Search: “reasoning”

Test-Time Compute Scaling for ASR with Depth-Conditioned Looped Transformers

arXiv:2606.04678v1 Announce Type: new Abstract: End-to-end ASR systems typically use fixed-depth acoustic encoders at inference, making it difficult to trade additional test-time computation for impro

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The Saturation Trap and the Subjectivity of Intervention Timing: Why Affect-Based Triggers and LLM Judges Fail to Time Interventions on Autonomous Agents

DGX agent

arXiv:2606.04296v1 Announce Type: new Abstract: As autonomous AI agents move from conversational systems to long-horizon software execution, runtime safety layers that decide when to interrupt an agen

model-releasesarxiv-cs-ai

4 Jun 2026

Thinking Through Signs: PEEL as a Semiotic Scaffolding for Epistemically Accountable AI-Enabled Research

arXiv:2606.04152v1 Announce Type: new Abstract: Large language models are reshaping research practice while quietly eroding researchers epistemic accountability. This commentary introduces PEEL - Prot

T^star: Progressive Block Scaling for Masked Diffusion Language Models Through Trajectory Aware Reinforcement Learning

arXiv:2601.11214v5 Announce Type: replace Abstract: We present T^star, a simple TraceRL-based training curriculum for progressive block-size scaling in masked diffusion language models (MDMs). Startin

WAM-Nav: Asymmetric Latent World-Action Modeling for Unified Visual Navigation

arXiv:2606.04907v1 Announce Type: new Abstract: Visual navigation requires generating smooth and collision-free trajectories under complex geometric and physical constraints. Existing reactive policie

safetyarxiv-cs-ro

When Clients Stop Following: A Cognitive Conceptualization Diagram-driven Framework for Strategic Counseling

arXiv:2606.04389v1 Announce Type: new Abstract: Large Language Models (LLMs) show promise in psychological counseling, yet existing benchmarks rely heavily on highly cooperative simulated clients. We

A 3D Isovist World Model -- Revealing a City's Unseen Geometry and Its Emergent Cross-City Signature

arXiv:2606.03609v1 Announce Type: cross Abstract: Embodied agents that navigate cities rely on world models that predict how their surroundings will change as they move. But for navigation, what matte

Tutorials

A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners

arXiv:2606.03685v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) improves end-to-end classical planning in large language models (LLMs), but do these models also learn to represent and r

tutorialsarxiv-cs-ai

Anomalies in Multivariate Time Series Benchmarks Are Mostly Univariate

arXiv:2606.02670v1 Announce Type: cross Abstract: Many recent multivariate time series anomaly detection (MT-SAD) models incorporate cross-channel modeling, under the implicit assumption that the stru

researcharxiv-cs-ai

AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following

arXiv:2606.03116v1 Announce Type: cross Abstract: The rapid advancement of instruction-guided audio generation has highlighted the critical need for robust alignment evaluation. Current automated eval

ASymPO: Asymmetric-Scale Policy Optimization for Asynchronous LLM Post-Training Without Behavior Information

arXiv:2606.03070v1 Announce Type: cross Abstract: Asynchronous reinforcement learning can improve language-model post-training throughput by decoupling response generation from policy optimization, bu

AVTrack: Audio-Visual Tracking in Human-centric Complex Scenes

arXiv:2606.02724v1 Announce Type: cross Abstract: Audio-visual speaker tracking aims to localize and track active speakers by leveraging auditory and visual cues, enabling fine-grained, human-centric

Benchmarking Visual State Tracking in Multimodal Video Understanding

model-releasesarxiv-cs-cv

arXiv:2606.03920v1 Announce Type: new Abstract: Understanding a video requires more than recognizing isolated moments, as humans continuously track entities, states, and events over time. This capacit

Beyond the Literal: Decomposing Pragmatic Intent in Multimodal Meme Understanding

arXiv:2606.03604v1 Announce Type: new Abstract: When asked what a meme or sarcastic post means, Large Vision Language Models (LVLMs) tend to describe what the image shows rather than what the author i

Can Structural Cues Save LLMs? Evaluating Language Models in Massive Document Streams

model-releasesarxiv-cs-cl

arXiv:2603.19250v2 Announce Type: replace Abstract: Evaluating language models in streaming environments is critical, yet underexplored. Existing benchmarks either focus on single complex events or pr

Closed-Loop Molecular Design with Calibrated Deference

arXiv:2606.02618v1 Announce Type: cross Abstract: We present Cognitive Loop via In-Situ Optimization (CLIO), an agent that couples a continuously-updated belief-state graph with a recursive plan-then-

Applications

Core-based Hierarchies for Efficient GraphRAG

arXiv:2603.05207v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by incorporating external knowledge. However, existing vector-based method

applicationsarxiv-cs-cl

Local Ai

DMT-CBT: Longitudinal Therapeutic State Modeling for CBT Counseling

arXiv:2606.03132v1 Announce Type: new Abstract: Large language models (LLMs) have shown growing potential for Cognitive Behavioral Therapy (CBT) counseling. However, most existing approaches still for

local-aiarxiv-cs-cl

Do Explanations Increase the Risk of Decision Logic Leakage? Explanation-Guided Stealing of Graph Models

arXiv:2506.03087v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have become essential tools for analyzing graph-structured data in domains such as drug discovery and financial a

Applications

Does Language Shift Break Medical Vision-Language Models? Indonesian Radiology Visual Question Answering Case Study

arXiv:2606.03693v1 Announce Type: new Abstract: Medical Vision-Language Models (VLMs) are typically evaluated on English radiology visual question answering benchmarks, leaving their robustness under

applicationsarxiv-cs-cl

DyaPlex: Full-Duplex Speech-Motion Model for Dyadic Interaction

arXiv:2606.03874v1 Announce Type: new Abstract: We present DyaPlex, a streaming, full-duplex speech-and-motion model designed for dyadic interaction. To capture the continuous and reciprocal nature of

agentsarxiv-cs-cv

Enginuity: A Dataset and Benchmark for Vision-Language Understanding of Engineering Diagrams

model-releasesarxiv-cs-cv

arXiv:2606.03410v1 Announce Type: new Abstract: Engineering diagrams pose a distinct challenge for vision-language models: unlike natural images or general documents, they encode information through d

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

arXiv:2606.03812v1 Announce Type: new Abstract: Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems, demand reliable hazard identifica

EvoTrainer: Co-Evolving LLM Policies and Training Harnesses for Autonomous Agentic Reinforcement Learning

arXiv:2606.03108v1 Announce Type: new Abstract: Autonomous LLM training is often framed as recipe search, which leaves the training harness largely static. This limitation sharpens in agentic RL, wher

Tutorials

Formalizing the Binding Problem

arXiv:2606.03976v1 Announce Type: cross Abstract: Representations of the world, arguably, contain information about features (e.g. something is blue, something is a circle) but also information about

tutorialsarxiv-cs-ai

From Control Boundary to Insurance Claim: Reconstructing AI-Mediated Losses Through the CER Framework

arXiv:2606.03777v1 Announce Type: new Abstract: AI losses that arise through an insured organization's generative or agentic AI system require state reconstruction, not merely event reconstruction, be

From Script to Semantics: Prompting Strategies for African NLI

model-releasesarxiv-cs-cl

arXiv:2606.03304v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly evaluated in multilingual settings, yet their inference behavior in low-resource African languages remains

GN0: Toward a Unified Paradigm for Generation, Evaluation, and Policy Learning in Visual-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2606.03682v1 Announce Type: new Abstract: Embodied navigation connects intelligent agents with the physical world and is fundamental for general robotic intelligence. Limited availability and qu

Tutorials

GS-ROR^2: Bidirectional-guided 3DGS and SDF for Reflective Object Relighting and Reconstruction

arXiv:2406.18544v4 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has shown a powerful capability for novel view synthesis due to its detailed expressive ability and highly efficient re

tutorialsarxiv-cs-cv

Honesty in Causal Forests: When It Helps and When It Hurts

arXiv:2506.13107v4 Announce Type: replace Abstract: Causal forests estimate how treatment effects vary across individuals, guiding personalized interventions in areas like marketing, operations, and p

HyperPatch: Sequential Knowledge Editing Under n-ary Structural Drift

model-releasesarxiv-cs-cl

arXiv:2606.03179v1 Announce Type: new Abstract: Large Language Models (LLMs) rely on Knowledge Editing (KE) to maintain temporal validity, yet real-world knowledge is inherently n-ary. We demonstrate

Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition

arXiv:2511.21731v2 Announce Type: replace-cross Abstract: We present the results of cognitive tests on conceptual combinations, performed using specific Large Language Models (LLMs) as test subjects.

IdiomX A Multilingual Benchmark for Idiom Understanding, Retrieval, and Interpretation

arXiv:2606.02584v1 Announce Type: cross Abstract: Idiomatic expressions remain a persistent challenge for natural language processing because their meanings are often non-compositional, context-depend

Inverting the Generation Process of Denoising Diffusion Implicit Models: Empirical Evaluation and a Novel Method

arXiv:2606.03111v1 Announce Type: new Abstract: This paper studies the problem of inverting the DDIM image generation process to recover latent variables, particularly the initial noise map, from a ge

researcharxiv-cs-cv

LAP: An Agent-to-Instrument Protocol for Autonomous Science

arXiv:2606.03755v1 Announce Type: new Abstract: Autonomous science is moving from demonstration to infrastructure. Large language model agents now plan experiments, and self-driving laboratories execu

Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models

arXiv:2606.02914v1 Announce Type: new Abstract: Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remai

Libra: Efficient Resource Management for Agentic RL Post-Training

arXiv:2606.03077v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a standard post-training paradigm for large language models (LLMs), extending beyond preference alignment to co

Lingo_Research_Group at SemEval-2026 Task 9: Evaluating Prompt Variants for Polarization Detection

arXiv:2606.03334v1 Announce Type: new Abstract: Our submission presented in this paper is for SemEval-2026 Task 9: Multilingual Text Classification Challenge - Polarization Detection and it covers all

MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents

arXiv:2606.03203v1 Announce Type: new Abstract: Computer-use agents could automate repetitive screen-based clinical work, but their reliability in medical graphical user interfaces remains largely unv

MemTrain: Self-Supervised Context Memory Training

arXiv:2606.03197v1 Announce Type: new Abstract: Memory is an indispensable capability for long-horizon LLM agents, enabling them to preserve and utilize information accumulated across extended interac

agentsarxiv-cs-cl

Mixed-Modality Dual Face-Hair Retrieval

model-releasesarxiv-cs-cv

arXiv:2606.03470v1 Announce Type: new Abstract: We introduce Dual Face-Hair Retrieval (DFHR), a new mixed-modality dual-reference task in image retrieval where a query consists of a face image specify

Multi^2: Hierarchical Multi-Agent Decision-Making with LLM-Based Agents in Interactive Environments

arXiv:2606.03698v1 Announce Type: new Abstract: A central goal of large language model (LLM) research is to build agentic systems that can plan, act, and adapt through sustained interaction with dynam

MUSE: A Unified Agentic Harness for MLLMs

arXiv:2606.03005v1 Announce Type: cross Abstract: Despite rapid progress, multimodal large language models (MLLMs) still fail on tasks that humans solve effortlessly, such as navigating a grid maze fr

Outsmarting the Chameleon: Counterfactual Decoupling for Tactical OOD Shifts in Live Streaming Risk Assessment

arXiv:2606.02946v1 Announce Type: new Abstract: Live streaming has emerged as a primary medium for social interaction and digital commerce, yet it is increasingly plagued by sophisticated risks. A fun

Local Ai

ParaBlock: Communication-Computation Parallel Block Coordinate Federated Learning for Large Language Models

arXiv:2511.19959v2 Announce Type: replace Abstract: Federated learning (FL) has been extensively studied as a privacy-preserving training paradigm. Recently, federated block coordinate descent scheme

local-aiarxiv-cs-lg

Predicting Inference-Time Scaling Gains from Labeled Validation-Set Output Statistics

arXiv:2606.02981v1 Announce Type: new Abstract: Best-of-N inference scaling (drawing N candidate answers from a language model and returning the one a reward model ranks highest) improves accuracy by

Psi-Bench: Evaluating Persona-Sensitive Influencing in Persuasive Dialogues

arXiv:2606.02754v1 Announce Type: new Abstract: Personalization is a crucial capability of modern language agents. However, current research primarily positions personalized agents as passive responde

RogueMerge: Robust and Unified Attacks against LLM Model Merging

arXiv:2606.03344v1 Announce Type: cross Abstract: Model merging composes specialized capabilities into a single LLM by aggregating task vectors sourced from unverified public platforms, exposing a cri