Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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논문에 대한 저작권은 저자 및 해당 기관에 있으며, 공유 시 출처만 명기하면 됩니다.

When Generative AI Meets Extended Reality: Enabling Scalable and Natural Interactions

An Explainable Market Integrity Monitoring System with Multi-Source Attention Signals and Transparent Scoring

Can We Trust LLM Detectors?

Embedding Retrofitting: Data Engineering for better RAG

Entropy-Tree: Tree-Based Decoding with Entropy-Guided Exploration

Elsewise: Authoring AI-Based Interactive Narrative with Possibility Space Visualization

Agentic Persona Control and Task State Tracking for Realistic User Simulation in Interactive Scenarios

LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback

Psychometric Comparability of LLM-Based Digital Twins

Scalable Board Expansion within a General Game System

Structured Hints for Sample-Efficient Lean Theorem Proving

Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

LLM Prompt Evaluation for Educational Applications

Multimodal Climate Disinformation Detection: Integrating Vision-Language Models with External Knowledge Sources

Controlling Long-Horizon Behavior in Language Model Agents with Explicit State Dynamics

Designing faster mixed integer linear programming algorithm via learning the optimal path

AgriPINN: A Process-Informed Neural Network for Interpretable and Scalable Crop Biomass Prediction Under Water Stress

Grounding Large Language Models in Reaction Knowledge Graphs for Synthesis Retrieval

Deja Vu in Plots: Leveraging Cross-Session Evidence with Retrieval-Augmented LLMs for Live Streaming Risk Assessment

Decoupling Return-to-Go for Efficient Decision Transformer

Natural Language-Driven Global Mapping of Martian Landforms

ICON: Invariant Counterfactual Optimization with Neuro-Symbolic Priors for Text-Based Person Search

EvoCUA: Evolving Computer Use Agents via Learning from Scalable Synthetic Experience

ErrorMap and ErrorAtlas: Charting the Failure Landscape of Large Language Models

Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification

VitalDiagnosis: AI-Driven Ecosystem for 24/7 Vital Monitoring and Chronic Disease Management

Creativity in the Age of AI: Rethinking the Role of Intentional Agency

Agentic Confidence Calibration

Off-Policy Actor-Critic with Sigmoid-Bounded Entropy for Real-World Robot Learning

Tabular Incremental Inference

PhysProver: Advancing Automatic Theorem Proving for Physics

Benchmarking Text-to-Python against Text-to-SQL: The Impact of Explicit Logic and Ambiguity

Investigation of the Generalisation Ability of Genetic Programming-evolved Scheduling Rules in Dynamic Flexible Job Shop Scheduling

AgentSM: Semantic Memory for Agentic Text-to-SQL

Improving Methodologies for LLM Evaluations Across Global Languages

Agentic Uncertainty Quantification

From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models

Improving Methodologies for Agentic Evaluations Across Domains: Leakage of Sensitive Information, Fraud and Cybersecurity Threats

Predictive Coding and Information Bottleneck for Hallucination Detection in Large Language Models

Agentic AI Governance and Lifecycle Management in Healthcare

CogToM: A Comprehensive Theory of Mind Benchmark inspired by Human Cognition for Large Language Models

Autonomous Business System via Neuro-symbolic AI

ALIGNAgent: Adaptive Learner Intelligence for Gap Identification and Next-step guidance

From Generative Engines to Actionable Simulators: The Imperative of Physical Grounding in World Models

TransportAgents: a multi-agents LLM framework for traffic accident severity prediction

The Dark Side of AI Transformers: Sentiment Polarization & the Loss of Business Neutrality by NLP Transformers

Tracking the Limits of Knowledge Propagation: How LLMs Fail at Multi-Step Reasoning with Conflicting Knowledge

MiRAGE: A Multiagent Framework for Generating Multimodal Multihop Question-Answer Dataset for RAG Evaluation

Reliability by design: quantifying and eliminating fabrication risk in LLMs. From generative to consultative AI: a comparative analysis in the legal domain and lessons for high-stakes knowledge bases

A tensor network formalism for neuro-symbolic AI

Not Your Typical Sycophant: The Elusive Nature of Sycophancy in Large Language Models

Beyond Prompting: Efficient and Robust Contextual Biasing for Speech LLMs via Logit-Space Integration (LOGIC)

GeMM-GAN: A Multimodal Generative Model Conditioned on Histopathology Images and Clinical Descriptions for Gene Expression Profile Generation

Logic Programming on Knowledge Graph Networks And its Application in Medical Domain

Prometheus Mind: Retrofitting Memory to Frozen Language Models

Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents

The Paradigm Shift: A Comprehensive Survey on Large Vision Language Models for Multimodal Fake News Detection

Aeon: High-Performance Neuro-Symbolic Memory Management for Long-Horizon LLM Agents

DeepSurvey-Bench: Evaluating Academic Value of Automatically Generated Scientific Survey

Uncovering Latent Bias in LLM-Based Emergency Department Triage Through Proxy Variables

Gated Sparse Attention: Combining Computational Efficiency with Training Stability for Long-Context Language Models

AI/ML in 3GPP 5G Advanced -- Services and Architecture

CookAnything: A Framework for Flexible and Consistent Multi-Step Recipe Image Generation

Dynamic Correction of Erroneous State Estimates via Diffusion Bayesian Exploration

Concept-Guided Backdoor Attack on Vision Language Models

On the Holographic Geometry of Deterministic Computation

Decoding inner speech with an end-to-end brain-to-text neural interface

Physics-informed Neural Operator Learning for Nonlinear Grad-Shafranov Equation

MindEval: Benchmarking Language Models on Multi-turn Mental Health Support

LAET: A Layer-wise Adaptive Ensemble Tuning Framework for Pretrained Language Models

FAST-CAD: A Fairness-Aware Framework for Non-Contact Stroke Diagnosis

Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationale

SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control

MOSS: Efficient and Accurate FP8 LLM Training with Microscaling and Automatic Scaling

Data-Augmented Deep Learning for Downhole Depth Sensing and Field Validation

Chinese Discharge Drug Recommendation in Metabolic Diseases with Large Language Models

Analysing Moral Bias in Finetuned LLMs through Mechanistic Interpretability

Orders in Chaos: Enhancing Large-Scale MoE LLM Serving with Data Movement Forecasting

Reinforce-Ada: An Adaptive Sampling Framework under Non-linear RL Objectives

TempoControl: Temporal Attention Guidance for Text-to-Video Models

AortaDiff: A Unified Multitask Diffusion Framework For Contrast-Free AAA Imaging

SoREX: Towards Self-Explainable Social Recommendation with Relevant Ego-Path Extraction

The AI Productivity Index (APEX)

Uncovering Grounding IDs: How External Cues Shape Multimodal Binding

Pushing Toward the Simplex Vertices: A Simple Remedy for Code Collapse in Smoothed Vector Quantization

V-CECE: Visual Counterfactual Explanations via Conceptual Edits

Momentum-constrained Hybrid Heuristic Trajectory Optimization Framework with Residual-enhanced DRL for Visually Impaired Scenarios

HARP: Hallucination Detection via Reasoning Subspace Projection

Rethinking Sparse Autoencoders: Select-and-Project for Fairness and Control from Encoder Features Alone

IPA: An Information-Reconstructive Input Projection Framework for Efficient Foundation Model Adaptation

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders

ORFuzz: Fuzzing the "Other Side" of LLM Safety -- Testing Over-Refusal

Retro-Expert: Collaborative Reasoning for Interpretable Retrosynthesis

A Survey on Diffusion Language Models

CodeNER: Code Prompting for Named Entity Recognition

ReSem3D: Refinable 3D Spatial Constraints via Fine-Grained Semantic Grounding for Generalizable Robotic Manipulation

VERIRAG: A Post-Retrieval Auditing of Scientific Study Summaries

SustainDiffusion: Optimising the Social and Environmental Sustainability of Stable Diffusion Models

LittleBit: Ultra Low-Bit Quantization via Latent Factorization

Real-Time Execution of Action Chunking Flow Policies

In-House Evaluation Is Not Enough: Towards Robust Third-Party Flaw Disclosure for General-Purpose AI

Created by

Haebom

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저자

Shayne Longpre, Kevin Klyman, Ruth E. Appel, Sayash Kapoor, Rishi Bommasani, Michelle Sahar, Sean McGregor, Avijit Ghosh, Borhane Blili-Hamelin, Nathan Butters, Alondra Nelson, Amit Elazari, Andrew Sellars, Casey John Ellis, Dane Sherrets, Dawn Song, Harley Geiger, Ilona Cohen, Lauren McIlvenny, Madhulika Srikumar, Mark M. Jaycox, Markus Anderljung, Nadine Farid Johnson, Nicholas Carlini, Nicolas Miailhe, Nik Marda, Peter Henderson, Rebecca S. Portnoff, Rebecca Weiss, Victoria Westerhoff, Yacine Jernite, Rumman Chowdhury, Percy Liang, Arvind Narayanan

개요

본 논문은 범용 인공지능(GPAI) 시스템의 광범위한 배포로 인해 발생하는 새로운 위험을 다룬다. 소프트웨어 보안과 같은 기존 분야와 비교하여 GPAI 시스템의 결함 보고를 위한 인프라, 관행 및 규범이 매우 미흡하다는 점을 지적한다. 소프트웨어 보안, 기계 학습, 법률, 사회과학 및 정책 분야 전문가들과의 협업을 바탕으로 GPAI 시스템 결함 평가 및 보고의 주요한 허점을 확인하고, 시스템 안전 향상을 위한 세 가지 개입 방안을 제시한다. 첫째, 표준화된 AI 결함 보고서와 연구자들을 위한 참여 규칙을 제안하여 GPAI 시스템의 결함 제출, 재현 및 분류 과정을 용이하게 한다. 둘째, 버그 바운티를 활용한 광범위한 결함 공개 프로그램을 GPAI 시스템 제공업체가 채택하고, 연구자를 보호하기 위한 법적 안전 장치를 마련할 것을 제안한다. 셋째, 많은 이해관계자에게 결함 보고서를 배포하기 위한 개선된 인프라 개발을 옹호한다. 다양한 제공업체의 GPAI 시스템 간에 전파될 수 있는 탈옥 및 기타 결함의 만연성을 고려할 때 이러한 개입은 점점 더 시급해지고 있다. AI 생태계에서 강력한 보고 및 조정을 촉진함으로써, 이러한 제안은 GPAI 시스템의 안전성, 보안 및 책임성을 크게 향상시킬 수 있다.

시사점, 한계점

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시사점:

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GPAI 시스템의 안전성 향상을 위한 표준화된 결함 보고 시스템 및 절차의 필요성 제시.

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버그 바운티 프로그램 및 법적 안전 장치를 통한 책임 있는 결함 공개 방안 제안.

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다양한 이해관계자 간의 효율적인 결함 정보 공유를 위한 인프라 구축의 중요성 강조.

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GPAI 시스템의 안전성, 보안 및 책임성 향상에 기여할 수 있는 실질적인 해결책 제시.

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한계점:

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제안된 개입 방안의 구체적인 실행 계획 및 평가 방안 부재.

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다양한 이해관계자 간의 합의 및 협력을 이끌어내는 데 어려움 발생 가능성.

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GPAI 시스템의 복잡성 및 다양성으로 인한 표준화의 어려움.

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법적 안전 장치의 구체적인 내용 및 효과에 대한 추가적인 연구 필요.

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