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Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
본 페이지는 Google Gemini를 활용해 요약 정리하며, 비영리로 운영 됩니다.
논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos

Compositional Discrete Latent Code for High Fidelity, Productive Diffusion Models

MERA Code: A Unified Framework for Evaluating Code Generation Across Tasks

Site-Level Fine-Tuning with Progressive Layer Freezing: Towards Robust Prediction of Bronchopulmonary Dysplasia from Day-1 Chest Radiographs in Extremely Preterm Infants

A Roadmap for Climate-Relevant Robotics Research

Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening

MMOne: Representing Multiple Modalities in One Scene

SWE-MERA: A Dynamic Benchmark for Agenticly Evaluating Large Language Models on Software Engineering Tasks

CodeAssistBench (CAB): Dataset & Benchmarking for Multi-turn Chat-Based Code Assistance

(Almost) Free Modality Stitching of Foundation Models

A Brain Tumor Segmentation Method Based on CLIP and 3D U-Net with Cross-Modal Semantic Guidance and Multi-Level Feature Fusion

KEN: Knowledge Augmentation and Emotion Guidance Network for Multimodal Fake News Detection

THOR: Transformer Heuristics for On-Demand Retrieval

SEALGuard: Safeguarding the Multilingual Conversations in Southeast Asian Languages for LLM Software Systems

KeyRe-ID: Keypoint-Guided Person Re-Identification using Part-Aware Representation in Videos

Prompt Perturbations Reveal Human-Like Biases in LLM Survey Responses

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Fast Bilateral Teleoperation and Imitation Learning Using Sensorless Force Control via Accurate Dynamics Model

Task-Specific Generative Dataset Distillation with Difficulty-Guided Sampling

VIDEE: Visual and Interactive Decomposition, Execution, and Evaluation of Text Analytics with Intelligent Agents

ReCode: Updating Code API Knowledge with Reinforcement Learning

Cross-Layer Discrete Concept Discovery for Interpreting Language Models

Semantic Structure-Aware Generative Attacks for Enhanced Adversarial Transferability

MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents

Multiple-Frequencies Population-Based Training

Critique-GRPO: Advancing LLM Reasoning with Natural Language and Numerical Feedback

Fine-Tune an SLM or Prompt an LLM? The Case of Generating Low-Code Workflows

ContextQFormer: A New Context Modeling Method for Multi-Turn Multi-Modal Conversations

GPU Performance Portability needs Autotuning

Generating Synthetic Data via Augmentations for Improved Facial Resemblance in DreamBooth and InstantID

Coral Protocol: Open Infrastructure Connecting The Internet of Agents

MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness

Federated Learning: A Survey on Privacy-Preserving Collaborative Intelligence

ConTextual: Improving Clinical Text Summarization in LLMs with Context-preserving Token Filtering and Knowledge Graphs

Task-Circuit Quantization: Leveraging Knowledge Localization and Interpretability for Compression

JailDAM: Jailbreak Detection with Adaptive Memory for Vision-Language Model

K-P Quantum Neural Networks

VectorFit : Adaptive Singular & Bias Vector Fine-Tuning of Pre-trained Foundation Models

Data-Efficient Deep Operator Network for Unsteady Flow: A Multi-Fidelity Approach with Physics-Guided Subsampling

Learning Universal Human Mobility Patterns with a Foundation Model for Cross-domain Data Fusion

GeoFlow-SLAM: A Robust Tightly-Coupled RGBD-Inertial and Legged Odometry Fusion SLAM for Dynamic Legged Robotics

A Multi-Stage Framework with Taxonomy-Guided Reasoning for Occupation Classification Using Large Language Models

Multi-View Node Pruning for Accurate Graph Representation

V-Max: A Reinforcement Learning Framework for Autonomous Driving

Interpretable Transformation and Analysis of Timelines through Learning via Surprisability

AI Governance InternationaL Evaluation Index (AGILE Index) 2024

UPCORE: Utility-Preserving Coreset Selection for Balanced Unlearning

Improving Transformer World Models for Data-Efficient RL

LLM-RecG: A Semantic Bias-Aware Framework for Zero-Shot Sequential Recommendation

SIDDA: SInkhorn Dynamic Domain Adaptation for Image Classification with Equivariant Neural Networks

Determination of galaxy photometric redshifts using Conditional Generative Adversarial Networks (CGANs)

Speech-Forensics: Towards Comprehensive Synthetic Speech Dataset Establishment and Analysis

MRGen: Segmentation Data Engine for Underrepresented MRI Modalities

IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization

Out-of-Distribution Recovery with Object-Centric Keypoint Inverse Policy for Visuomotor Imitation Learning

Dataset resulting from the user study on comprehensibility of explainable AI algorithms

Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models

LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization

Identifying Task Groupings for Multi-Task Learning Using Pointwise V-Usable Information

DeFine: Decision-Making with Analogical Reasoning over Factor Profiles

Benchmarking Sub-Genre Classification For Mainstage Dance Music

Risks of ignoring uncertainty propagation in AI-augmented security pipelines

MedPix 2.0: A Comprehensive Multimodal Biomedical Data set for Advanced AI Applications with Retrieval Augmented Generation and Knowledge Graphs

Leveraging Quantum Superposition to Infer the Dynamic Behavior of a Spatial-Temporal Neural Network Signaling Model

Bounding the Worst-class Error: A Boosting Approach

TBDetector:Transformer-Based Detector for Advanced Persistent Threats with Provenance Graph

Machine Learning Systems: A Survey from a Data-Oriented Perspective

Aime: Towards Fully-Autonomous Multi-Agent Framework

SmartThinker: Learning to Compress and Preserve Reasoning by Step-Level Length Control

Ready Jurist One: Benchmarking Language Agents for Legal Intelligence in Dynamic Environments

NTRL: Encounter Generation via Reinforcement Learning for Dynamic Difficulty Adjustment in Dungeons and Dragons

Judging with Many Minds: Do More Perspectives Mean Less Prejudice? On Bias Amplifications and Resistance in Multi-Agent Based LLM-as-Judge

ActionStudio: A Lightweight Framework for Data and Training of Large Action Models

BEARCUBS: A benchmark for computer-using web agents

Demystifying MuZero Planning: Interpreting the Learned Model

LLM-Enhanced User-Item Interactions: Leveraging Edge Information for Optimized Recommendations

VideoITG: Multimodal Video Understanding with Instructed Temporal Grounding

VisionThink: Smart and Efficient Vision Language Model via Reinforcement Learning

Imbalance in Balance: Online Concept Balancing in Generation Models

Latent Policy Steering with Embodiment-Agnostic Pretrained World Models

Vision-and-Language Training Helps Deploy Taxonomic Knowledge but Does Not Fundamentally Alter It

Revisiting Reliability in the Reasoning-based Pose Estimation Benchmark

AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research

Towards Formal Verification of LLM-Generated Code from Natural Language Prompts

Evaluating Reinforcement Learning Algorithms for Navigation in Simulated Robotic Quadrupeds: A Comparative Study Inspired by Guide Dog Behaviour

Overview of the TalentCLEF 2025: Skill and Job Title Intelligence for Human Capital Management

QuestA: Expanding Reasoning Capacity in LLMs via Question Augmentation

Merge Kernel for Bayesian Optimization on Permutation Space

Efficient Adaptation of Pre-trained Vision Transformer underpinned by Approximately Orthogonal Fine-Tuning Strategy

Automating Steering for Safe Multimodal Large Language Models

HATS: Hindi Analogy Test Set for Evaluating Reasoning in Large Language Models

VITA: Vision-to-Action Flow Matching Policy

$S^2M^2$: Scalable Stereo Matching Model for Reliable Depth Estimation

Synthesizing Reality: Leveraging the Generative AI-Powered Platform Midjourney for Construction Worker Detection

Aligning Humans and Robots via Reinforcement Learning from Implicit Human Feedback

SHIELD: A Secure and Highly Enhanced Integrated Learning for Robust Deepfake Detection against Adversarial Attacks

Prompt Injection 2.0: Hybrid AI Threats

Orbis: Overcoming Challenges of Long-Horizon Prediction in Driving World Models

Inverse Reinforcement Learning Meets Large Language Model Post-Training: Basics, Advances, and Opportunities

HA-VLN: A Benchmark for Human-Aware Navigation in Discrete-Continuous Environments with Dynamic Multi-Human Interactions, Real-World Validation, and an Open Leaderboard

Created by

Haebom

저자

Yifei Dong, Fengyi Wu, Qi He, Heng Li, Minghan Li, Zebang Cheng, Yuxuan Zhou, Jingdong Sun, Qi Dai, Zhi-Qi Cheng, Alexander G Hauptmann

개요

본 논문은 기존의 Vision-and-Language Navigation (VLN) 시스템이 이산적(파노라마) 또는 연속적(자유 이동) 패러다임 중 하나에만 초점을 맞추는 한계를 극복하고, 사람이 많고 역동적인 환경의 복잡성을 고려한 통합적인 Human-Aware VLN (HA-VLN) 벤치마크를 제시합니다. 이를 위해 개인 공간 요구 사항을 고려한 이산-연속 탐색을 균형 있게 처리하는 표준화된 작업 정의, 현실적인 다중 인간 상호 작용, 실외 환경, 그리고 개선된 동작-언어 정렬을 포착하는 향상된 인간 동작 데이터셋(HAPS 2.0) 및 업그레이드된 시뮬레이터, 16,844개의 인간 중심 지시에 대한 광범위한 벤치마킹, 혼잡한 실내 공간에서의 실제 로봇 테스트, 그리고 이산 및 연속 작업에 대한 투명한 비교를 지원하는 공개 리더보드를 제공합니다. 실험 결과는 사회적 맥락이 통합될 때 탐색 성공률이 향상되고 충돌이 감소함을 보여주며, 인간 중심 설계의 필요성을 강조합니다. 모든 데이터셋, 시뮬레이터, 에이전트 코드 및 평가 도구를 공개하여 더 안전하고, 능력 있고, 사회적으로 책임감 있는 VLN 연구를 발전시키는 것을 목표로 합니다.

시사점, 한계점

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시사점:

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사람이 많고 역동적인 환경에서의 VLN 시스템 개발을 위한 새로운 벤치마크(HA-VLN) 제시.

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이산적 및 연속적 탐색 패러다임을 통합하여 더욱 현실적인 VLN 연구 가능.

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사회적 맥락을 고려한 VLN 에이전트 개발의 중요성 강조.

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개선된 데이터셋(HAPS 2.0)과 시뮬레이터 제공을 통한 연구의 재현성 및 발전 가능성 증대.

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실제 로봇 테스트를 통한 시뮬레이션-실제 전이 성능 검증.

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공개 리더보드를 통한 투명한 비교 및 연구 발전 촉진.

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한계점:

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HAPS 2.0 데이터셋의 수집 과정 및 범위에 대한 구체적인 설명 부족.

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다양한 환경(예: 옥외 환경)에서의 일반화 성능에 대한 추가적인 검증 필요.

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극도로 복잡하거나 예측 불가능한 상황에 대한 에이전트의 대응 능력 평가 부족.

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사회적 상호작용의 다양성을 완벽히 반영하지 못할 가능성.

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