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.

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model

Power Stabilization for AI Training Datacenters

A Systematic Study of Deep Learning Models and xAI Methods for Region-of-Interest Detection in MRI Scans

Documenting Deployment with Fabric: A Repository of Real-World AI Governance

Surya: Foundation Model for Heliophysics

Hard Examples Are All You Need: Maximizing GRPO Post-Training Under Annotation Budgets

MCLPD:Multi-view Contrastive Learning for EEG-based PD Detection Across Datasets

FinAgentBench: A Benchmark Dataset for Agentic Retrieval in Financial Question Answering

VerilogLAVD: LLM-Aided Rule Generation for Vulnerability Detection in Verilog

Kourkoutas-Beta: A Sunspike-Driven Adam Optimizer with Desert Flair

SecFSM: Knowledge Graph-Guided Verilog Code Generation for Secure Finite State Machines in Systems-on-Chip

Fortifying the Agentic Web: A Unified Zero-Trust Architecture Against Logic-layer Threats

LATTE: Learning Aligned Transactions and Textual Embeddings for Bank Clients

Preacher: Paper-to-Video Agentic System

Agoran: An Agentic Open Marketplace for 6G RAN Automation

Architectural Co-Design for Zero-Shot Anomaly Detection: Decoupling Representation and Dynamically Fusing Features in CLIP

IBPS: Indian Bail Prediction System

Diagnosing Memorization in Chain-of-Thought Reasoning, One Token at a Time

TS-Insight: Visualizing Thompson Sampling for Verification and XAI

When Better Eyes Lead to Blindness: A Diagnostic Study of the Information Bottleneck in CNN-LSTM Image Captioning Models

Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters

Generation of structure-guided pMHC-I libraries using Diffusion Models

Cross-Modality Masked Learning for Survival Prediction in ICI Treated NSCLC Patients

MCA-RG: Enhancing LLMs with Medical Concept Alignment for Radiology Report Generation

KEA Explain: Explanations of Hallucinations using Graph Kernel Analysis

Empirical Evidence for Alignment Faking in a Small LLM and Prompt-Based Mitigation Techniques

A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysis

Deep regularization networks for inverse problems with noisy operators

LaMP-Cap: Personalized Figure Caption Generation With Multimodal Figure Profiles

On the Fundamental Impossibility of Hallucination Control in Large Language Models

Lossless Token Sequence Compression via Meta-Tokens

Versatile Cardiovascular Signal Generation with a Unified Diffusion Transformer

Flexible Tool Selection through Low-dimensional Attribute Alignment of Vision and Language

Mutarjim: Advancing Bidirectional Arabic-English Translation with a Small Language Model

MMiC: Mitigating Modality Incompleteness in Clustered Federated Learning

Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey

Sadeed: Advancing Arabic Diacritization Through Small Language Model

Annif at SemEval-2025 Task 5: Traditional XMTC augmented by LLMs

CaRL: Learning Scalable Planning Policies with Simple Rewards

On the Consistency of GNN Explanations for Malware Detection

Cequel: Cost-Effective Querying of Large Language Models for Text Clustering

Kuwain 1.5B: An Arabic SLM via Language Injection

MuSeD: A Multimodal Spanish Dataset for Sexism Detection in Social Media Videos

TextSplat: Text-Guided Semantic Fusion for Generalizable Gaussian Splatting

VerifiAgent: a Unified Verification Agent in Language Model Reasoning

Embodied Long Horizon Manipulation with Closed-loop Code Generation and Incremental Few-shot Adaptation

Revisiting Out-of-Distribution Detection in Real-time Object Detection: From Benchmark Pitfalls to a New Mitigation Paradigm

A Case for Specialisation in Non-Human Entities

Pragmatic Inference Chain (PIC) Improving LLMs' Reasoning of Authentic Implicit Toxic Language

Synthetic vs. Gold: The Role of LLM Generated Labels and Data in Cyberbullying Detection

Innamark: A Whitespace Replacement Information-Hiding Method

Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering

RefineCoder: Iterative Improving of Large Language Models via Adaptive Critique Refinement for Code Generation

Setup Once, Secure Always: A Single-Setup Secure Federated Learning Aggregation Protocol with Forward and Backward Secrecy for Dynamic Users

Self-Supervised Prompt Optimization

Learning to Generate Unit Tests for Automated Debugging

Modeling Discrimination with Causal Abstraction

Large Language Models for Automated Literature Review: An Evaluation of Reference Generation, Abstract Writing, and Review Composition

Evaluation Agent: Efficient and Promptable Evaluation Framework for Visual Generative Models

Knowledge-Guided Prompt Learning for Request Quality Assurance in Public Code Review

Fine-tuning foundational models to code diagnoses from veterinary health records

Teuken-7B-Base & Teuken-7B-Instruct: Towards European LLMs

Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models

Continual Learning for Multimodal Data Fusion of a Soft Gripper

BoostTrack++: using tracklet information to detect more objects in multiple object tracking

OPDR: Order-Preserving Dimension Reduction for Semantic Embedding of Multimodal Scientific Data

CREMA: A Contrastive Regularized Masked Autoencoder for Robust ECG Diagnostics across Clinical Domains

Generating 3D Terrain with 2D Cellular Automata

Unplug and Play Language Models: Decomposing Experts in Language Models at Inference Time

Using a cognitive architecture to consider antiBlackness in design and development of AI systems

ITL-LIME: Instance-Based Transfer Learning for Enhancing Local Explanations in Low-Resource Data Settings

ThinkTuning: Instilling Cognitive Reflections without Distillation

A "good regulator theorem" for embodied agents

Prescriptive Agents based on RAG for Automated Maintenance (PARAM)

One Subgoal at a Time: Zero-Shot Generalization to Arbitrary Linear Temporal Logic Requirements in Multi-Task Reinforcement Learning

Opus: A Prompt Intention Framework for Complex Workflow Generation

Exploring Big Five Personality and AI Capability Effects in LLM-Simulated Negotiation Dialogues

It's the Thought that Counts: Evaluating the Attempts of Frontier LLMs to Persuade on Harmful Topics

GATES: Cost-aware Dynamic Workflow Scheduling via Graph Attention Networks and Evolution Strategy

Automatic Curriculum Design for Zero-Shot Human-AI Coordination

PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data

SycEval: Evaluating LLM Sycophancy

CopyrightShield: Enhancing Diffusion Model Security against Copyright Infringement Attacks

VLASCD: A Visual Language Action Model for Simultaneous Chatting and Decision Making

Exploring the Effect of Explanation Content and Format on User Comprehension and Trust in Healthcare

On Learning Action Costs from Input Plans

Human-Object Interaction from Human-Level Instructions

Non-linear Welfare-Aware Strategic Learning

CRISPR-GPT for Agentic Automation of Gene-editing Experiments

SceneGen: Single-Image 3D Scene Generation in One Feedforward Pass

Discovering Hidden Algebraic Structures via Transformers with Rank-Aware Beam GRPO

LiveMCP-101: Stress Testing and Diagnosing MCP-enabled Agents on Challenging Queries

Neural Robot Dynamics

Dissecting Tool-Integrated Reasoning: An Empirical Study and Analysis

"Does the cafe entrance look accessible? Where is the door?" Towards Geospatial AI Agents for Visual Inquiries

End-to-End Agentic RAG System Training for Traceable Diagnostic Reasoning

Numerical models outperform AI weather forecasts of record-breaking extremes

EcomMMMU: Strategic Utilization of Visuals for Robust Multimodal E-Commerce Models

Tutorial on the Probabilistic Unification of Estimation Theory, Machine Learning, and Generative AI

StreamMem: Query-Agnostic KV Cache Memory for Streaming Video Understanding

Exploring Big Five Personality and AI Capability Effects in LLM-Simulated Negotiation Dialogues

Created by

Haebom

저자

Myke C. Cohen, Zhe Su, Hsien-Te Kao, Daniel Nguyen, Spencer Lynch, Maarten Sap, Svitlana Volkova

개요

본 논문은 임무 수행이 중요한 협상 상황에서 작용자 AI 시스템을 위한 평가 프레임워크를 제시합니다. 다양한 인간 운영자와 이해관계자에 적응할 수 있는 AI 에이전트의 필요성을 해결하기 위해 Sotopia 시뮬레이션 테스트베드를 사용하여 두 가지 실험을 통해 성격 특성과 AI 에이전트 특성이 LLM로 시뮬레이션된 사회적 협상 결과에 어떻게 영향을 미치는지 체계적으로 평가했습니다. 이는 팀 간 조정 및 민군 상호 작용을 포함하는 다양한 응용 프로그램에 필수적인 기능입니다. 실험 1에서는 인과적 발견 방법을 사용하여 성격 특성이 가격 협상에 미치는 영향을 측정하여, 친화성과 외향성이 신뢰성, 목표 달성 및 지식 획득 결과에 상당한 영향을 미친다는 것을 발견했습니다. 팀 커뮤니케이션에서 추출된 사회인지 어휘 척도는 에이전트의 공감적 의사소통, 도덕적 기반 및 의견 패턴에서 미묘한 차이를 감지하여, 위험이 큰 작전 시나리오에서 안정적으로 작동해야 하는 작용자 AI 시스템에 대한 실행 가능한 통찰력을 제공합니다. 실험 2에서는 시뮬레이션된 인간의 성격과 AI 시스템 특성(특히 투명성, 역량, 적응성)을 조작하여 인간-AI 직업 협상을 평가하여 AI 에이전트의 신뢰성이 임무 효과에 어떻게 영향을 미치는지 보여줍니다. 이러한 결과는 다양한 운영자의 성격과 인간-에이전트 팀 역학에 걸쳐 AI 에이전트의 신뢰성을 실험하기 위한 반복 가능한 평가 방법론을 확립하여 안정적인 AI 시스템에 대한 운영 요구 사항을 직접적으로 지원합니다. 본 연구는 표준 성능 측정 기준을 넘어 복잡한 작전에서 임무 성공에 필수적인 사회적 역동성을 통합함으로써 작용자 AI 워크플로의 평가를 발전시킵니다.

시사점, 한계점

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시사점:

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임무 수행이 중요한 협상 상황에서 작용자 AI 시스템을 평가하기 위한 반복 가능한 방법론 제시.

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성격 특성과 AI 에이전트 특성이 협상 결과에 미치는 영향에 대한 통찰력 제공.

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사회적 역동성을 고려한 AI 시스템 평가의 중요성 강조.

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다양한 인간 운영자와의 상호 작용을 고려한 AI 에이전트 설계에 대한 지침 제공.

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한계점:

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Sotopia 시뮬레이션 환경의 한계. 실제 세계 적용 가능성에 대한 추가 연구 필요.

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LLM 기반 시뮬레이션의 제한. 인간의 복잡한 행동을 완벽하게 반영하지 못할 수 있음.

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특정 성격 특성 및 AI 에이전트 특성에 대한 집중. 더 넓은 범위의 요소에 대한 추가 연구 필요.

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시뮬레이션 결과의 일반화 가능성에 대한 추가 검증 필요.

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