Search: “reasoning”

Transferable Physics-Informed Representations via Closed-Form Head Adaptation

arXiv:2604.21761v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have garnered significant interest for their potential in solving partial differential equations (PDEs) that go

tutorialsarxiv-cs-lg

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Tumor-anchored deep feature random forests for out-of-distribution detection in lung cancer segmentation

DGX agent

arXiv:2512.08216v3 Announce Type: replace-cross Abstract: Accurate segmentation of lung tumors from 3D computed tomography (CT) scans is essential for automated treatment planning and response assessm

safetyarxiv-cs-cv

24 Apr 2026

UbiQVision: Quantifying Uncertainty in XAI for Image Recognition

arXiv:2512.20288v2 Announce Type: replace-cross Abstract: Recent advances in deep learning have led to its widespread adoption across diverse domains, including medical imaging. This progress is drive

Unbiased Prevalence Estimation with Multicalibrated LLMs

arXiv:2604.21549v1 Announce Type: new Abstract: Estimating the prevalence of a category in a population using imperfect measurement devices (diagnostic tests, classifiers, or large language models) is

Local Ai

Unlocking the Power of Critical Factors for 3D Visual Geometry Estimation

arXiv:2604.21713v1 Announce Type: new Abstract: Feed-forward visual geometry estimation has recently made rapid progress. However, an important gap remains: multi-frame models usually produce better c

local-aiarxiv-cs-cv

VFM^{4}SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection

arXiv:2604.21502v1 Announce Type: new Abstract: In real-world scenarios, continual changes in weather, illumination, and imaging conditions cause significant domain shifts, leading detectors trained o

safetyarxiv-cs-cv

When Agents Look the Same: Quantifying Distillation-Induced Similarity in Tool-Use Behaviors

model-releasesarxiv-cs-cl

arXiv:2604.21255v1 Announce Type: new Abstract: Model distillation is a primary driver behind the rapid progress of LLM agents, yet it often leads to behavioral homogenization. Many emerging agents sh

Why Do Language Model Agents Whistleblow?

arXiv:2511.17085v3 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds

Anchor-and-Resume Concession Under Dynamic Pricing for LLM-Augmented Freight Negotiation

arXiv:2604.20732v1 Announce Type: cross Abstract: Freight brokerages negotiate thousands of carrier rates daily under dynamic pricing conditions where models frequently revise targets mid-conversation

Camera Control for Text-to-Image Generation via Learning Viewpoint Tokens

arXiv:2604.19954v1 Announce Type: new Abstract: Current text-to-image models struggle to provide precise camera control using natural language alone. In this work, we present a framework for precise c

tutorialsarxiv-cs-cv

Can 'AI' Be a Doctor? A Study of Empathy, Readability, and Alignment in Clinical LLMs

arXiv:2604.20791v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed in healthcare, yet their communicative alignment with clinical standards remains insufficiently

Can LLMs Infer Conversational Agent Users' Personality Traits from Chat History?

arXiv:2604.19785v1 Announce Type: cross Abstract: Sensitive information, such as knowledge about an individual's personality, can be can be misused to influence behavior (e.g., via personalized messag

ChipCraftBrain: Validation-First RTL Generation via Multi-Agent Orchestration

arXiv:2604.19856v1 Announce Type: cross Abstract: Large Language Models (LLMs) show promise for generating Register-Transfer Level (RTL) code from natural language specifications, but single-shot gene

Applications

Closing the Domain Gap in Biomedical Imaging by In-Context Control Samples

arXiv:2604.20824v1 Announce Type: new Abstract: The central problem in biomedical imaging are batch effects: systematic technical variations unrelated to the biological signal of interest. These batch

applicationsarxiv-cs-lg

Commonsense Knowledge with Negation: A Resource to Enhance Negation Understanding

arXiv:2604.19921v1 Announce Type: new Abstract: Negation is a common and important semantic feature in natural language, yet Large Language Models (LLMs) struggle when negation is involved in natural

researcharxiv-cs-cl

Context Attribution with Multi-Armed Bandit Optimization

arXiv:2506.19977v2 Announce Type: replace Abstract: Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable a

Coverage, Not Averages: Semantic Stratification for Trustworthy Retrieval Evaluation

arXiv:2604.20763v1 Announce Type: cross Abstract: Retrieval quality is the primary bottleneck for accuracy and robustness in retrieval-augmented generation (RAG). Current evaluation relies on heuristi

CreativeGame:Toward Mechanic-Aware Creative Game Generation

arXiv:2604.19926v1 Announce Type: new Abstract: Large language models can generate plausible game code, but turning this capability into iterative creative improvement remains difficult. In practice,

CyberCertBench: Evaluating LLMs in Cybersecurity Certification Knowledge

arXiv:2604.20389v1 Announce Type: cross Abstract: The rapid evolution and use of Large Language Models (LLMs) in professional workflows require an evaluation of their domain-specific knowledge against

DeVI: Physics-based Dexterous Human-Object Interaction via Synthetic Video Imitation

arXiv:2604.20841v1 Announce Type: new Abstract: Recent advances in video generative models enable the synthesis of realistic human-object interaction videos across a wide range of scenarios and object

agentsarxiv-cs-cv

Applications

Do Hallucination Neurons Generalize? Evidence from Cross-Domain Transfer in LLMs

arXiv:2604.19765v1 Announce Type: cross Abstract: Recent work identifies a sparse set of 'hallucination neurons' (H-neurons), less than 0.1% of feed-forward network neurons, that reliably predict when

applicationsarxiv-cs-ai

DR-Venus: Towards Frontier Edge-Scale Deep Research Agents with Only 10K Open Data

arXiv:2604.19859v1 Announce Type: cross Abstract: Edge-scale deep research agents based on small language models are attractive for real-world deployment due to their advantages in cost, latency, and

Evaluating Assurance Cases as Text-Attributed Graphs for Structure and Provenance Analysis

arXiv:2604.20577v1 Announce Type: cross Abstract: An assurance case is a structured argument document that justifies claims about a system's requirements or properties, which are supported by evidence

safetyarxiv-cs-lg

Applications

Explainability in Generative Medical Diffusion Models: A Faithfulness-Based Analysis on MRI Synthesis

arXiv:2602.09781v2 Announce Type: replace-cross Abstract: This study investigates the explainability of generative diffusion models in the context of medical imaging, focusing on Magnetic resonance im

applicationsarxiv-cs-ai

Exploring Data Augmentation and Resampling Strategies for Transformer-Based Models to Address Class Imbalance in AI Scoring of Scientific Explanations in NGSS Classroom

arXiv:2604.19754v1 Announce Type: new Abstract: Automated scoring of students' scientific explanations offers the potential for immediate, accurate feedback, yet class imbalance in rubric categories p

Exploring High-Order Self-Similarity for Video Understanding

arXiv:2604.20760v1 Announce Type: new Abstract: Space-time self-similarity (STSS), which captures visual correspondences across frames, provides an effective way to represent temporal dynamics for vid

tutorialsarxiv-cs-cv

Fast-then-Fine: A Two-Stage Framework with Multi-Granular Representation for Cross-Modal Retrieval in Remote Sensing

model-releasesarxiv-cs-cv

arXiv:2604.20429v1 Announce Type: new Abstract: Remote sensing (RS) image-text retrieval plays a critical role in understanding massive RS imagery. However, the dense multi-object distribution and com

FELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Data

arXiv:2510.25223v3 Announce Type: replace Abstract: Event log data, recording fine-grained user actions and system events, represent one of the most valuable assets for modern digital services. Howeve

Forage V2: Knowledge Evolution and Transfer in Autonomous Agent Organizations

arXiv:2604.19837v1 Announce Type: new Abstract: Autonomous agents operating in open-world tasks -- where the completion boundary is not given in advance -- face denominator blindness: they systematica

Formal Verification of Minimax Algorithms

arXiv:2509.20138v2 Announce Type: replace Abstract: Minimax-based search algorithms with alpha-beta pruning and transposition tables are a central component of classical game-playing engines and remai

From Data to Theory: Autonomous Large Language Model Agents for Materials Science

arXiv:2604.19789v1 Announce Type: new Abstract: We present an autonomous large language model (LLM) agent for end-to-end, data-driven materials theory development. The model can choose an equation for

From Fuzzy to Formal: Scaling Hospital Quality Improvement with AI

arXiv:2604.20055v1 Announce Type: new Abstract: Hospital Quality Improvement (QI) plays a critical role in optimizing healthcare delivery by translating high-level hospital goals into actionable solut

From Ideal to Real: Stable Video Object Removal under Imperfect Conditions

arXiv:2603.09283v2 Announce Type: replace Abstract: Removing objects from videos remains difficult in the presence of real-world imperfections such as shadows, abrupt motion, and defective masks. Exis

tutorialsarxiv-cs-cv

From Recall to Forgetting: Benchmarking Long-Term Memory for Personalized Agents

model-releasesarxiv-cs-cl

arXiv:2604.20006v1 Announce Type: new Abstract: Personalized agents that interact with users over long periods must maintain persistent memory across sessions and update it as circumstances change. Ho

From Scene to Object: Text-Guided Dual-Gaze Prediction

arXiv:2604.20191v1 Announce Type: cross Abstract: Interpretable driver attention prediction is crucial for human-like autonomous driving. However, existing datasets provide only scene-level global gaz

Graph2Counsel: Clinically Grounded Synthetic Counseling Dialogue Generation from Client Psychological Graphs

arXiv:2604.20382v1 Announce Type: new Abstract: Rising demand for mental health support has increased interest in using Large Language Models (LLMs) for counseling. However, adapting LLMs to this high

safetyarxiv-cs-cl

Handbook of Rough Set Extensions and Uncertainty Models

arXiv:2604.19794v1 Announce Type: new Abstract: Rough set theory models uncertainty by approximating target concepts through lower and upper sets induced by indiscernibility, or more generally, by gra

i-WiViG: Interpretable Window Vision GNN

arXiv:2503.08321v2 Announce Type: replace Abstract: Vision graph neural networks have emerged as a popular approach for modeling the global and spatial context for image recognition. However, a signif

safetyarxiv-cs-cv

If you're waiting for a sign... that might not be it! Mitigating Trust Boundary Confusion from Visual Injections on Vision-Language Agentic Systems

arXiv:2604.19844v1 Announce Type: cross Abstract: Recent advances in embodied Vision-Language Agentic Systems (VLAS), powered by large vision-language models (LVLMs), enable AI systems to perceive and

IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory

arXiv:2604.20136v1 Announce Type: cross Abstract: Correcting errors in long-video understanding is disproportionately costly: existing multimodal pipelines produce opaque, end-to-end outputs that expo

KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devices

arXiv:2604.19834v1 Announce Type: new Abstract: Functional fitness movements are widely used in training, competition, and health-oriented exercise programs, yet consistently enforcing repetition (rep

researcharxiv-cs-cv

Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generation

model-releasesarxiv-cs-cl

arXiv:2502.12911v3 Announce Type: replace Abstract: Generating SQLs from user queries is a long-standing challenge, where the accuracy of initial schema linking significantly impacts subsequent SQL ge

Language-Coupled Reinforcement Learning for Multilingual Retrieval-Augmented Generation

arXiv:2601.14896v2 Announce Type: replace Abstract: Multilingual retrieval-augmented generation (MRAG) requires models to effectively acquire and integrate beneficial external knowledge from multiling

safetyarxiv-cs-cl

Large Language Models Meet Biomedical Knowledge Graphs for Mechanistically Grounded Therapeutic Prioritization

arXiv:2604.19815v1 Announce Type: new Abstract: Drug repurposing is often framed as a candidate identification task, but existing approaches provide limited guidance for distinguishing biologically pl

Local Ai

Learning Spatial-Temporal Coherent Correlations for Speech-Preserving Facial Expression Manipulation

arXiv:2604.20226v1 Announce Type: new Abstract: Speech-preserving facial expression manipulation (SPFEM) aims to modify facial emotions while meticulously maintaining the mouth animation associated wi

local-aiarxiv-cs-cv

LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model

arXiv:2604.20796v1 Announce Type: new Abstract: We present LLaDA2.0-Uni, a unified discrete diffusion large language model (dLLM) that supports multimodal understanding and generation within a nativel

researcharxiv-cs-cv

LLM Agents Predict Social Media Reactions but Do Not Outperform Text Classifiers: Benchmarking Simulation Accuracy Using 120K+ Personas of 1511 Humans

arXiv:2604.19787v1 Announce Type: cross Abstract: Social media platforms mediate how billions form opinions and engage with public discourse. As autonomous AI agents increasingly participate in these

Location-Aware Pretraining for Medical Difference Visual Question Answering

arXiv:2603.04950v2 Announce Type: replace-cross Abstract: Differential medical VQA models compare multiple images to identify clinically meaningful changes and rely on vision encoders to capture fine-