Search: “reasoning”

VisualWorldBench: A Fine-Grained Multi-Task Benchmark for Evaluating Visual World Knowledge in MLLMs

arXiv:2610.20083v1 Announce Type: new Abstract: Visual world knowledge is a core capability of multimodal large language models (MLLMs), underpinning knowledge-intensive visual question answering and

15 Oct 2026

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Where to Start, How to Move: Analyzing Curricula under GRPO for Long-Horizon LLM Agents

DGX agent

arXiv:2610.19349v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) provides no reward-relative learning signal when all rollouts receive identical rewards. In long-horizon tas

safetyarxiv-cs-cl

15 Oct 2026

Local Ai

Anomaly-Guided Observation and Two-Level Semantic Feedback for Training-Free Video Anomaly Analysis

arXiv:2610.16324v1 Announce Type: new Abstract: Training-free language-based video anomaly detection (VAD) uses frozen vision--language models (VLMs) and large language models (LLMs) to localize abnor

local-aiarxiv-cs-cv

Auditing Failure Attribution: Label Predictability and Judge Behavior

arXiv:2610.17747v1 Announce Type: cross Abstract: Failure-attribution benchmarks ask an LLM judge which step or agent caused a failure. A high score should mean the judge checked the faulty step again

Bayesian Test-Time Inference of Task-Aligned Similarity from Weak Interactive Feedback

arXiv:2610.18656v1 Announce Type: new Abstract: Language model systems repeatedly make test-time decisions by comparing similarity: they retrieve exemplars, rank candidates, and revise responses. Yet

Checking the Checkers: A Synthesis of Verifier Noise and Robustness in RLVR

arXiv:2610.17824v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a principal recipe for improving the reasoning of large language models (LLMs). It rest

safetyarxiv-cs-lg

ChunkAct: Action Chunking for Agentic Robotics

arXiv:2610.18874v1 Announce Type: cross Abstract: Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, motion, and vision-language-action

Conditional Multi-Event Temporal Grounding in Long-Form Video

arXiv:2606.15320v2 Announce Type: replace Abstract: Multimodal large language models have made rapid progress in video temporal grounding, yet real-world applications routinely require localizing ever

D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control

arXiv:2610.17114v1 Announce Type: new Abstract: Frontier large language models (LLMs) now reason about space well enough to program robots, yet the world models behind robot policies are implicit, hel

EventLens: Event-Structure Reinforcement Learning for Video Understanding

arXiv:2610.16172v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure tha

safetyarxiv-cs-cv

Explainable Visual Anomaly Detection via Concept Bottleneck Models

arXiv:2511.20088v3 Announce Type: replace Abstract: In recent years, VAD (Visual Anomaly Detection) has attracted significant attention due to its high interpretability, as it provides visual explanat

researcharxiv-cs-cv

Local Ai

Failure Recovery via Belief Updates and World Modeling for Long-Horizon Agents

arXiv:2610.18082v1 Announce Type: new Abstract: Long-horizon agents often struggle to recover from failures whose causes lie several steps earlier, beyond what local reflection or backtracking can res

local-aiarxiv-cs-lg

Local Ai

G^2WAM: World Action Models for Efficient and Geometry Grounded Image-Goal Navigation

arXiv:2610.16558v1 Announce Type: cross Abstract: World models capture environment dynamics and support counterfactual reasoning for planning. In image-goal navigation, where the target often lies bey

local-aiarxiv-cs-ro

GA-SVD: Generation-aware Singular Value Decomposition for LLM Compression

arXiv:2610.15398v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong generalization across a broad range of reasoning and generation tasks, but their large parameter counts

Learning Robust Visuomotor Policies via Dynamics Alignment

arXiv:2510.27114v2 Announce Type: replace-cross Abstract: Generative BC policies model expert action distributions well, but they do not explicitly reason about what scene a candidate action would pro

safetyarxiv-cs-lg

Tutorials

LLM-to-Flow Distillation: Teaching Natural Language Goals to Scientific Generators

arXiv:2610.17246v1 Announce Type: new Abstract: Generative discovery in science requires coupling high-level scientific reasoning with the ability to generate samples respecting the structure of a des

tutorialsarxiv-cs-lg

LynxScenes: A Large-Scale Real-World Benchmark for Outdoor Wheel-Legged Robot Perception, Navigation, Imagination and Reconstruction

arXiv:2610.18093v1 Announce Type: new Abstract: Wheel-legged robots operating in outdoor spaces shared with humans require accurate perception, socially compliant navigation, future-scene reasoning, a

MemAct: Streaming Spatial Understanding with Memory and Active Exploration

arXiv:2610.17640v1 Announce Type: new Abstract: Spatial understanding is essential for embodied agents navigating and interacting with the physical world. As observations arrive incrementally, agents

agentsarxiv-cs-cv

MERIT: Scaling KG Foundation Models with Relation Transformers

arXiv:2610.15638v1 Announce Type: new Abstract: Knowledge graph (KG) foundation models (KGFMs) predict links on unseen graphs zero-shot. KGFMs have been pioneered by ULTRA which builds a relation grap

Neural Bayesian Networks for Modular and Scalable Decision-Making Under Uncertainty

arXiv:2610.16902v1 Announce Type: cross Abstract: Bayesian Networks (BNs) are established tools for letting agents reason under uncertainty in sequential decision-making. They split a joint distributi

Observe, Share, or Predict? Disentangling Partner Information in Embodied Multi-Agent Collaboration

arXiv:2610.16895v1 Announce Type: cross Abstract: LLMs are used as high-level controllers for embodied agents, but it remains unclear whether they support collaborative reasoning, such as anticipating

Omni-Modal LLMs Know More Than They Say

arXiv:2610.16135v1 Announce Type: cross Abstract: Omni-modal large language models (Omni-LLMs) extend LLMs to process heterogeneous modalities (e.g., vision, audio, and IMU signals) alongside language

safetyarxiv-cs-cv

Pixels or Code? Benchmarking Instruction-Guided Visual Artifact Operation

arXiv:2610.16444v1 Announce Type: new Abstract: Visual artifacts such as charts, technical diagrams, webpages, and document pages underpin scientific, commercial, and engineering workflows. Editing th

agentsarxiv-cs-cv

Tutorials

PixSearch: Region-Grounded Retrieval for Knowledgeable Large Multimodal Models

arXiv:2601.19060v2 Announce Type: replace Abstract: Multimodal Retrieval-Augmented Generation (MM-RAG) augments visual question answering (VQA) with external knowledge, but many systems rely on modula

tutorialsarxiv-cs-cv

Probe and Skip: Self-Predictive Token Skipping for Efficient Long-Context LLM Inference

arXiv:2601.13155v3 Announce Type: replace-cross Abstract: Long-context inference enhances the reasoning capability of Large Language Models (LLMs), but incurs significant computational overhead. Token

RSAJEV: Training-Free Abstaining Prototype Memory for Eliminating Silent Hallucination in JEV-Based Remote Sensing Classification

arXiv:2610.15742v1 Announce Type: new Abstract: Scene classification of remote sensing imagery with multimodal large language models (MLLMs) is formulated as a single-forward-pass decision problem: ca

researcharxiv-cs-cv

RSIgen: Reciprocal Self-Improvement for Agentic Visual Generation

arXiv:2610.18688v1 Announce Type: new Abstract: Agentic visual generation produces experience that can improve the native understanding (agent) and generation roles of a unified multimodal backbone, b

Sharper Frames, Worse Rooms: Viewpoint Coverage Dominates Image Quality in Feed-Forward 3D Reconstruction

arXiv:2610.15854v1 Announce Type: new Abstract: Grounded spatial reasoning about indoor scenes rests on a geometric reconstruction that the multimodal system does not itself produce. Feed-forward mult

researcharxiv-cs-cv

Spectral-Driven Adaptive-Rank Optimizer for Large Language Model Reinforcement Learning with Verifiable Rewards

arXiv:2610.16533v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is reshaping how large language models (LLMs) acquire reasoning capabilities, yet the optimizers

Tiny Recursive Message Passing

arXiv:2610.18649v1 Announce Type: new Abstract: Message passing neural networks have shown remarkable performance in algorithmic and constraint reasoning, due to their ability to encode the structure

VbotNav-0: Asynchronous Cloud-Edge Dual-Policy Navigation across Indoor and Outdoor Environments

arXiv:2610.14634v1 Announce Type: new Abstract: Continuous indoor-outdoor navigation connects destination-level reasoning with motion decisions that must respond to current observations. We present Vb

safetyarxiv-cs-ro

What Can Language Models Inherit from Solomonoff Induction? Limits, Attainable Properties, and What Served Conditionals Reveal

arXiv:2610.14007v1 Announce Type: new Abstract: A familiar line of reasoning runs as follows: language models are flexible approximators trained under a strictly proper loss, so scale brings them clos

Applications

Where is the multimodal goal post? On the Ability of Foundation Models to Recognize Highlights in Videos

arXiv:2601.16333v3 Announce Type: replace Abstract: Foundation models are used for many real-world applications involving language understanding and generation from temporally-ordered multimodal event

applicationsarxiv-cs-cv

World2TS: Real-World Event Context for Time-Series Forecasting

arXiv:2610.14861v1 Announce Type: new Abstract: Time-series forecasting plays a vital role in a wide range of real-world applications. Recent approaches have achieved strong performance by modeling te

agentsarxiv-cs-lg

Agentic Large Language Models

arXiv:2610.13455v1 Announce Type: new Abstract: Large language models (LLMs) have taken the world by storm. Their ability to communicate with us in our own language, and to reason about our world, has

agentsarxiv-cs-ai

Attention Sees, MLP Refuses: Tracing the Attention-to-MLP Safety Pathway in LLMs

model-releasesarxiv-cs-ai

arXiv:2610.13078v1 Announce Type: new Abstract: Safety-aligned large language models (LLMs) remain vulnerable to jailbreaks and can over-refuse benign requests. Understanding these failures requires d

AutoIndexer: Flexible-Order Decoding by Training Causal Models on Chains of Edits

arXiv:2610.12545v1 Announce Type: cross Abstract: Autoregressive decoding is less suited to non-causally ordered data, e.g., cross-references or future dependencies, since their outputs cannot be revi

researcharxiv-cs-ai

BT-Agent: Deploying Onboard Robot Agents with Behavior Trees and Multi-Fidelity Evaluation

arXiv:2610.13862v1 Announce Type: new Abstract: Deploying language-model agents onboard mobile robots requires task reasoning and responsive execution within limited compute and memory. We propose BT-

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. Aut

safetyarxiv-cs-cl

Gamma: Grounded Multi-Agent Memory with Mechanical Audit for Memory-Intensive Manipulation

arXiv:2610.12793v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) policies fail on memory tasks, behaviour that depends on events observed long before the current frame, because

Generalized Proximal Policy Optimization: Unifying LLM RL Algorithms from the Perspective of Divergence

arXiv:2610.13015v1 Announce Type: cross Abstract: Reinforcement learning has become the foundational paradigm for enhancing the reasoning capabilities of LLMs. Yet the dominant approach, Proximal Poli

safetyarxiv-cs-ai

JitterVLA: A Replay Benchmark for Motion Quality in VLA-Driven Human-Robot Manipulation

arXiv:2610.13628v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies issue sparse targets whose arrival at the robot controller is delayed and irregular, so a reasonable predicted a

MoPrO-SD: Modular Prompt Optimization for Stance Detection

model-releasesarxiv-cs-cl

arXiv:2610.13386v1 Announce Type: new Abstract: Stance detection remains challenging for large language models (LLMs) due to implicit opinions, sarcasm, and context-dependent expressions of stance. Al

Tutorials

One-Step Text Generation by Seq-Drifting

arXiv:2610.12879v1 Announce Type: new Abstract: Diffusion language models generate tokens in parallel, but still require multiple sampling steps to produce high-quality text. In this paper, we investi

tutorialsarxiv-cs-ai

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 sam

researcharxiv-cs-cl

PRIME: Pre-Retrieval Index Modeling Enhancement for Structured Document Retrieval-Real

arXiv:2610.13296v1 Announce Type: cross Abstract: High-precision retrieval over external knowledge bases is essential for LLM agents to operate effectively. However, existing Information Retrieval (IR

researcharxiv-cs-ai

Hardware

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 add

hardwarearxiv-cs-cl

S^3R: Fast and Faithful RL Rollouts via Self-Sparse Speculative Decoding

model-releasesarxiv-cs-cl

arXiv:2610.13202v1 Announce Type: cross Abstract: Fast rollout generation for long-context reinforcement learning with verifiable rewards (RLVR) requires reducing KV-cache traffic without changing the