Search: “reasoning”

Decoupling Search from Reasoning: A Vendor-Agnostic Grounding Architecture for LLM Agents

arXiv:2606.18947v2 Announce Type: replace Abstract: Production LLM agents increasingly depend on real-time search, yet native search grounding bundles retrieval policy, provider choice, evidence injec

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Model Releases

Designing Textual Interfaces To Enhance Llm Reasoning On Audio-Visual Question Answering

DGX agent

arXiv:2610.20085v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) has shown strong effectiveness for text-based LLMs and LLM systems, but its application to audio-visual understand

model-releasesarxiv-cs-cl

15 Oct 2026

From Triage to Impact: A Multi-Hop Reasoning Benchmark for Explainable Persian Hate Speech

arXiv:2610.20370v1 Announce Type: new Abstract: Hate speech has become increasingly prevalent on social media, raising concerns about its detection, interpretation, and moderation. Persian, a relative

Applications

Have You Been Convinced? A Neuro-symbolic Argumentation Reasoning Approach to Detecting Persuasiveness in ChangeMyView Discussions

arXiv:2610.15091v1 Announce Type: cross Abstract: Argument structures represent how individual arguments interact within a discourse. However, leveraging these structures to infer meaningful knowledge

applicationsarxiv-cs-ai

Nemotron 3.5 Super VL from @NVIDIAAI is live in LM Studio! • 120B total / 12B active MoE • Supports vision input, reasoning • Trained for vi…

model-releaseslm-studio--x

Nemotron 3.5 Super VL from @NVIDIAAI is live in LM Studio! • 120B total / 12B active MoE • Supports vision input, reasoning • Trained for visual understanding, tool use Requires ~70GB RAM to run local

Reasoning for Propaganda Detection via Label-Guided CoT Optimisation

arXiv:2610.17271v1 Announce Type: new Abstract: Propaganda detection systems usually operate as black boxes, lacking explanations. To address this, we hypothesise that persuasive techniques contain de

ReTAC: Residual Test-Time Agentic Computation for Video Spatial Reasoning

arXiv:2610.16315v1 Announce Type: new Abstract: Test-time agentic computation can improve multimodal large language models (MLLMs) through planning, tool use, iterative perception, and reflection, but

HumanPhys: A Human-Centric Physical-World Perception Benchmark for Real-World Visual Reasoning

arXiv:2610.14679v1 Announce Type: new Abstract: We introduce HumanPhys, a human-centric benchmark for real-world physical perception, and a training corpus emitted by the same pipeline. Each question

PaceReasoner: Label-Free Learning to Answer Briefly from Long Reasoning

arXiv:2610.17900v1 Announce Type: cross Abstract: Extended chain-of-thought reasoning improves problem-solving performance but increases inference cost and latency, motivating more accurate answers wi

safetyarxiv-cs-lg

Tutorials

SHELDON: Reasoning through Dual Search over Hypothesis and Observation Spaces

arXiv:2610.18025v1 Announce Type: cross Abstract: Test-time scaling has enabled LLMs to solve increasingly complex reasoning, discovery, and optimization tasks. However, existing approaches often gath

tutorialsarxiv-cs-lg

VisualCoding: Learning Executable Skills for Reliable Visual Reasoning

arXiv:2610.14403v1 Announce Type: new Abstract: Learning reusable skills can improve visual reasoning agents, yet applying a skill still requires the agent to implement or invoke a procedure and produ

VETR: Execution-Grounded Self-Improving Agent for Symbolic Graphics Reasoning

arXiv:2610.13098v1 Announce Type: new Abstract: Visual agents for symbolic graphics reasoning depend on executable world representations, yet continued improvement remains bottlenecked by ambiguous su

12 Oct 2026

Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology

arXiv:2610.12022v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external

Humanity's Sixth Sense: Benchmarking Intuitive Visual Reasoning in Multimodal Models

arXiv:2610.08966v2 Announce Type: replace Abstract: Humans perceive far more in a scene than what is explicitly depicted: a single glance captures past causes and future trajectories; a quick peek det

Less from More: Reinforcing Sparse Video Reasoning from Dense References

arXiv:2610.10893v1 Announce Type: new Abstract: Video-language models commonly assume that more temporal observations lead to more reliable reasoning. We question this assumption and argue that the ke

researcharxiv-cs-cv

SpaceCast-Bench: Evaluating Predictive Spatial Reasoning in Vision-Language Models

arXiv:2610.12402v1 Announce Type: cross Abstract: Existing spatial reasoning benchmarks mainly test spatial perception: reading off relations already visible in the input. Yet real-world spatial intel

Not All Uncertainty Matters: Simulation-in-the-Loop Fast-Slow Reasoning for Decision-Critical Autonomous Driving System

arXiv:2610.09520v1 Announce Type: new Abstract: Large vision-language models (VLMs) provide powerful open-world perception and reasoning for autonomous driving, but their high computational cost and i

agentsarxiv-cs-ro

8 Oct 2026

Spend Bytes on Breadth: Precision-Count Trade-offs for Decode-Time KV Compression in Long Chain-of-Thought Reasoning

arXiv:2610.05685v2 Announce Type: replace Abstract: Reasoning models write most of their KV cache while decoding long chains of thought (CoT), so the cache has to be compressed online under a fixed me

researcharxiv-cs-cl

8 Oct 2026

TopoCurve: Geometry-Aware Topology Reasoning via Bezier Curves in Autonomous Driving

arXiv:2610.09118v1 Announce Type: new Abstract: Topology reasoning jointly detects 3D lanes and traffic elements from multi-view images and infers their structural connectivity. Current methods model

8 Oct 2026

A Systematic Study of Small Language Models on Abstract Reasoning Tasks

arXiv:2610.08680v1 Announce Type: cross Abstract: Endpoint accuracy on abstract-reasoning benchmarks does not reveal whether a language model has acquired a transferable rule or fit distribution-speci

Adaptive Power Sampling for LLM Reasoning

arXiv:2610.08563v1 Announce Type: new Abstract: Sequence-level power sampling has recently emerged as a training-free approach to reasoning by sampling from a sharpened output distribution of a base l

Medical Image Alignment Assessment as a Test of Generalist Visual Reasoning in Frontier Multimodal Models

arXiv:2610.06896v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) are increasingly positioned as general purpose visual reasoners as part of the quest for artificial ge

Neural Algorithmic Reasoning for Graph Saddle Point Problems

arXiv:2610.07255v1 Announce Type: new Abstract: Neural algorithmic reasoning, or aligning a neural network with an algorithmic paradigm, has emerged as an approach to solving polynomial-time-solvable

safetyarxiv-cs-lg

VeriFine: Scaling Verification for Self-Improvement in Embodied Reasoning

arXiv:2610.08761v1 Announce Type: new Abstract: Self-improving policies continually expose new failure patterns, changing what their judges must be able to verify. However, current fixed judges constr

When Does External Guidance Help LLM Reasoning? A Bias-Variance Theory of Guidance-Augmented GRPO

arXiv:2610.06861v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become the dominant paradigm for eliciting multi-step reasoning in large language models, an

safetyarxiv-cs-cl

ARISE: Adaptive Agentic Reasoning with Image-grounded Self-Evaluation for Interpretable IBD Assessment

arXiv:2610.04777v1 Announce Type: new Abstract: Inflammatory bowel disease (IBD) requires frequent imaging-based assessment, yet interpretation of modalities such as wireless capsule endoscopy (WCE) a

agentsarxiv-cs-cv

6 Oct 2026

DeReAct: Decomposed Reasoning and Acting for Reliable AI Agents

arXiv:2610.02351v1 Announce Type: new Abstract: ReAct-based agents typically rely on a single LLM policy to propose actions, interact with the environment, and decide when a task is complete. This cou

5 Oct 2026

Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier reasoning efficiency - Advance…

Introducing Beam: a highly efficient agentic open model with 501B total parameters and 23B active. - Frontier reasoning efficiency - Advances the Western open frontier on coding & agentic tasks - Trai

agentselon-musk--x

5 Oct 2026

Mental-R1: Aligning LLM Reasoning for Mental Health Assessment

arXiv:2606.13176v2 Announce Type: replace Abstract: Mental health problems such as anxiety, depression, and suicide remain urgent global challenges, where timely and accurate assessment is critical fo

5 Oct 2026

Characterizing a Configuration Where Inference-Time PRM-Pruned Fragment Grafting Is Inert: Evidence from Three Reasoning LMs

arXiv:2610.00047v1 Announce Type: new Abstract: Diversity collapse in parallel chain-of-thought has motivated inference-time interventions built on a natural design: when a process reward model (PRM)

Function-Structured Reinforcement Learning with Executable Verifiers for Mathematical Reasoning

model-releasesarxiv-cs-lg

arXiv:2610.01729v1 Announce Type: new Abstract: Algorithmic mathematical reasoning requires reliable decomposition, computation, and aggregation. Final-answer rewards provide limited guidance on inter

Modeling The Object Representations Underlying Human Physical Reasoning

arXiv:2602.12486v2 Announce Type: replace-cross Abstract: Humans appear to represent objects when reasoning about physics with coarse, volumetric 'bodies' that smooth concavities, trading fine visual

ReSolve: Reusing Candidate Reasoning through Selective Generative Moderation

arXiv:2610.01140v1 Announce Type: new Abstract: Sampling multiple solutions spends computation on intermediate deductions and unfinished arguments as well as final answers. We introduce ReSolve, a tra

Beyond the Shadows of Plato's Cave: Evaluating False Memory in Autonomous Agents via Counterfactual Reasoning

arXiv:2609.39473v1 Announce Type: new Abstract: Autonomous agents increasingly rely on memory to generalize beyond their training environments. However, agents are bounded by what they have seen and b

Local Ai

Frame Differential On-Policy Self-Distillation for Video Reasoning

arXiv:2609.39021v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially improved the reasoning ability of multimodal language models through verifiable rewards and increasingly f

local-aiarxiv-cs-cv

MedRECT: A Bilingual Medical Reasoning Benchmark for Error Correction in Clinical Texts

arXiv:2511.00421v2 Announce Type: replace-cross Abstract: Large language models (LLMs) show promise in medical applications, but their ability to detect and correct errors in clinical texts remains un

MemLife: Curating and Reasoning over Long-Term Egocentric Video Memories

arXiv:2609.40195v1 Announce Type: cross Abstract: Long-term egocentric video enables personalized AI assistants to reason about daily life. However, as video histories grow to hundreds of hours spanni

Network-based Spatial Context Retrieval for Open-weight LLMs: A Faithfulness Benchmark for Grounded Geographic Reasoning

model-releasesarxiv-cs-lg

arXiv:2609.39437v1 Announce Type: new Abstract: Large language models (LLMs) encode substantial latent geographic knowledge, yet they reason poorly over space and are unreliable when queried from coor

SCB: SpeechConversationBench for Evaluating Multi-Turn Reasoning in Speech-to-Speech Models

arXiv:2609.40198v1 Announce Type: cross Abstract: Speech-to-speech systems must solve tasks whose requirements emerge across conversational turns. We introduce SpeechConversationBench (SCB), a focused

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 tr

researcharxiv-cs-cl

ARK: A Dual-Axis Multimodal Retrieval Benchmark along Reasoning and Knowledge

arXiv:2602.09839v2 Announce Type: replace Abstract: Existing multimodal retrieval benchmarks largely emphasize semantic matching on daily-life images and offer limited diagnostics of professional know

CoEM: Empowering Long-Context Reasoning with Commit-on-Evidence Memory

arXiv:2609.36935v1 Announce Type: new Abstract: Long-context reasoning is essential for complex and long-horizon tasks, yet the performance of large language models (LLMs) degrades as context length i

Decoding Affective Nuances: Enhancing MLLMs via Hierarchical Emotion Reasoning and Contrastive Discriminative Pruning

arXiv:2609.36782v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) have demonstrated exceptional capabilities in objective understanding tasks, their performance in affecti

researcharxiv-cs-cv

Diagnosing and Improving Probabilistic Reasoning in Large Language Models

arXiv:2609.38005v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed as decision assistants who must reason probabilistically from available evidence under explicit d

DSPO: Diversity-aware Subjective Policy Optimization for Robust Emotional Reasoning

arXiv:2609.36775v1 Announce Type: new Abstract: Reinforcement Learning has significantly advanced the complex reasoning capabilities of MLLMs. However, prevailing RL algorithms suffer a severe failure

safetyarxiv-cs-cv

FloCA: Towards Faithful and Logically Consistent Flowchart Reasoning

arXiv:2602.14035v2 Announce Type: replace Abstract: Flowchart-oriented dialogue (FOD) systems aim to guide users through multi-turn decision-making or operational procedures by following a domain-spec

IESR:Efficient MCTS-Based Modular Reasoning for Text-to-SQL with Large Language Models

arXiv:2602.05385v2 Announce Type: replace Abstract: Text-to-SQL is a key natural language processing task that maps natural language questions to SQL queries, enabling intuitive interaction with web-b

Hardware

Neurosymbolic Routing for Reliable Reasoning on Resource-Constrained Edge Devices

arXiv:2609.35833v1 Announce Type: new Abstract: Running a language model on edge hardware provides private and low-latency reasoning without a network connection, and yet the small models that fit on

hardwarearxiv-cs-ai