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.

ChemDFM-R: An Chemical Reasoner LLM Enhanced with Atomized Chemical Knowledge

Training language models to be warm and empathetic makes them less reliable and more sycophantic

Decision Transformer-Based Drone Trajectory Planning with Dynamic Safety-Efficiency Trade-Offs

Multimodal LLMs as Customized Reward Models for Text-to-Image Generation

A ChatGPT-based approach for questions generation in higher education

ChartM$^3$: Benchmarking Chart Editing with Multimodal Instructions

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

FRED: Financial Retrieval-Enhanced Detection and Editing of Hallucinations in Language Models

Policy-Driven AI in Dataspaces: Taxonomy, Explainability, and Pathways for Compliant Innovation

Interpretable Open-Vocabulary Referring Object Detection with Reverse Contrast Attention

RaGS: Unleashing 3D Gaussian Splatting from 4D Radar and Monocular Cues for 3D Object Detection

TextSAM-EUS: Text Prompt Learning for SAM to Accurately Segment Pancreatic Tumor in Endoscopic Ultrasound

Ultra3D: Efficient and High-Fidelity 3D Generation with Part Attention

Probing EFX via PMMS: (Non-)Existence Results in Discrete Fair Division

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

Can GPT-4o mini and Gemini 2.0 Flash Predict Fine-Grained Fashion Product Attributes? A Zero-Shot Analysis

Scaling RL to Long Videos

Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

Mitigating loss of variance in ensemble data assimilation: machine learning-based and distance-free localization

LLM-as-a-qualitative-judge: automating error analysis in natural language generation

Equivariant Flow Matching for Point Cloud Assembly

The challenge of hidden gifts in multi-agent reinforcement learning

Curvature Dynamic Black-box Attack: revisiting adversarial robustness via dynamic curvature estimation

Outcome-based Reinforcement Learning to Predict the Future

Denoising Concept Vectors with Sparse Autoencoders for Improved Language Model Steering

Local Mixtures of Experts: Essentially Free Test-Time Training via Model Merging

Anti-Inpainting: A Proactive Defense Approach against Malicious Diffusion-based Inpainters under Unknown Conditions

Will AI Take My Job? Evolving Perceptions of Automation and Labor Risk in Latin America

Enhancing Multimodal In-Context Learning for Image Classification through Coreset Optimization

D\'ej\`a Vu: Multilingual LLM Evaluation through the Lens of Machine Translation Evaluation

OpenEarthSensing: Large-Scale Fine-Grained Benchmark for Open-World Remote Sensing

CleanMel: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR

GneissWeb: Preparing High Quality Data for LLMs at Scale

Year-over-Year Developments in Financial Fraud Detection via Deep Learning: A Systematic Literature Review

Unsupervised Learning in Echo State Networks for Input Reconstruction

Wavelet Meets Adam: Compressing Gradients for Memory-Efficient Training

Application of Vision-Language Model to Pedestrians Behavior and Scene Understanding in Autonomous Driving

SyncDiff: Synchronized Motion Diffusion for Multi-Body Human-Object Interaction Synthesis

Rationale-guided Prompting for Knowledge-based Visual Question Answering

Modeling Story Expectations to Understand Engagement: A Generative Framework Using LLMs

FastTrackTr:Towards Fast Multi-Object Tracking with Transformers

Toward Automated Validation of Language Model Synthesized Test Cases using Semantic Entropy

StoryTeller: Improving Long Video Description through Global Audio-Visual Character Identification

Natural Language Processing for the Legal Domain: A Survey of Tasks, Datasets, Models, and Challenges

Positive-Augmented Contrastive Learning for Vision-and-Language Evaluation and Training

Neutral Residues: Revisiting Adapters for Model Extension

Past Meets Present: Creating Historical Analogy with Large Language Models

Automated Prompt Engineering for Cost-Effective Code Generation Using Evolutionary Algorithm

Strategic Integration of Artificial Intelligence in the C-Suite: The Role of the Chief AI Officer

The Cooperative Network Architecture: Learning Structured Networks as Representation of Sensory Patterns

NeurIT: Pushing the Limit of Neural Inertial Tracking for Indoor Robotic IoT

Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions

Bridging Privacy and Robustness for Trustworthy Machine Learning

Towards the Law of Capacity Gap in Distilling Language Models

Federated Distributionally Robust Optimization with Non-Convex Objectives: Algorithm and Analysis

UI-AGILE: Advancing GUI Agents with Effective Reinforcement Learning and Precise Inference-Time Grounding

Efficient Pain Recognition via Respiration Signals: A Single Cross-Attention Transformer Multi-Window Fusion Pipeline

Multi-Representation Diagrams for Pain Recognition: Integrating Various Electrodermal Activity Signals into a Single Image

Tiny-BioMoE: a Lightweight Embedding Model for Biosignal Analysis

MultiEditor: Controllable Multimodal Object Editing for Driving Scenarios Using 3D Gaussian Splatting Priors

DualSG: A Dual-Stream Explicit Semantic-Guided Multivariate Time Series Forecasting Framework

ST-GDance: Long-Term and Collision-Free Group Choreography from Music

A Survey of Self-Evolving Agents: On Path to Artificial Super Intelligence

Multi-Agent Reinforcement Learning for Dynamic Mobility Resource Allocation with Hierarchical Adaptive Grouping

HypKG: Hypergraph-based Knowledge Graph Contextualization for Precision Healthcare

The wall confronting large language models

Clustering via Self-Supervised Diffusion

Embodied Web Agents: Bridging Physical-Digital Realms for Integrated Agent Intelligence

Subgoal-Guided Policy Heuristic Search with Learned Subgoals

Don't Lag, RAG: Training-Free Adversarial Detection Using RAG

AGITB: A Signal-Level Benchmark for Evaluating Artificial General Intelligence

Scoring Verifiers: Evaluating Synthetic Verification for Code and Reasoning

CollabLLM: From Passive Responders to Active Collaborators

A Survey on Large Language Model Acceleration based on KV Cache Management

Can adversarial attacks by large language models be attributed?

Learning Neural Strategy-Proof Matching Mechanism from Examples

KIX: A Knowledge and Interaction-Centric Metacognitive Framework for Task Generalization

Where to show Demos in Your Prompt: A Positional Bias of In-Context Learning

A Bit of Freedom Goes a Long Way: Classical and Quantum Algorithms for Reinforcement Learning under a Generative Model

Repair-R1: Better Test Before Repair

RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents

CapRecover: A Cross-Modality Feature Inversion Attack Framework on Vision Language Models

MoCHA: Advanced Vision-Language Reasoning with MoE Connector and Hierarchical Group Attention

Advancing Fetal Ultrasound Image Quality Assessment in Low-Resource Settings

G-Core: A Simple, Scalable and Balanced RLHF Trainer

Empirical Evaluation of Concept Drift in ML-Based Android Malware Detection

Teaching the Teacher: Improving Neural Network Distillability for Symbolic Regression via Jacobian Regularization

Bayesian Optimization of Process Parameters of a Sensor-Based Sorting System using Gaussian Processes as Surrogate Models

Of Good Demons and Bad Angels: Guaranteeing Safe Control under Finite Precision

Reducing Hallucinations in Summarization via Reinforcement Learning with Entity Hallucination Index

OFCnetLLM: Large Language Model for Network Monitoring and Alertness

Bifr\"{o}st: Spatial Networking with Bigraphs

Hydra-Bench: A Benchmark for Multi-Modal Leaf Wetness Sensing

Designing for Self-Regulation in Informal Programming Learning: Insights from a Storytelling-Centric Approach

RobEthiChor: Automated Context-aware Ethics-based Negotiation for Autonomous Robots

A Systematic Literature Review on Detecting Software Vulnerabilities with Large Language Models

Safe Deployment of Offline Reinforcement Learning via Input Convex Action Correction

H2Tune: Federated Foundation Model Fine-Tuning with Hybrid Heterogeneity

LOTS of Fashion! Multi-Conditioning for Image Generation via Sketch-Text Pairing

Adaptive Duration Model for Text Speech Alignment

Probing and Steering Evaluation Awareness of Language Models

Created by

Haebom

저자

Jord Nguyen, Khiem Hoang, Carlo Leonardo Attubato, Felix Hofstatter

개요

Llama-3.3-70B-Instruct 모델을 대상으로 평가 인식(evaluation awareness) 현상을 연구했습니다. 평가 인식이란 언어 모델이 테스트 단계와 배포 단계를 구분하는 능력을 말하며, AI 거버넌스 프레임워크 및 자발적인 산업 약속의 신뢰성을 저해할 수 있는 심각한 안전 및 정책적 의미를 지닙니다. 본 논문에서는 선형 프로브(linear probes)를 사용하여 실제 평가 프롬프트와 배포 프롬프트를 구분할 수 있음을 보였으며, 이는 현재 모델이 내부적으로 이러한 구분을 나타낸다는 것을 시사합니다. 또한, 현재의 안전 평가가 프로브에 의해 정확하게 분류되는 것을 발견하여, 모델에게 이미 인공적이거나 비진실적으로 보인다는 것을 시사합니다. 이러한 결과는 신뢰할 수 있는 평가를 보장하고 기만적인 기능을 이해하는 것이 중요함을 강조합니다. 더 넓게 보면, 본 연구는 특히 평가 인식과 기만에 더 능숙한 미래 모델을 위해 블랙박스 방식의 안전 감사를 지원하는 데 모델 내부를 어떻게 활용할 수 있는지 보여줍니다.

시사점, 한계점

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시사점:

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언어 모델의 평가 인식 능력이 AI 거버넌스 및 안전 평가의 신뢰성에 심각한 위협이 될 수 있음을 보여줍니다.

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선형 프로브와 같은 블랙박스 기법을 활용하여 모델의 내부 표현을 분석함으로써 안전 감사를 향상시킬 수 있는 가능성을 제시합니다.

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현재의 안전 평가 방식이 모델에 의해 인식될 수 있으며, 더욱 정교한 평가 방법의 필요성을 강조합니다.

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한계점:

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연구 대상이 Llama-3.3-70B-Instruct 하나의 모델에 국한되어 일반화에 대한 추가 연구가 필요합니다.

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선형 프로브의 성능은 모델의 내부 표현에 대한 완전한 이해를 제공하지 못할 수 있습니다.

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평가 인식에 대한 더욱 심층적인 메커니즘 분석이 필요합니다.

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