News / #reasoning Tag Reasoning 500 articles archived under #reasoning · RSS Sign in to follow Hugging Face Daily Papers research 10d ago GradCuit: Credit-Assigned Gradient Flow Enables Robust and Interpretable Test-Time Latent Reasoning Abstract Optimization-based latent reasoning improves large language model outputs by optimizing instance-specific continuous states at test time while keeping model parameters frozen. Existing methods, however, typically connect these states to the reasoning trajectory through… 8 Hugging Face Daily Papers research 10d ago DeepVoyager-VL: Incentivizing Vision-in-the-Loop Search for Long-Horizon Multimodal Agents Abstract Multimodal large language models (MLLMs) have advanced visual understanding and reasoning, yet their static parametric knowledge limits their ability to address knowledge-intensive and dynamically evolving open-world problems. To move beyond this limitation, multimodal… 24 Hugging Face Daily Papers research 10d ago 3DZip: Spatial-Aware Feature Diversity-Guided Token Compression for 3D Question Answering Abstract Recent 3D vision-language models (3D VLMs) construct geometry aware tokens by projecting 2D visual features into world coordinates, enabling spatial reasoning for tasks such as 3D question answering. However, this design generates thousands of tokens per scene,… 13 Hugging Face Daily Papers research 10d ago LongHorizon-Harness: Advancing Long-Horizon Agents for Real-World Tasks Abstract Large language model (LLM) agents increasingly undertake long-horizon tasks that require sustained reasoning, tool use, and revision across many interdependent steps. However, existing agent harnesses maintain task execution, task state, and completion assessment within… 37 Smol AI News news-outlet 10d ago not much happened today **Alibaba** launched **Qwen3.8-Max**, enhancing multimodal capabilities and agent ecosystem integration. **NVIDIA** introduced **Alpamayo 2 Super** for autonomous vehicle reasoning, while **Mistral AI** released **Shieldstral**, a 3B parameter open-weights safety model for… 17 arXiv — Machine Learning research 10d ago Learning Compositional Meta-Routing for Agentic Workflows: An Executable Benchmark arXiv:2608.00106v1 Announce Type: new Abstract: Agentic systems must decide not only what answer to produce, but which reasoning and execution operations should precede it. A controller may answer directly, decompose a request, retrieve evidence, execute code, delegate to a… 17 arXiv — Machine Learning research 10d ago Agentic Graph Token Reasoning arXiv:2608.00542v1 Announce Type: new Abstract: Graphs model relational data throughout science and industry, from citation networks to product co-purchase graphs. Because the nodes of many such graphs carry rich text, a growing line of work applies large language models (LLMs)… 11 arXiv — Machine Learning research 10d ago Question Begets Question: Self-Evolving Curriculum for Reinforcement Fine-Tuning on Competition Mathematics arXiv:2608.01522v1 Announce Type: new Abstract: Teaching a language model a skill it has not mastered is obstructed by three recurring difficulties: training data is scarce, ground-truth reasoning traces are usually unavailable, and models often exhibit an apparent ceiling… 19 arXiv — Machine Learning research 10d ago Gram-Space: Structure-Preserving Codebook Compression for Memory-Efficient Neuro-Symbolic AI arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory bottlenecks that limit scalability and deployment. In this paper, we propose… 17 arXiv — Machine Learning research 10d ago Measuring in-context algorithmic reasoning in language models against an exact Bayes-optimal standard arXiv:2608.01575v1 Announce Type: new Abstract: Whether large language models perform genuine algorithmic reasoning or mere pattern completion is hard to test, because most benchmarks lack a ground truth for correct inductive inference. We introduce F-ICL, an in-context-learning… 20 arXiv — NLP / Computation & Language research 10d ago Cost-Effective Automated Judging of Natural-Language Mathematical Proofs arXiv:2608.00004v1 Announce Type: new Abstract: Grading natural-language mathematical proofs is a recurring cost in evaluating math-reasoning systems, and frontier LLM judges are expensive. We ask whether cheap open-weight models can serve as reliable judges given a candidate… 14 arXiv — NLP / Computation & Language research 10d ago Native Multilingual Chain-of-Thought Reasoning in Low-Resource Southeast Asian Languages arXiv:2608.00533v1 Announce Type: new Abstract: Large Language Models have achieved substantial progress in reasoning capabilities. Yet in low-resource native settings, many suffer from cross-lingual collapse, reverting to English during intermediate steps that require complex… 23 arXiv — NLP / Computation & Language research 10d ago Practical Online KV Cache Compaction for LLM Agents: An Empirical Study arXiv:2608.00902v1 Announce Type: new Abstract: LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV cache compaction can reduce this cost, but most prior methods assume a static… 33 arXiv — NLP / Computation & Language research 10d ago Cloud-ScPO: Hidden-State Geometry for Semi-Supervised Preference Optimization in LLM Reasoning arXiv:2608.01014v1 Announce Type: new Abstract: Preference optimization improves mathematical reasoning in large language models (LLMs), but reliable chosen-rejected pairs usually require verified answers, human annotations, or external reward models. We investigate whether… 34 arXiv — NLP / Computation & Language research 10d ago Why LLMs Give In: Conversational Factors and Reasoning Behind Medical Sycophancy arXiv:2608.01017v1 Announce Type: new Abstract: A language model that abandons a correct medical answer under user pushback is more dangerous than one that was simply wrong, because it lends the credibility of a correct answer to the user's misinformation. Such model behavior,… 12 arXiv — NLP / Computation & Language research 10d ago Attend to Your Own Thoughts: Breaking the Barrier for Post-Training Quantization of Reasoning LLMs through the Lens of 1.58-Bit Quantization arXiv:2608.01078v1 Announce Type: new Abstract: We propose ScaleQ-1.58, a scalable ternary post-training quantization (PTQ) framework for reasoning LLMs. Its core insight stems from an empirical finding: although modern LLMs are typically trained to exhibit chain-of-thought… 27 arXiv — NLP / Computation & Language research 10d ago CrossLex: A Source-Grounded Benchmark for Cross-Jurisdictional Legal Reasoning in Large Language Models arXiv:2608.01292v1 Announce Type: new Abstract: Legal reasoning is inherently jurisdiction-dependent: the same facts can call for different legal rules and yield different conclusions across legal systems. Yet existing benchmarks rarely evaluate whether large language models… 34 arXiv — NLP / Computation & Language research 10d ago BiCAA: Bidirectional Credit Assignment for Search-Augmented Agent arXiv:2608.01321v1 Announce Type: new Abstract: Multi-step search is a fundamental capability for search agents, enabling them to iteratively acquire, refine, and integrate external evidence for complex reasoning QA. However, vanilla GRPO allocates rewards exclusively based on… 5 arXiv — NLP / Computation & Language research 10d ago LongChart VQA: A Comprehensive Benchmark for MLLMs with Complex Multi-Chart Reasoning arXiv:2608.01328v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are rapidly evolving with expanded context windows and stronger reasoning capabilities, enabling multi-chart understanding and multi-step inference. These abilities are increasingly… 10 arXiv — NLP / Computation & Language research 10d ago Prompt-Induced Waste in Large Reasoning Models: A Preregistered Two-Harness Benchmark of Coding Agents arXiv:2608.01347v1 Announce Type: new Abstract: Large reasoning models used as coding agents incur costs from deliberation, tool calls, and repeated agent turns, yet the causal effect of prompt wording on this spend has not been measured systematically. We present a… 36 arXiv — NLP / Computation & Language research 10d ago HopRefusalBench: Diagnosing Refusal Failures in Search-Augmented Agents for Multi-Hop Reasoning arXiv:2608.01358v1 Announce Type: new Abstract: Search-augmented large language model agents are increasingly capable of solving knowledge-intensive tasks, but their behavior when a multi-hop question is fundamentally unanswerable remains poorly understood. Existing abstention… 33 arXiv — NLP / Computation & Language research 10d ago Semantic Alignment of AI Models: Concept Collapse, Checkpoint Dynamics, and Cross-Lingual Transfer arXiv:2608.01585v1 Announce Type: new Abstract: Language model benchmarking is a difficult task. Outcome reasoning alone does not test the model's conceptualization of language and popular open-source benchmarks are quickly saturated or ingested as training data. It is important… 7 arXiv — NLP / Computation & Language research 10d ago PICTURE: Enhancing Theory-of-Mind in Large Language Models by Revealing, Not Hiding, Characters' Lack of Knowledge arXiv:2608.01598v1 Announce Type: new Abstract: Simulating human-like Theory of Mind (ToM) has been a longstanding problem in natural language processing (NLP). To address this, existing works introduce a reasoning step of event hiding (a.k.a. perspective-taking), where events… 8 arXiv — NLP / Computation & Language research 10d ago Does Accuracy Equal Evidence? Reasoning Faithfulness under KV Cache Compression arXiv:2608.01631v1 Announce Type: new Abstract: KV cache compression is commonly evaluated by final-answer accuracy, implicitly assuming that preserving the answer also preserves the reasoning that supports it. We test this assumption for large reasoning models and show that it… 5 Hugging Face Daily Papers research 10d ago StyleForge: Indoor Furniture Styling by Counterfactual Reasoning in a Hypergraph Field Abstract Fixed-layout indoor furniture styling requires selecting assets that form a coherent room without changing the prescribed furniture categories, positions, orientations, or scales. Existing approaches typically retrieve each asset independently or rely on static local… 32 Hugging Face Daily Papers research 10d ago Deferred Exposure of Future Trajectories for Verifiable Reasoning in Autonomous Driving VLMs Abstract Recent Vision-Language-Action (VLA) models for autonomous driving (AD) increasingly utilize chain-of-thought (CoT) supervision to enhance the reasoning capabilities of their Vision-Language Model (VLM) components, yet existing annotation pipelines commonly expose the… 28 r/LocalLLaMA community 10d ago [NEW MODELS!] Supra2-100M Base and Instruct - go check them out! Hey guys! After a LOT of good feedback on our previous models like Supra-50M-Instruct and -Reasoning, many community likes, follows and upvotes we saw many community requests asking for new models. We've inspired a lot of people with our work - and now we're presenting the all… 14 r/LocalLLaMA community 11d ago AI9Stars released G9v3-39A5B AI9Stars has released G9v3-39A5B an open weights language model designed to deliver even stronger reasoning capabilities than ai9stars/G9v3-3B with its 39B and 5 active experts. It is released under the Apache 2.0 license making it fully open for personal and commercial use It… 10 Hugging Face Daily Papers research 11d ago Not All Tokens Deserve Equal Credit: Counterfactual Sensitivity Credit Reallocation for Long-CoT Reasoning Abstract Reinforcement learning with verifiable rewards (RLVR) is central to improving long-CoT reasoning in large language models. Critic-free methods such as GRPO convert response-level rewards into advantages and uniformly broadcast them across tokens, overlooking their… 17 Hugging Face Daily Papers research 11d ago Would You Walk to the Car Wash? Revealing the Salience Bias of Large Language Models in Commonsense Reasoning Abstract As large language models (LLMs) continue to advance in complex reasoning tasks, they have learned to heavily prioritize explicit conditions provided in the input. However, in everyday commonsense reasoning, this mechanism exposes a critical vulnerability which we term… 18 arXiv — Machine Learning research 11d ago Reflection or Re-Generation? Why LLM Revision Fails Where Human Revision Succeeds arXiv:2607.28908v1 Announce Type: new Abstract: Reflection, the ability to revisit and revise prior reasoning, is central to how humans improve their answers. Large language models (LLMs) are increasingly prompted to "reflect," yet whether this resembles human revision remains… 34 arXiv — NLP / Computation & Language research 11d ago ThinkReset: Learnable Intermediate Interface Construction for Bounded-Context Long-Horizon Reasoning arXiv:2607.28642v1 Announce Type: cross Abstract: Long chain-of-thought reasoning improves performance on complex problems, but it also introduces redundancy accumulation, context overflow, and error anchoring. We argue that under bounded context windows, the core bottleneck is… 31 arXiv — NLP / Computation & Language research 11d ago How Hard Does It Think? Analyzing Step-Aware Reasoning Energy in LLM Chain-of-Thought Trajectories arXiv:2607.28674v1 Announce Type: cross Abstract: Understanding how computational effort is allocated across individual chain-of-thought (CoT) reasoning steps remains an open challenge: existing interpretability methods rely on output-level signals or collapse processing depth… 28 arXiv — NLP / Computation & Language research 11d ago Are the Financial Reasoning from LLMs Credible? A Real World Test over Long-Horizon Statements arXiv:2607.28661v1 Announce Type: new 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… 30 arXiv — NLP / Computation & Language research 11d ago Demystifying Entropy-based Selection for Chain-of-Thought Compression in Large Reasoning Models arXiv:2607.28707v1 Announce Type: new Abstract: Entropy-based pruning has been proposed as an effective method for compressing Chain-of-Thought (CoT) reasoning with negligible accuracy loss. We test the robustness of low- and high-entropy CoT step selection methods across… 32 arXiv — NLP / Computation & Language research 11d ago BLADE: Boundary-Expanded and Layer-Adaptive Dynamic Exit for Efficient LLM Reasoning arXiv:2607.28966v1 Announce Type: new Abstract: Large language models often improve task performance by generating long reasoning traces, but the resulting computation is frequently wasted on redundant verification and revision. Existing probe-based early-exit approaches mainly… 4 arXiv — NLP / Computation & Language research 11d ago Tokenizer-Agnostic Engram Module arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relies on token-level $N$-gram hashing for Engram embedding lookup, introducing a… 31 arXiv — NLP / Computation & Language research 11d ago Learning Latent Reasoning Traces for Scalar Reward Models End-to-End arXiv:2607.29185v1 Announce Type: new Abstract: Reward models (RMs) are central to aligning large language models with human preferences via reinforcement learning. Although traditional scalar RMs enable efficient and probabilistic reward modeling, they rely on superficial cues… 25 arXiv — NLP / Computation & Language research 11d ago Knowing When to Quit: Diagnosing and Training LLMs to Abort Futile Reasoning arXiv:2607.29211v1 Announce Type: new Abstract: Large language models generate computationally expensive yet semantically void reasoning on beyond-capability tasks, creating risks where plausible-sounding but incorrect derivations mislead users. We characterize this… 37 arXiv — NLP / Computation & Language research 11d ago Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation arXiv:2607.29287v1 Announce Type: new Abstract: Multi-domain machine translation (MDMT) poses a unique challenge due to varying levels of linguistic complexity across domains. Inspired by human translators' ability to adapt reasoning effort based on difficulty, we propose TwT… 33 arXiv — NLP / Computation & Language research 11d ago Evidence-Type Competition: When Can Interventional Data Teach Language Models Causal Direction? arXiv:2607.29484v1 Announce Type: new Abstract: Interventional data is widely regarded as the gold standard for teaching models causal reasoning. We test this assumption in a fully controlled synthetic environment pitting observational correlation against causal effect, and find… 31 arXiv — NLP / Computation & Language research 11d ago TransMem: Transforming Hidden States into Memory for Large Language Models arXiv:2607.29032v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly operate over long interaction histories, where effective reasoning requires identifying and exploiting task-relevant evidence distributed across past observations and actions.… 29 arXiv — NLP / Computation & Language research 11d ago When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering arXiv:2601.19827v5 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) extends large language models (LLMs) beyond parametric knowledge, yet it is unclear when iterative retrieval-reasoning loops meaningfully outperform static RAG, particularly in scientific… 36 arXiv — NLP / Computation & Language research 11d ago Towards the Holographic Characteristic of LLMs for Efficient Short-text Generation arXiv:2601.22546v2 Announce Type: replace Abstract: The recent advancements in Large Language Models (LLMs) have attracted interest in exploring their in-context learning abilities and chain-of-thought capabilities. However, there are few studies investigating the specific… 25 arXiv — NLP / Computation & Language research 11d ago DRIP-R: A Benchmark for Decision-Making and Reasoning Under Real-World Policy Ambiguity in the Retail Domain arXiv:2605.07699v2 Announce Type: replace Abstract: LLM-based agents are increasingly deployed for routine but consequential tasks in real-world domains, where their behavior is governed by inherently ambiguous domain policies that admit multiple valid interpretations. Despite… 14 Hugging Face Daily Papers research 11d ago From RLVR to RLSVR: Task Transformation Induces Self-Verifiable Rewards for Open-Ended LLM Self-Improvement Abstract Reinforcement Learning with Verifiable Rewards (RLVR) has driven recent progress in reasoning-oriented large language models (LLMs) by enabling large-scale optimization. However, its applicability remains largely limited to domains such as mathematics and coding, where… 38 r/MachineLearning community 12d ago [R] CausalVLBench: Benchmarking Visual Causal Reasoning in Large VLMs.   submitted by   /u/moschles [link]   [comments] 5 llama.cpp releases dev-tools 12d ago b10219 cli : persist reasoning_content in chat history ( #26362 ) cli : persist reasoning_content in chat history llama-cli collected reasoning from the stream for display but only stored assistant content in messages, so --reasoning-preserve could not re-inject prior thoughts on later… 22 NVIDIA Developer Blog official-blog 13d ago Co-Designing AI Model Attention for Fast, Interactive Long-Context Inference As agentic and long-context workloads become common, the context lengths increase and attention consumes a larger share of inference time (Figure 1). Because... 20 r/LocalLLaMA community 13d ago Deepseek flash 0731 reasoning is hilarious Tell me this is not funny - " OH MY GOD. I THINK I FINALLY SEE IT!!! The black pixels are at the QUAD CENTERS because of the mipmapping of the UV derivative at the quad DIAGONAL ... no. Hmm." I have never seen a reasoning trace say "OH MY GOD," lol.   submitted by  … 4 Page 5 of 10 · 500 articles ← Newer Older →
