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.

Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning for LLMs

Accurate and scalable exchange-correlation with deep learning

AIn't Nothing But a Survey? Using Large Language Models for Coding German Open-Ended Survey Responses on Survey Motivation

Probabilistic Aggregation and Targeted Embedding Optimization for Collective Moral Reasoning in Large Language Models

Aligning Evaluation with Clinical Priorities: Calibration, Label Shift, and Error Costs

GRAM: A Generative Foundation Reward Model for Reward Generalization

VideoMAR: Autoregressive Video Generatio with Continuous Tokens

FrontendBench: A Benchmark for Evaluating LLMs on Front-End Development via Automatic Evaluation

Seewo's Submission to MLC-SLM: Lessons learned from Speech Reasoning Language Models

No-Regret Learning Under Adversarial Resource Constraints: A Spending Plan Is All You Need!

Serving Large Language Models on Huawei CloudMatrix384

PLD: A Choice-Theoretic List-Wise Knowledge Distillation

TARDIS STRIDE: A Spatio-Temporal Road Image Dataset and World Model for Autonomy

Refactoring Codebases through Library Design

TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding

Multi-Agent Language Models: Advancing Cooperation, Coordination, and Adaptation

Multi-Task Reward Learning from Human Ratings

Too Big to Think: Capacity, Memorization, and Generalization in Pre-Trained Transformers

Router-R1: Teaching LLMs Multi-Round Routing and Aggregation via Reinforcement Learning

Vision Transformers Don't Need Trained Registers

BIS Reasoning 1.0: The First Large-Scale Japanese Benchmark for Belief-Inconsistent Syllogistic Reasoning

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

CORA: Coalitional Rational Advantage Decomposition for Multi-Agent Policy Gradients

Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications

ChemHAS: Hierarchical Agent Stacking for Enhancing Chemistry Tools

ALPS: Attention Localization and Pruning Strategy for Efficient Alignment of Large Language Models

Think Twice before Adaptation: Improving Adaptability of DeepFake Detection via Online Test-Time Adaptation

Efficient Long CoT Reasoning in Small Language Models

Imagine Beyond! Distributionally Robust Auto-Encoding for State Space Coverage in Online Reinforcement Learning

MSVIT: Improving Spiking Vision Transformer Using Multi-scale Attention Fusion

J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization

Fractured Chain-of-Thought Reasoning

DreamGen: Unlocking Generalization in Robot Learning through Video World Models

UD-English-CHILDES: A Collected Resource of Gold and Silver Universal Dependencies Trees for Child Language Interactions

Position Paper: Rethinking Privacy in RL for Sequential Decision-making in the Age of LLMs

Influential Bandits: Pulling an Arm May Change the Environment

SCAM: A Real-World Typographic Robustness Evaluation for Multimodal Foundation Models

Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning

Exploring Personalized Federated Learning Architectures for Violence Detection in Surveillance Videos

A Bird Song Detector for improving bird identification through Deep Learning: a case study from Do\~nana

KANITE: Kolmogorov-Arnold Networks for ITE estimation

Beyond Propagation of Chaos: A Stochastic Algorithm for Mean Field Optimization

Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing

Adding Chocolate to Mint: Mitigating Metric Interference in Machine Translation

EgoBlind: Towards Egocentric Visual Assistance for the Blind

PsychBench: A comprehensive and professional benchmark for evaluating the performance of LLM-assisted psychiatric clinical practice

Machine Learners Should Acknowledge the Legal Implications of Large Language Models as Personal Data

Supporting the development of Machine Learning for fundamental science in a federated Cloud with the AI_INFN platform

CODESYNC: Synchronizing Large Language Models with Dynamic Code Evolution at Scale

Wolfpack Adversarial Attack for Robust Multi-Agent Reinforcement Learning

Task-Aware Virtual Training: Enhancing Generalization in Meta-Reinforcement Learning for Out-of-Distribution Tasks

Representations Shape Weak-to-Strong Generalization: Theoretical Insights and Empirical Predictions

Perspective Transition of Large Language Models for Solving Subjective Tasks

Can LLMs Ask Good Questions?

Aligning AI Research with the Needs of Clinical Coding Workflows: Eight Recommendations Based on US Data Analysis and Critical Review

SurgSora: Object-Aware Diffusion Model for Controllable Surgical Video Generation

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

Multiclass Post-Earthquake Building Assessment Integrating High-Resolution Optical and SAR Satellite Imagery, Ground Motion, and Soil Data with Transformers

REVOLVE: Optimizing AI Systems by Tracking Response Evolution in Textual Optimization

FLARE: Towards Universal Dataset Purification against Backdoor Attacks

Heterogeneous Relationships of Subjects and Shapelets for Semi-supervised Multivariate Series Classification

Contrast Similarity-Aware Dual-Pathway Mamba for Multivariate Time Series Node Classification

Semantic-Geometric-Physical-Driven Robot Manipulation Skill Transfer via Skill Library and Tactile Representation

LL\"aMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch

Math Neurosurgery: Isolating Language Models' Math Reasoning Abilities Using Only Forward Passes

The Epochal Sawtooth Phenomenon: Unveiling Training Loss Oscillations in Adam and Other Optimizers

Pap2Pat: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairs

Deep Graph Anomaly Detection: A Survey and New Perspectives

A Novel Perturb-ability Score to Mitigate Evasion Adversarial Attacks on Flow-Based ML-NIDS

Style-Preserving Lip Sync via Audio-Aware Style Reference

Advancing oncology with federated learning: transcending boundaries in breast, lung, and prostate cancer. A systematic review

Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey

Informed Correctors for Discrete Diffusion Models

RadioRAG: Online Retrieval-augmented Generation for Radiology Question Answering

A Systematic Survey of Natural Language Processing for the Greek Language

Predicting the Understandability of Computational Notebooks through Code Metrics Analysis

An Effective Incorporating Heterogeneous Knowledge Curriculum Learning for Sequence Labeling

HiURE: Hierarchical Exemplar Contrastive Learning for Unsupervised Relation Extraction

The NordDRG AI Benchmark for Large Language Models

From Data-Driven to Purpose-Driven Artificial Intelligence: Systems Thinking for Data-Analytic Automation of Patient Care

Breaking Bad Molecules: Are MLLMs Ready for Structure-Level Molecular Detoxification?

Entropy-based Exploration Conduction for Multi-step Reasoning

Solving Satisfiability Modulo Counting Exactly with Probabilistic Circuits

Synthesizing Composite Hierarchical Structure from Symbolic Music Corpora

Learning Strategic Language Agents in the Werewolf Game with Iterative Latent Space Policy Optimization

Optimal Transport for Probabilistic Circuits

OM4OV: Leveraging Ontology Matching for Ontology Versioning

Behaviour Planning: A Toolkit for Diverse Planning

Spatial Context-based Self-Supervised Learning for Handwritten Text Recognition

"Generate" the Future of Work through AI: Empirical Evidence from Online Labor Markets

Dense SAE Latents Are Features, Not Bugs

Sekai: A Video Dataset towards World Exploration

Leaky Thoughts: Large Reasoning Models Are Not Private Thinkers

AutoRule: Reasoning Chain-of-thought Extracted Rule-based Rewards Improve Preference Learning

Demystifying the Visual Quality Paradox in Multimodal Large Language Models

Revisiting Compositional Generalization Capability of Large Language Models Considering Instruction Following Ability

Federated Learning for MRI-based BrainAGE: a multicenter study on post-stroke functional outcome prediction

GFLC: Graph-based Fairness-aware Label Correction for Fair Classification

The Compositional Architecture of Regret in Large Language Models

LoX: Low-Rank Extrapolation Robustifies LLM Safety Against Fine-tuning

MORALISE: A Structured Benchmark for Moral Alignment in Visual Language Models

Created by

Haebom

저자

Xiao Lin, Zhining Liu, Ze Yang, Gaotang Li, Ruizhong Qiu, Shuke Wang, Hui Liu, Haotian Li, Sumit Keswani, Vishwa Pardeshi, Huijun Zhao, Wei Fan, Hanghang Tong

개요

본 논문은 자율주행 및 의료 분석과 같이 도덕적으로 민감한 영역에서 점점 더 영향력이 커지고 있는 비전-언어 모델(VLMs)의 도덕적 정렬을 평가하기 위한 포괄적인 벤치마크인 MORALISE를 제시합니다. 기존 연구의 한계점인 텍스트 모달리티에만 초점을 맞추거나 AI 생성 이미지에 의존하는 문제를 극복하기 위해, Turiel의 영역 이론을 기반으로 13가지 도덕적 주제를 제시하고, 전문가 검증을 거친 2,481개의 고품질 이미지-텍스트 쌍을 수동으로 큐레이션했습니다. 각 쌍에는 도덕적 주제 위반 여부와 위반의 모달리티(이미지 또는 텍스트)를 나타내는 두 가지 세분화된 레이블이 부여됩니다. 평가를 위해 도덕적 판단 및 도덕적 규범 귀속 두 가지 작업을 포함하며, 19개의 인기 있는 오픈 및 클로즈 소스 VLM에 대한 광범위한 실험을 통해 최첨단 모델에서 지속적인 도덕적 한계를 보여줍니다. MORALISE 벤치마크는 https://huggingface.co/datasets/Ze1025/MORALISE 에서 공개적으로 이용 가능합니다.

Ze1025/MORALISE · Datasets at Hugging Face

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

시사점, 한계점

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시사점:

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Turiel의 영역 이론에 기반한 13가지 도덕적 주제를 포함하는 포괄적인 도덕적 정렬 평가 벤치마크를 제시합니다.

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실제 세계 데이터를 사용하여 생성된 이미지와 텍스트의 도덕적 위반을 평가함으로써 현실적인 평가를 제공합니다.

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도덕적 판단 및 도덕적 규범 귀속이라는 두 가지 평가 작업을 통해 VLMs의 도덕적 인식과 추론 능력을 종합적으로 평가합니다.

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최첨단 VLMs의 도덕적 한계를 드러내어 향후 연구 방향을 제시합니다.

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공개적으로 이용 가능한 벤치마크 데이터셋을 제공합니다.

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한계점:

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수동으로 데이터를 큐레이션하여 시간과 자원이 많이 소요될 수 있습니다.

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벤치마크에 포함된 도덕적 주제가 모든 상황을 포괄하지 못할 수 있습니다.

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전문가 검증 과정에서 주관적인 판단이 개입될 가능성이 있습니다.

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다양한 문화적 배경을 고려하지 못했을 가능성이 있습니다.

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새로운 유형의 도덕적 위반에 대한 적응성이 부족할 수 있습니다.

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