Search: “reasoning”

Collapse, Not Complexity: Failure-Conditioned Decomposition Repair for End-to-End Document Parsing

arXiv:2609.23592v1 Announce Type: cross Abstract: End-to-end document parsers increasingly offer an optional reasoning mode for complex pages. On a 180-page entropy-stratified discovery sample with on

22 Sept 2026

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Agents

CTRL: Control-Based Time Series Forecasting with LLM-Guided Residual Learning

DGX agent

arXiv:2609.23257v1 Announce Type: cross Abstract: Time series forecasting underpins critical decision-making across diverse domains. While large language models (LLMs) offer promising reasoning capabi

agentsarxiv-cs-cl

22 Sept 2026

Information-Time Proximal Policy Optimization

arXiv:2609.24380v1 Announce Type: new Abstract: RLVR has substantially improved the reasoning capabilities of LLMs. However, existing methods typically parameterize temporal progression in the Markov

safetyarxiv-cs-lg

22 Sept 2026

Tool-Augmented On-Policy Distillation for LLM Domain Adaptation in Sequence-Based Omics Tasks

arXiv:2609.23435v1 Announce Type: cross Abstract: Multi-omics sequences contain complex biological patterns, yet deciphering their mechanisms for automated scientific discovery remains challenging. As

22 Sept 2026

50+ Hours and 100M+ Tokens Later, Open Source Autonomous Agent is GETTING CLOSER at Solving an Open Math problem

model-releasesr-localllama

This experiment is live, you can inspect all the internal reasoning, memories, attempts here: https://artificium-covering-experiment.gr.bio/ The problem that the agent is trying to solve is a covering

21 Sept 2026

Beyond Exact Match: Task-Aware GRPO for Cross-Domain PCBA Visual Question Answering

arXiv:2609.21276v1 Announce Type: cross Abstract: In automated Printed Circuit Board Assembly (PCBA) inspection, standards-guided decisions require systems to jointly reason over fine-grained visual c

21 Sept 2026

PRIME: Perception Feedback with Situational Memory Embeddings in VLA Models

arXiv:2609.22040v1 Announce Type: new Abstract: Current Vision-Language-Action (VLA) models for autonomous driving operate primarily through feedforward inference across the perception--reasoning--pla

21 Sept 2026

Attention Dispersion as a Diagnostic Signal for Hallucination in Large Language Models

arXiv:2609.18320v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit hallucinations, presenting a major barrier to reliability in complex reasoning tasks. While traditional

safetyarxiv-cs-cl

CapMem: A Benchmark for Caption-Based Episodic Memory in Egocentric Video

arXiv:2609.17688v1 Announce Type: new Abstract: Wearable assistants require episodic memory over egocentric video, yet current vision-language models face bounded frame budgets, growing visual-token c

HALT: Hallucination Assessment via Log-probs as Time series

arXiv:2602.02888v2 Announce Type: replace-cross Abstract: Hallucinations remain a major obstacle for large language models (LLMs), especially in safety-critical domains. We present HALT (Hallucination

Label-free steering: Compressing test-time reinforcement learning into bias-only subspaces

arXiv:2609.18587v1 Announce Type: cross Abstract: Test-time reinforcement learning (TTRL) enables models to improve their reasoning without relying on labeled training data, but existing approaches ty

MUSE: Benchmarking Large Vision-Language Models on Multi-Modal Understanding in Situated Education

arXiv:2609.19088v1 Announce Type: new Abstract: Large vision-language models have achieved remarkable progress in multi-modal understanding, yet their capabilities in educational settings remain insuf

UAVs Meet Embodied Intelligence: Bridging Human Intents and Flying Dynamics Via Harnessing Physical-Digital AI Agents

arXiv:2609.18326v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) extend embodied intelligence into continuous three-dimensional space, where perception, reasoning, physical embodiment,

agentsarxiv-cs-ro

Visual Compliance via Executable Safety Rule Entailment

arXiv:2609.18328v1 Announce Type: new Abstract: Recent advances in LLMs and VLMs have enabled safety systems to reason beyond simple risk patterns toward more contextual and semantic safety concerns.

Available but Unclaimed: An Empirical Study of Human-AI Synergy

arXiv:2609.16793v1 Announce Type: cross Abstract: People increasingly reason with large language models (LLMs), yet complementary capabilities do not guarantee outperforming both components. In a betw

16 Sept 2026

Script Fragmentation and Format: What Drives the English-Bengali Performance Gap in Open LLMs?

arXiv:2507.23248v2 Announce Type: replace Abstract: Bengali is spoken by more than 230 million people, yet no standardized instrument evaluates large language models (LLMs) on Bengali across the task

16 Sept 2026

Beyond Depth and Width: The Information-Slack Dilemma in Streaming Test-Time Compute

arXiv:2609.14995v1 Announce Type: new Abstract: The same task and compute budget can require different reasoning policies when evidence arrives in a different order. Early computation has more time to

researcharxiv-cs-cl

Applications

Beyond OCR Accuracy: Text-Centric VQA Under Image Degradation with Modular and End-to-End

arXiv:2609.13815v1 Announce Type: new Abstract: Text-centric Visual Question Answering (VQA) requires reading and reasoning over text embedded in images, a task made substantially harder when images s

applicationsarxiv-cs-cv

Bridging Thought and Action: Taming Long-Horizon Instability in Open-Source LLM Agents with a MetaTool-Enhanced ROS Framework

arXiv:2609.13335v1 Announce Type: cross Abstract: Large Language Models (LLMs) have enabled more natural human-robot interaction, but open-source models often exhibit unstable long-horizon reasoning a

agentsarxiv-cs-ai

Compositional SVG Generation via VLM-Driven Hierarchical Semantic Parsing

arXiv:2609.14657v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) excel at visual reasoning, generating structured, editable Scalable Vector Graphics (SVG) remains a fundamental ch

HISPO: Hierarchical Importance-Sampling Policy Optimization with Entropy-Derived Segments

arXiv:2609.15471v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a central approach for improving mathematical reasoning in language models, but long-fo

MedVA: An End-to-End Neuro-Symbolic Agentic System for Medical Volume Visualization

arXiv:2609.14874v1 Announce Type: cross Abstract: Medical volume visualization requires selecting regions of interest (ROIs) and carefully controlling their relative visual emphasis according to a giv

agentsarxiv-cs-cv

SALUTE: Benchmarking and Adapting LLMs for the Defense Domain

arXiv:2609.15022v1 Announce Type: new Abstract: Defense is a knowledge-intensive domain that requires precise understanding of specialized terminology, doctrinal concepts, operational procedures, and

R2VC: Modular Fact-Checking with Retrieval, Verification, and Confidence Calibration

arXiv:2609.11955v1 Announce Type: new Abstract: Large language models are increasingly used for automated fact checking, but end-to-end prompting often entangles evidence retrieval, reasoning, and unc

researcharxiv-cs-cl

14 Sept 2026

Local Ai

internlm/Intern-S2 · Hugging Face

from internlm: We introduce Intern-S2-397B, our most capable multimodal foundation model for scientific intelligence and long-horizon agents. Intern-S2-397B scales along three critical dimensions: pre

local-air-localllama

13 Sept 2026

Caption-once, Frames-on-Demand: Visual-Need Routing for Budget-Aware Agentic Long Video Understanding

arXiv:2609.11899v1 Announce Type: new Abstract: Long-video understanding on edge devices must reason over hours of content under tight compute and bandwidth budgets. Subsampling visual tokens loses te

agentsarxiv-cs-cv

LexAgentHallu: A Hierarchical Benchmark for Profiling Hallucinations in Legal Agents

arXiv:2609.09754v1 Announce Type: new Abstract: As large language models are increasingly deployed as tool-augmented legal agents, they introduce agentic hallucinations where tool-call and reasoning e

OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis

arXiv:2603.20278v2 Announce Type: replace-cross Abstract: Training deep research agents requires long-horizon trajectories that interleave search, evidence aggregation, and multi-step reasoning. Howev

agentsarxiv-cs-cl

Towards Reliable Medical LLMs: Benchmarking and Enhancing Confidence Estimation of Large Language Models in Medical Consultation

arXiv:2601.15645v2 Announce Type: replace Abstract: Large-scale language models (LLMs) often offer clinical judgments based on incomplete information, increasing the risk of misdiagnosis. Existing stu

From Version Conflicts to Decision Conflicts: Selective Revalidation for Long-Running AI Agents

arXiv:2609.08015v1 Announce Type: new Abstract: Long-running AI agents may read state, reason, wait for tools or human approval, and perform an external action much later. The state that justified the

agentsarxiv-cs-ai

10 Sept 2026

SkillAlign: Aligning Skill Interfaces for LLM-based Agents

arXiv:2609.07255v1 Announce Type: new Abstract: Language-model agents increasingly rely on skills: reusable procedural knowledge for reasoning, tool use, and interaction. Existing work studies how ski

10 Sept 2026

What Does MMLU Actually Measure? A Psychometric Audit of Difficulty Structure in Aggregate Benchmark Scores

arXiv:2609.09372v1 Announce Type: cross Abstract: Although MMLU is widely adopted as a benchmark for calibrating general AI capabilities, we psychometrically demonstrate that its aggregate score prima

10 Sept 2026

3DHarnessBench: Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models

arXiv:2609.06535v1 Announce Type: new Abstract: We introduce 3DHarnessBench, a benchmark that evaluates the agentic ability of frontier vision-language models (VLMs) to recover 3D geometry as Blender

BanglaMemeX: Advancing Cultural Metaphoric Image Interpretation in Bangla with a Multimodal Explainable Dataset

arXiv:2609.08029v1 Announce Type: cross Abstract: Vision Language Models have achieved strong performance on multimodal benchmarks, yet their ability to reason about culturally grounded and metaphor-r

ChatBEV: Empowering Traffic Scene Understanding and Simulation via Vision-Language Model

arXiv:2503.13938v3 Announce Type: replace Abstract: Comprehensive traffic scene understanding is a foundational capability for Intelligent Transportation Systems (ITS) underpinning applications such a

From Gaze to Meaning: A Training-Free AI Agent for Unified Grounding and Explanation

arXiv:2609.06208v1 Announce Type: new Abstract: Understanding human attention is fundamental for scene interpretation, yet existing approaches often rely on heavily trained models that lack interpreta

agentsarxiv-cs-cv

I Don't Miss You, but I Do: Self-Explanation Faithfulness of Modality Missingness in Vision-Language Models

arXiv:2609.07596v1 Announce Type: cross Abstract: Vision-language models are increasingly used in settings where some input modalities may be unavailable, yet we know little about whether they can fai

researcharxiv-cs-cv

Applications

SpatialBlock: Enhancing Spatial Intelligence in LVLMs via Synthetic Block-Stacking Problem

arXiv:2609.07064v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have achieved strong performance on diverse visual tasks, yet their ability to reconstruct and reason about the 3D

applicationsarxiv-cs-cv

inclusionAI/Ling-3.0-flash-VL · Hugging Face

model-releasesr-localllama

Ling-3.0-flash-VL inherits the language, reasoning, and long-context capabilities of Ling-3.0-flash, while extending them with native image and video understanding. The model has 124B total parameters

8 Sept 2026

Tutorials

Beyond Retrieval: Progressive Latent Memory Evolution for Streaming Video Understanding

arXiv:2609.04131v1 Announce Type: new Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to process continuous visual inputs and respond to user queries under st

tutorialsarxiv-cs-cv

DE-Venus: A Data-Efficient RLVR Framework for Large Language Models

arXiv:2609.03324v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves large language model reasoning, but its practical scaling is constrained by expensive on-

safetyarxiv-cs-lg

Even Qwen3.8 followed the instruction inside my translation data, and Gemma 4 beat the translation specialists I tested

model-releasesr-localllama

A month ago I posted about Gemma sometimes solving the reasoning problems inside my translation data instead of translating them. A few people suggested two very fixes, which is to use a proper transl

Instruction Duplication as an Inference-Time Control Primitive

arXiv:2609.04024v1 Announce Type: new Abstract: Procedural instruction following is a basic requirement for controllable language-model systems, especially when generated trajectories are inspected or

researcharxiv-cs-ai

Principia: Relational Physics Tests for Video Models

arXiv:2609.04200v1 Announce Type: new Abstract: Evaluating physical reasoning in video models is difficult because absolute motion measurements depend on frame rate, object scale, and camera calibrati

AGI Maze Prediction Datasets: A Compact Benchmark for Learning World Dynamics with Transformers

arXiv:2609.02339v1 Announce Type: cross Abstract: World modeling requires a predictive model to maintain and update an internal state adequate for reasoning about the consequences of actions. We intro

Cliff: Learning Process Rewards from the First Mistake

arXiv:2609.02817v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for large language model (LLM) post-training, but its reliance

safetyarxiv-cs-lg

Post-Training Language Models for Gold-Medal Performance in Coding Competitions

arXiv:2609.02849v1 Announce Type: cross Abstract: Competitive programming has become a key test of large language model reasoning, with international competitions such as IOI and ICPC representing its

The Ceiling Is in the Channel: Auditing Learner Gaps and Measurement Frontiers in Clinical Prediction

arXiv:2609.01909v1 Announce Type: new Abstract: Clinical prediction can saturate for two different reasons: a fitted learner may fail to extract available information, or the recorded variables may im

researcharxiv-cs-ai