Search: “reasoning”

OUTLETS: Output-Length Prediction from Speculative Decoding Backbones

arXiv:2609.01068v1 Announce Type: new Abstract: The heavy-tailed distribution of output lengths in Large Language Model (LLM) serving poses major challenges for resource provisioning and cluster sched

researcharxiv-cs-cl

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ParaStudent: Closing the Sim2Real Gap in User Simulators for AI Tutor Evaluation

DGX agent

arXiv:2507.12674v3 Announce Type: replace-cross Abstract: Evaluating Artificial Intelligence (AI) tutor feedback before deployment requires anticipating student engagement, typically assessed through

researcharxiv-cs-ai

2 Sept 2026

Physically Plausible Video Generation via Visual-Semantic Chain-of-Events Conditioning

arXiv:2609.00656v1 Announce Type: new Abstract: Physically Plausible Video Generation (PPVG) seeks to synthesize videos consistent with physical principles, yet remains challenging due to underspecifi

researcharxiv-cs-cv

Qwen-Drive-1.0: An Initial Step towards a Vision-Language Foundation Model for Autonomous Driving

arXiv:2609.00111v1 Announce Type: new Abstract: We present Qwen-Drive-1.0, an initial step towards a vision-language foundation model for autonomous driving. Qwen-Drive-1.0 retains the architecture of

ReA-OVCD: Training-Free Open-Vocabulary Change Detection via Semantic-Spatial Reliability Assessment

arXiv:2606.20032v2 Announce Type: replace Abstract: Unlike traditional remote sensing change detection that relies on predefined categories, Open-Vocabulary Change Detection (OVCD) identifies land cov

researcharxiv-cs-cv

Reinforcement Learning Enhanced LLM Agents for Complex Vehicle Routing Problems

arXiv:2609.00859v1 Announce Type: new Abstract: Vehicle Routing Problems (VRPs) are fundamental combinatorial optimization problems with widespread applications in various scenarios. The advanced opti

ReNFT: Repairing Mode Collapse in Reward Post-Training via Internal Probability-Mass Recalibration

arXiv:2609.00061v1 Announce Type: cross Abstract: Reward post-training of diffusion generators inevitably concentrates probability mass on a few reward-favored modes, a mode collapse that erases withi

Replicating TRACE: A Practitioner's Guide to Its Threshold and Particle Budget

model-releasesarxiv-cs-lg

arXiv:2609.01108v1 Announce Type: new Abstract: TRACE (Math & Lienhart, arXiv:2602.01135) reads causal graphs over event types out of a pretrained autoregressive sequence model by thresholding a per-p

Revisiting Face Recognition for Monozygotic Twins: The Celeb Twins Test Set

arXiv:2609.01141v1 Announce Type: cross Abstract: Past literature on face recognition for monozygotic (('identical') twins points to facial marks and mirror asymmetry as possible directions for improv

RingMoClaw: An Experience-Inspired Multi-Agent Framework for Self-Evolving Research in Remote Sensing

arXiv:2609.00814v1 Announce Type: new Abstract: Remote sensing visual models have continuously advanced various interpretation tasks. However, the research process behind model improvement still heavi

agentsarxiv-cs-cv

Socrates went Nuclear: Comparing Interaction Strategies for AI systems in a Learning Context using Brain Sensing

arXiv:2609.00584v1 Announce Type: new Abstract: Does unrestricted AI access bypass the cognitive effort required for learning, or does it streamline knowledge acquisition? This paper reports on a stud

Solaris: Towards Interfaces That Are Generated, Not Coded

arXiv:2609.00776v1 Announce Type: cross Abstract: Digital interfaces are traditionally implemented through intermediate representations such as code, requiring their appearance and behavior to be spec

researcharxiv-cs-ai

Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection

arXiv:2603.02974v2 Announce Type: replace Abstract: DINO models provide rich patch-level representations that have recently enabled strong performance in unsupervised anomaly detection (UAD). Most exi

TEIDAN: A Multilingual Multiparty Dialogue Corpus

arXiv:2609.00802v1 Announce Type: new Abstract: Multi-party interaction is a central setting for human communication and a necessary target for human-agent interaction systems that must participate in

agentsarxiv-cs-cl

Hardware

Text Capability Loss in Vision-Language Adaptation: An Attention-Sink Diagnosis

arXiv:2609.00746v1 Announce Type: new Abstract: Fine-tuning a pretrained LLM into a vision-language model (VLM) can erode the backbone's text capability, with the damage concentrated on tasks that req

hardwarearxiv-cs-lg

The Rise of Verbal Reinforcement Learning

arXiv:2609.01597v1 Announce Type: cross Abstract: Natural language is emerging as a primary feedback channel for improving language agents, capable of conveying intent, preferences, and causal structu

The Visual Insensitivity Gap: Diagnosing When Vision-Language Models Fail to Use Visual Evidence

arXiv:2609.00868v1 Announce Type: cross Abstract: Vision-language models are evaluated by aggregate accuracy on multimodal benchmarks, a practice that implicitly assumes the model uses its visual inpu

researcharxiv-cs-cl

TimeSteer: Inference-Time Speech Scheduling in Joint Audio-Visual Diffusion Models

arXiv:2609.01277v1 Announce Type: cross Abstract: Although pretrained joint audio-visual diffusion models offer rich control over what to generate, they provide no explicit control over when an uttera

Trust Your Guide Only When Certain: Uncertainty-Aware Sparse Alignment at Inference Time

arXiv:2609.00624v1 Announce Type: new Abstract: A prominent paradigm in inference-time alignment employs lightweight supervisors to steer Large Language Models (LLMs). Through empirical analysis, we i

safetyarxiv-cs-cl

UI-Venus-2 Technical Report

arXiv:2609.00028v1 Announce Type: new Abstract: Multimodal GUI agents have emerged as a promising paradigm for digital task automation, yet transitioning from benchmark-oriented models to dependable r

Uncovering and Mitigating Aggregation-Induced Reward Hacking in Multi-Reward Reinforcement Learning

arXiv:2609.00213v1 Announce Type: new Abstract: Reinforcement learning fine-tuning of large language models increasingly adopts multiple reward dimensions, including verifiable rules, task-specific ev

safetyarxiv-cs-cl

Verifiable Disaster Storylines and Causal Knowledge Graphs: A Citation-Grounded Pipeline from Heterogeneous Humanitarian Sources

arXiv:2609.00858v1 Announce Type: new Abstract: Effective humanitarian response depends on the rapid synthesis of heterogeneous, high-volume information sources - a task that routinely exceeds human a

researcharxiv-cs-ai

Local Ai

Vision-Based Leader-Follower Formation Control for Cooperative UAVs in GPS-Degraded Environments

arXiv:2609.01420v1 Announce Type: new Abstract: Cooperation in multi-UAV systems requires reliable relative perception so that follower vehicles can maintain formation and continue their mission safel

local-aiarxiv-cs-ro

ViTAL-X: Video-Text Alignment with Cross-Modal Temporal Edits

arXiv:2609.00505v1 Announce Type: new Abstract: Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues l

WHALE: A Simple Recipe for Joint Harness-Weight Optimization

arXiv:2609.00196v1 Announce Type: cross Abstract: Agent performance depends jointly on the model parameters and the executable harness code that manages context and control flow. Optimizing either com

What Does an Agentic Software Engineering Benchmark Measure? Profiling Task Demands and Agent Behaviour Beyond What Category Labels Reveal

arXiv:2609.01271v1 Announce Type: cross Abstract: Agentic software engineering benchmarks are typically summarized by nominal category labels such as 'bug fix' or 'feature implementation,' yet benchma

Tutorials

What, Where, and How: Probing Spatiotemporal Representations in Video Foundation Models

arXiv:2609.01551v1 Announce Type: new Abstract: Self-supervised video foundation models learn rich spatiotemporal representations, yet it remains unclear what visual concepts these representations enc

tutorialsarxiv-cs-cv

Where the Verifier Fails: A Category-Level Audit of Reward Signals in RLVR

arXiv:2609.01354v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) and standard benchmark evaluation both rely on an automatic verifier that turns a free text answer

A Cognitive Architecture for Shared Autonomy in AUV Operations

arXiv:2608.29347v1 Announce Type: new Abstract: Operators remain essential to Remotely Operated Vehicle (ROV) operation, yet often suffer from low situational awareness and high workload, both of whic

safetyarxiv-cs-ro

A Comprehensive Survey on Multi-Agent Cooperative Decision-Making: Scenarios, Approaches, Challenges and Perspectives

arXiv:2503.13415v2 Announce Type: replace-cross Abstract: With the rapid development of artificial intelligence, intelligent decision-making techniques have gradually surpassed human levels in various

A rigor-matched audit of periodic-step layer skipping for efficient llm inference: conflayers versus swift, with a supplemental analysis of trained routing alternatives

arXiv:2608.28846v1 Announce Type: cross Abstract: Layer-skipping methods for efficient LLM inference decide, at some granularity, which transformer layers to execute for a given input. We present a ri

researcharxiv-cs-ai

Tutorials

Acoustically Grounded Cost Learning for Open-Vocabulary Audio-Visual Semantic Segmentation

arXiv:2608.29121v1 Announce Type: new Abstract: Open-Vocabulary Audio-Visual Semantic Segmentation (OV-AVSS) aims to perform pixel-level segmentation of sound-emitting objects from an open set of cate

tutorialsarxiv-cs-cv

AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs

arXiv:2601.06022v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit complementary strengths arising from differences in pretraining data, model architectures, and decoding b

AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models

model-releasesarxiv-cs-lg

arXiv:2608.29208v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet

AgentLogs: A Dataset for Opening the Black Box of GitHub's Cloud Agent

arXiv:2608.29204v1 Announce Type: cross Abstract: Generative AI-based software engineering agents are becoming routine contributors to real-world software projects. On GitHub, developers can assign ta

AgenTRIM: Tool Risk Mitigation for Agentic AI

arXiv:2601.12449v2 Announce Type: replace-cross Abstract: AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper to

Agents in the Large: Perception-Centered Architecture for Persistent Agents

arXiv:2608.30478v1 Announce Type: new Abstract: Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling a

agentsarxiv-cs-cl

AGM: Achievement-Grounded Memory for Closed-Loop Agents with Frozen VLA Policies

arXiv:2608.29537v1 Announce Type: cross Abstract: Frozen vision-language-action (VLA) policies offer broad manipulation skills but execute open-loop action chunks without tracking task progress, so th

AlgoWorlds: Benchmarking Tool Use for Global Optimization in Algorithmic Worlds

arXiv:2608.29397v1 Announce Type: new Abstract: Tool-use benchmarks generally evaluate whether an agent completes a workflow using appropriate tools and valid arguments. However, feasibility alone is

Aligning Multi-Trajectory Supervision with Policy Optimization for VLA Driving

arXiv:2608.30122v1 Announce Type: cross Abstract: Vision-language-action (VLA) driving methods increasingly combine multi-trajectory imitation learning with group-relative policy optimization (GRPO),

Amortizing intractable inference in large language models

arXiv:2310.04363v3 Announce Type: replace-cross Abstract: Autoregressive large language models (LLMs) compress knowledge from their training data through next-token conditional distributions. This lim

safetyarxiv-cs-cl

AnnotateAnything: Automatic Annotation of 3D Assets for Robot Manipulation

arXiv:2606.17446v2 Announce Type: replace-cross Abstract: Simulation enables scalable robot data collection, but raw 3D assets provide only geometry, lacking the semantic, interactive, and physical kn

Applications

Auditing Anonymous AI Models: A Four-Stage Protocol for Black-Box Identity Verification

arXiv:2608.31142v1 Announce Type: cross Abstract: The 2025--2026 AI market has seen a wave of stealth releases: frontier models launched anonymously on developer platforms under codenames. For their u

applicationsarxiv-cs-ai

Automated Testing of LLM-Based Post Hoc Explainers Using Model Checking as an Oracle

arXiv:2608.30581v1 Announce Type: new Abstract: Large language models (LLMs) are used as post hoc explainers of sequential decision-making policies, producing natural-language explanations of why an a

Automatic Conversion of NICE Guidelines to an Executable Computational Model Using Large Language Models

arXiv:2608.30022v1 Announce Type: new Abstract: Introduction: NICE guidelines provide evidence-based recommendations for clinical care but remain largely in unstructured natural language. Existing app

A.X K2 Technical Report

arXiv:2608.30181v1 Announce Type: new Abstract: We introduce A.X K2, a 688B-parameter Mixture-of-Experts (MoE) language model trained from scratch as a high-performance foundation for agentic applicat

Beyond Correctness: Validity-Oriented Evaluation of Biomedical LLM Judges

arXiv:2608.29127v1 Announce Type: new Abstract: We propose a scalable, validity-oriented pipeline for evaluating biomedical LLM judges when high-quality human judgments are scarce. First, we augment e

Beyond Semantic Similarity: Reducing Unnecessary API Calls via Behavior-Aligned Retriever

arXiv:2508.14323v3 Announce Type: replace Abstract: Tool-augmented LLMs invoke external functions to extend their capabilities, but errors in the invocation decision, such as calling a tool when none