Distilling Causal Chain Reasoning arXiv:2608.03673v1 Announce Type: new Abstract: Many critical reasoning tasks, including clinical diagnosis, legal judgment, and industrial fault diagnosis, require step-dependent causal chains in which early errors propagate and correct conclusions can mask invalid reasoning.… 28 arXiv — Machine Learning research 25d ago DiagLoop: A Counterfactual Data Flywheel with Stage-Localized Reinforcement for Diagnostic LLMs arXiv:2608.03674v1 Announce Type: new Abstract: Causal diagnostic models must explain how conclusions follow from evidence because diagnoses guide repairs and treatments. Yet serious cases are scarce, records rarely contain reasoning paths, and data transfer poorly across… 35 arXiv — NLP / Computation & Language research 25d ago OncoTriad-QA: A Patient-Level Radiology-Pathology-Genomics Benchmark for Pan-Cancer Reasoning arXiv:2608.02615v1 Announce Type: new Abstract: Cancer diagnosis and characterization require integrating complementary evidence from radiology, pathology, genomics, and clinical metadata. However, most medical large language model (LLM) and vision-language model (VLM)… 10 arXiv — NLP / Computation & Language research 25d ago Knowing the Form, Not the Function: Automatically Auditing Answer--Authority Decoupling in Legal Benchmarks arXiv:2608.02621v1 Announce Type: new Abstract: Legal benchmarks typically score final answers even when models also state legal authority. We test whether answer correctness can serve as a proxy for authority grounding. Under ordinary reasoning prompts that did not request… 33 arXiv — NLP / Computation & Language research 25d ago BODHI: Do LLMs Branch Out and Discover Heterogeneous Inferences? arXiv:2608.02867v1 Announce Type: new Abstract: Although reinforcement learning with verifiable rewards (RLVR) has improved the performance of large language models (LLMs) across a variety of reasoning tasks, there is significant debate as to whether RLVR expands the reasoning… 10 arXiv — NLP / Computation & Language research 25d ago TQLite: Multi-LLM Jury Guided Distillation for Real-time MQM Translation Quality Evaluation arXiv:2608.02975v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated impressive performance in MQM-based translation quality (TQ) evaluation, and recent advances in large reasoning models (LRMs) promise even greater improvements. However, both LLMs and… 22 arXiv — NLP / Computation & Language research 25d ago Beyond Accuracy: A Multidimensional Evaluation of Statistical Reasoning in Large Language Models arXiv:2608.03038v1 Announce Type: new Abstract: Statistical reasoning is multidimensional, yet evaluations of large language models (LLMs) typically emphasize response accuracy while overlooking how models construct and communicate statistical explanations. This study… 15 arXiv — NLP / Computation & Language research 25d ago PI-Mem: Pushing Long-Context Reasoning to 3.6M Tokens with Parallel-Iterative Memory arXiv:2608.03048v1 Announce Type: new Abstract: Long-context reasoning remains a critical bottleneck for large language models, as recent recurrent-memory approaches face two inherent challenges: sequential chunk-wise updates can overwrite early critical evidence with later… 15 arXiv — NLP / Computation & Language research 25d ago CVPO: Enhancing LLM Reinforcement Learning Reasoning via Value-Variance Adaptation and Dynamic Curriculum Learning arXiv:2608.03068v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as an effective method for enhancing the reasoning capabilities of large language models (LLMs). However, existing methods suffer from insufficient precision in feedback on generated answer… 12 arXiv — NLP / Computation & Language research 25d ago PAMT: Process-Aligned Reinforcement Learning for Multi-Domain Machine Translation arXiv:2608.03077v1 Announce Type: new Abstract: Multi-domain machine translation (MDMT) requires more than fluent generation: it demands domain-sensitive translation decisions such as domain disambiguation, terminology control, and stylistic adaptation. Large reasoning models… 36 arXiv — NLP / Computation & Language research 25d ago Aligning Large Vision-Language Models at Test Time: A Trajectory-Guided Structured Sampling Approach arXiv:2608.03204v1 Announce Type: new Abstract: Post-training reinforcement learning (RL) algorithms are commonly used to align large vision-language models (LVLMs) with human intent and the requirements of visual reasoning tasks. However, existing RL-based alignment methods are… 18 arXiv — NLP / Computation & Language research 25d ago Don't Let Me Ask for It: LLMs Show Deficiencies in Active Multi-Turn Information Acquisition for Abductive Inference arXiv:2608.03388v1 Announce Type: new Abstract: Abductive reasoning requires forming hypotheses that explain observed evidence and revising them as new evidence becomes available. While large language models (LLMs) are often evaluated on whether they solve abductive reasoning… 21 arXiv — NLP / Computation & Language research 25d ago Hi-TTRL: Regulating Consensus with Hints for Test-Time Reinforcement Learning arXiv:2608.03545v1 Announce Type: new Abstract: Test-time reinforcement learning (TTRL) improves the reasoning capabilities of large language models without labeled data by updating the policy with pseudo-labels constructed through majority voting. While effective, the reward… 35 arXiv — NLP / Computation & Language research 25d ago SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv:2608.03573v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) exhibit fundamentally different behaviors in enhancing multi-task reasoning for large language models (LLMs). Our preliminary experiments revealed a phenomenon: SFT… 9 arXiv — NLP / Computation & Language research 25d ago LoopMTP: A looped transformer guided by latent multi-token prediction arXiv:2608.03624v1 Announce Type: new Abstract: Looped transformers have emerged as a parameter-efficient alternative to scaling depth for strong reasoning. By reusing one stack of layers across $T$ iterations, they attain the effective depth and reasoning capabilities of larger… 22 arXiv — NLP / Computation & Language research 25d ago MultiGlobeQA: A Multilingual and Globally Diverse Benchmark for Geospatial Reasoning arXiv:2608.03882v1 Announce Type: new Abstract: Geospatial reasoning, i.e., computing distances, containment, and other spatial relations over real-world entities, is central to navigation and logistics, yet large language models (LLMs) struggle with the required geometric and… 17 arXiv — NLP / Computation & Language research 25d ago TurnSight: Turn-Level Hindsight Self-Distillation for Tool-Integrated Reasoning arXiv:2608.04007v1 Announce Type: new Abstract: Tool-Integrated Reasoning (TIR) enables LLMs to solve complex tasks through iterative tool interactions. However, existing reinforcement learning methods often rely on trajectory-level supervision, limiting fine-grained credit… 24 arXiv — NLP / Computation & Language research 25d ago Reinforcement Learning with Evolving Rubrics as Rewards for Audio Reasoning arXiv:2608.02831v1 Announce Type: cross Abstract: Audio reasoning is essential for machine understanding of the acoustic world. Reinforcement learning with verifiable rewards can elicit such reasoning, yet existing reward designs are complementary in their limitations:… 14 arXiv — NLP / Computation & Language research 25d ago CURV: Enhancing Chart Understanding Through Curriculum Visual Grounded Reasoning arXiv:2608.02833v1 Announce Type: cross Abstract: Chart question answering (CQA) requires multimodal large language models (MLLMs) to integrate visual comprehension with logical reasoning, yet current models struggle with accurate visual grounding and coherent reasoning chains.… 14 Hugging Face Daily Papers research 25d ago TurnSight: Turn-Level Hindsight Self-Distillation for Tool-Integrated Reasoning Abstract Tool-Integrated Reasoning (TIR) enables LLMs to solve complex tasks through iterative tool interactions. However, existing reinforcement learning methods often rely on trajectory-level supervision, limiting fine-grained credit assignment in long-horizon TIR scenarios.… 26 Page 9 of 10 · 500 articles ← Newer Older →
