Search: “reasoning”

SynthAgent: Adapting Web Agents with Synthetic Supervision

arXiv:2511.06101v3 Announce Type: replace-cross Abstract: Web agents struggle to adapt to new websites due to the scarcity of environment specific tasks and demonstrations. Recent works have explored

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The Devil is in the Details -- From OCR for Old Church Slavonic to Purely Visual Stemma Reconstruction

DGX agent

arXiv:2604.11724v1 Announce Type: new Abstract: The age of artificial intelligence has brought many new possibilities and pitfalls in many fields and tasks. The devil is in the details, and those come

agentsarxiv-cs-cv

14 Apr 2026

The Phantom of PCIe: Constraining Generative Artificial Intelligences for Practical Peripherals Trace Synthesizing

arXiv:2411.06376v3 Announce Type: replace-cross Abstract: Peripheral Component Interconnect Express (PCIe) is the de facto interconnect standard for high-speed peripherals and CPUs. The development of

The Rise and Fall of G in AGI

arXiv:2604.09911v1 Announce Type: cross Abstract: In the psychological literature the term `general intelligence' describes correlations between abilities and not simply the number of abilities. This

TraversalBench: Challenging Paths to Follow for Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2604.10999v1 Announce Type: new Abstract: Vision-language models (VLMs) perform strongly on many multimodal benchmarks. However, the ability to follow complex visual paths -- a task that human o

Triviality Corrected Endogenous Reward

arXiv:2604.11522v1 Announce Type: new Abstract: Reinforcement learning for open-ended text generation is constrained by the lack of verifiable rewards, necessitating reliance on judge models that requ

safetyarxiv-cs-cl

Uncertainty-Aware Web-Conditioned Scientific Fact-Checking

arXiv:2604.11036v1 Announce Type: cross Abstract: Scientific fact-checking is vital for assessing claims in specialized domains such as biomedicine and materials science, yet existing systems often ha

Utilizing and Calibrating Hindsight Process Rewards via Reinforcement with Mutual Information Self-Evaluation

arXiv:2604.11611v1 Announce Type: new Abstract: To overcome the sparse reward challenge in reinforcement learning (RL) for agents based on large language models (LLMs), we propose Mutual Information S

safetyarxiv-cs-cl

Verify Before You Fix: Agentic Execution Grounding for Trustworthy Cross-Language Code Analysis

arXiv:2604.10800v1 Announce Type: cross Abstract: Learned classifiers deployed in agentic pipelines face a fundamental reliability problem: predictions are probabilistic inferences, not verified concl

VeriTrans: Fine-Tuned LLM-Assisted NL-to-PL Translation via a Deterministic Neuro-Symbolic Pipeline

arXiv:2604.10341v1 Announce Type: new Abstract: extbf{VeriTrans} is a reliability-first ML system that compiles natural-language requirements into solver-ready logic with validator-gated reliability.

Vestibular reservoir computing

arXiv:2604.09943v1 Announce Type: new Abstract: Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However,

researcharxiv-cs-lg

Visual Late Chunking: An Empirical Study of Contextual Chunking for Efficient Visual Document Retrieval

arXiv:2604.10167v1 Announce Type: cross Abstract: Multi-vector models dominate Visual Document Retrieval (VDR) due to their fine-grained matching capabilities, but their high storage and computational

researcharxiv-cs-cl

VS-Bench: Evaluating VLMs for Strategic Abilities in Multi-Agent Environments

arXiv:2506.02387v3 Announce Type: replace Abstract: Recent advancements in Vision Language Models (VLMs) have expanded their capabilities to interactive agent tasks, yet existing benchmarks remain lim

What Do Vision-Language Models Encode for Personalized Image Aesthetics Assessment?

arXiv:2604.11374v1 Announce Type: cross Abstract: Personalized image aesthetics assessment (PIAA) is an important research problem with practical real-world applications. While methods based on vision

applicationsarxiv-cs-cl

Tutorials

What do your logits know? (The answer may surprise you!)

arXiv:2604.09885v1 Announce Type: new Abstract: Recent work has shown that probing model internals can reveal a wealth of information not apparent from the model generations. This poses the risk of un

tutorialsarxiv-cs-ai

What to Say and When to Say it: Live Fitness Coaching as a Testbed for Situated Interaction

model-releasesarxiv-cs-cv

arXiv:2407.08101v4 Announce Type: replace Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, wher

When simulations look right but causal effects go wrong: Large language models as behavioral simulators

arXiv:2604.02458v2 Announce Type: replace-cross Abstract: Behavioral simulation is increasingly used to anticipate responses to interventions. Large language models (LLMs) enable researchers to specif

When Valid Signals Fail: Regime Boundaries Between LLM Features and RL Trading Policies

arXiv:2604.10996v1 Announce Type: cross Abstract: Can large language models (LLMs) generate continuous numerical features that improve reinforcement learning (RL) trading agents? We build a modular pi

Why Do Large Language Models Generate Harmful Content?

arXiv:2604.11663v1 Announce Type: new Abstract: Large Language Models (LLMs) have been shown to generate harmful content. However, the underlying causes of such behavior remain under explored. We prop

Why Don't You Know? Evaluating the Impact of Uncertainty Sources on Uncertainty Quantification in LLMs

arXiv:2604.10495v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in real-world applications, reliable uncertainty quantification (UQ) becomes critical for safe

applicationsarxiv-cs-cl

Working Paper: Towards Schema-based Learning from a Category-Theoretic Perspective

arXiv:2604.10589v1 Announce Type: new Abstract: We introduce a hierarchical categorical framework for Schema-Based Learning (SBL) structured across four interconnected levels. At the schema level, a f

2D or 3D: Who Governs Salience in VLA Models? -- Tri-Stage Token Pruning Framework with Modality Salience Awareness

arXiv:2604.09244v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as the mainstream of embodied intelligence. Recent VLA models have expanded their input modalities fr

researcharxiv-cs-cv

A Benchmark of Dexterity for Anthropomorphic Robotic Hands

model-releasesarxiv-cs-ro

arXiv:2604.09294v1 Announce Type: new Abstract: Dexterity is a central yet ambiguously defined concept in the design and evaluation of anthropomorphic robotic hands. In practice, the term is often use

Act or Escalate? Evaluating Escalation Behavior in Automation with Language Models

arXiv:2604.08588v1 Announce Type: cross Abstract: Effective automation hinges on deciding when to act and when to escalate. We model this as a decision under uncertainty: an LLM forms a prediction, es

ActivityEditor: Learning to Synthesize Physically Valid Human Mobility

arXiv:2604.05529v2 Announce Type: replace Abstract: Human mobility modeling is indispensable for diverse urban applications. However, existing data-driven methods often suffer from data scarcity, limi

Adaptive Action Chunking at Inference-time for Vision-Language-Action Models

arXiv:2604.04161v2 Announce Type: replace Abstract: In Vision-Language-Action (VLA) models, action chunking (i.e., executing a sequence of actions without intermediate replanning) is a key technique t

applicationsarxiv-cs-ro

Advantage-Guided Diffusion for Model-Based Reinforcement Learning

arXiv:2604.09035v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) with autoregressive world models suffers from compounding errors, whereas diffusion world models mitigate this

Agentic Jackal: Live Execution and Semantic Value Grounding for Text-to-JQL

model-releasesarxiv-cs-cl

arXiv:2604.09470v1 Announce Type: new Abstract: Translating natural language into Jira Query Language (JQL) requires resolving ambiguous field references, instance-specific categorical values, and com

AI Driven Soccer Analysis Using Computer Vision

arXiv:2604.08722v1 Announce Type: cross Abstract: Sport analysis is crucial for team performance since it provides actionable data that can inform coaching decisions, improve player performance, and e

applicationsarxiv-cs-ai

All You Need for Object Detection: From Pixels, Points, and Prompts to Next-Gen Fusion and Multimodal LLMs/VLMs in Autonomous Vehicles

arXiv:2510.26641v4 Announce Type: replace Abstract: Autonomous Vehicles (AVs) are transforming the future of transportation through advances in intelligent perception, decision-making, and control sys

agentsarxiv-cs-cv

Automated Instruction Revision (AIR): A Structured Comparison of Task Adaptation Strategies for LLM

model-releasesarxiv-cs-cl

arXiv:2604.09418v1 Announce Type: new Abstract: This paper studies Automated Instruction Revision (AIR), a rule-induction-based method for adapting large language models (LLMs) to downstream tasks usi

Automated Standardization of Legacy Biomedical Metadata Using an Ontology-Constrained LLM Agent

arXiv:2604.08552v1 Announce Type: cross Abstract: Scientific metadata are often incomplete and noncompliant with community standards, limiting dataset findability, interoperability, and reuse. When re

ChipSeek: Optimizing Verilog Generation via EDA-Integrated Reinforcement Learning

arXiv:2507.04736v2 Announce Type: replace Abstract: Large Language Models have emerged as powerful tools for automating Register-Transfer Level (RTL) code generation, yet they face critical limitation

Constraining Sequential Model Editing with Editing Anchor Compression

arXiv:2503.00035v2 Announce Type: replace-cross Abstract: Large language models (LLMs) struggle with hallucinations due to false or outdated knowledge. Given the high resource demands of retraining th

Contribution of task-irrelevant stimuli to drift of neural representations

arXiv:2510.21588v2 Announce Type: replace-cross Abstract: Biological and artificial learners are inherently exposed to a stream of data and experience throughout their lifetimes and must constantly ad

agentsarxiv-cs-lg

Distributionally Robust Token Optimization in RLHF

arXiv:2604.08577v1 Announce Type: cross Abstract: Large Language Models (LLMs) tend to respond correctly to prompts that align to the data they were trained and fine-tuned on. Yet, small shifts in wor

Do Vision Language Models Need to Process Image Tokens?

arXiv:2604.09425v1 Announce Type: new Abstract: Vision Language Models (VLMs) have achieved remarkable success by integrating visual encoders with large language models (LLMs). While VLMs process dens

researcharxiv-cs-cv

Dynamic sparsity in tree-structured feed-forward layers at scale

arXiv:2604.08565v1 Announce Type: cross Abstract: At typical context lengths, the feed-forward MLP block accounts for a large share of a transformer's compute budget, motivating sparse alternatives to

EXAONE 4.5 Technical Report

model-releasesarxiv-cs-cl

arXiv:2604.08644v1 Announce Type: new Abstract: This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integr

Explorable Theorems: Making Written Theorems Explorable by Grounding Them in Formal Representations

arXiv:2604.02598v2 Announce Type: replace-cross Abstract: LLM-generated explanations can make technical content more accessible, but there is a ceiling on what they can support interactively. Because

Fast-dVLM: Efficient Block-Diffusion VLM via Direct Conversion from Autoregressive VLM

arXiv:2604.06832v2 Announce Type: replace Abstract: Vision-language models (VLMs) predominantly rely on autoregressive decoding, which generates tokens one at a time and fundamentally limits inference

agentsarxiv-cs-cl

Hardware

Fast Model-guided Instance-wise Adaptation Framework for Real-world Pansharpening with Fidelity Constraints

arXiv:2604.08903v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) and high-resolution panchromati

hardwarearxiv-cs-cv

Frequency-Enhanced Diffusion Models: Curriculum-Guided Semantic Alignment for Zero-Shot Skeleton Action Recognition

arXiv:2604.09063v1 Announce Type: cross Abstract: Human action recognition is pivotal in computer vision, with applications ranging from surveillance to human-robot interaction. Despite the effectiven

From Paper to Program: Accelerating Quantum Many-Body Algorithm Development via a Multi-Stage LLM-Assisted Workflow

arXiv:2604.04089v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate code rapidly but remain unreliable for scientific algorithms whose correctness depends on structural

Gen-n-Val: Agentic Image Data Generation and Validation

arXiv:2506.04676v2 Announce Type: replace-cross Abstract: The data scarcity, label noise, and long-tailed category imbalance remain important and unresolved challenges in many computer vision tasks, s

GeoMMBench and GeoMMAgent: Toward Expert-Level Multimodal Intelligence in Geoscience and Remote Sensing

model-releasesarxiv-cs-cv

arXiv:2604.08896v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have accelerated progress in domain-oriented AI, yet their development in geoscience and rem

GNN-as-Judge: Unleashing the Power of LLMs for Graph Learning with GNN Feedback

arXiv:2604.08553v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong performance on text-attributed graphs (TAGs) due to their superior semantic understanding ability on te

Harnessing Weak Pair Uncertainty for Text-based Person Search

arXiv:2604.08877v1 Announce Type: new Abstract: In this paper, we study the text-based person search, which is to retrieve the person of interest via natural language description. Prevailing methods u

researcharxiv-cs-cv