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.

Strategic Dishonesty Can Undermine AI Safety Evaluations of Frontier LLMs

Reinforced Generation of Combinatorial Structures: Applications to Complexity Theory

The Narcissus Hypothesis: Descending to the Rung of Illusion

Adaptive Kernel Design for Bayesian Optimization Is a Piece of CAKE with LLMs

Joint Memory Frequency and Computing Frequency Scaling for Energy-efficient DNN Inference

Fine-Grained Detection of AI-Generated Text Using Sentence-Level Segmentation

Multimodal Medical Image Classification via Synergistic Learning Pre-training

MVCL-DAF++: Enhancing Multimodal Intent Recognition via Prototype-Aware Contrastive Alignment and Coarse-to-Fine Dynamic Attention Fusion

A Chain-of-thought Reasoning Breast Ultrasound Dataset Covering All Histopathology Categories

PruneCD: Contrasting Pruned Self Model to Improve Decoding Factuality

AHA - Predicting What Matters Next: Online Highlight Detection Without Looking Ahead

Highly Imbalanced Regression with Tabular Data in SEP and Other Applications

Gender and Political Bias in Large Language Models: A Demonstration Platform

RPG: A Repository Planning Graph for Unified and Scalable Codebase Generation

Interpretable Nanoporous Materials Design with Symmetry-Aware Networks

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models

MOCHA: Multi-modal Objects-aware Cross-arcHitecture Alignment

LLM Agents for Interactive Workflow Provenance: Reference Architecture and Evaluation Methodology

Justice in Judgment: Unveiling (Hidden) Bias in LLM-assisted Peer Reviews

Single-stream Policy Optimization

FragmentGPT: A Unified GPT Model for Fragment Growing, Linking, and Merging in Molecular Design

ToMA: Token Merge with Attention for Diffusion Models

Clip Your Sequences Fairly: Enforcing Length Fairness for Sequence-Level RL

MEGS$^{2}$: Memory-Efficient Gaussian Splatting via Spherical Gaussians and Unified Pruning

FediLoRA: Heterogeneous LoRA for Federated Multimodal Fine-tuning under Missing Modalities

Long-Range Graph Wavelet Networks

Agentic Software Engineering: Foundational Pillars and a Research Roadmap

TinyDef-DETR: A DETR-based Framework for Defect Detection in Transmission Lines from UAV Imagery

PDTrim: Targeted Pruning for Prefill-Decode Disaggregation in Inference

The Transparent Earth: A Multimodal Foundation Model for the Earth's Subsurface

An Information-Flow Perspective on Explainability Requirements: Specification and Verification

SoK: Large Language Model Copyright Auditing via Fingerprinting

Unlearning as Ablation: Toward a Falsifiable Benchmark for Generative Scientific Discovery

Linguistic Neuron Overlap Patterns to Facilitate Cross-lingual Transfer on Low-resource Languages

Retrieval Enhanced Feedback via In-context Neural Error-book

OpenWHO: A Document-Level Parallel Corpus for Health Translation in Low-Resource Languages

Hierarchical Evaluation Function: A Multi-Metric Approach for Optimizing Demand Forecasting Models

Generative Medical Event Models Improve with Scale

Benchmarking Quantum and Classical Sequential Models for Urban Telecommunication Forecasting

Integrating Belief Domains into Probabilistic Logic Programs

Automating Steering for Safe Multimodal Large Language Models

QSpark: Towards Reliable Qiskit Code Generation

Prompting for Performance: Exploring LLMs for Configuring Software

Intra-DP: A High Performance Collaborative Inference System for Mobile Edge Computing

Exploring Image Generation via Mutually Exclusive Probability Spaces and Local Correlation Hypothesis

Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models

Image Segmentation and Classification of E-waste for Training Robots for Waste Segregation

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

Speculative Decoding via Hybrid Drafting and Rollback-Aware Branch Parallelism

Foresight: Adaptive Layer Reuse for Accelerated and High-Quality Text-to-Video Generation

BroadGen: A Framework for Generating Effective and Efficient Advertiser Broad Match Keyphrase Recommendations

Large Language Models Implicitly Learn to See and Hear Just By Reading

AvatarShield: Visual Reinforcement Learning for Human-Centric Synthetic Video Detection

WavReward: Spoken Dialogue Models With Generalist Reward Evaluators

Beyond Input Activations: Identifying Influential Latents by Gradient Sparse Autoencoders

Pandora: A Code-Driven Large Language Model Agent for Unified Reasoning Across Diverse Structured Knowledge

Visual Chronicles: Using Multimodal LLMs to Analyze Massive Collections of Images

LookAhead Tuning: Safer Language Models via Partial Answer Previews

CaKE: Circuit-aware Editing Enables Generalizable Knowledge Learners

A Survey on Sparse Autoencoders: Interpreting the Internal Mechanisms of Large Language Models

Union of Experts: Adapting Hierarchical Routing to Equivalently Decomposed Transformer

Leveraging Large Models to Evaluate Novel Content: A Case Study on Advertisement Creativity

Promote, Suppress, Iterate: How Language Models Answer One-to-Many Factual Queries

Can LLMs Explain Themselves Counterfactually?

Structure-prior Informed Diffusion Model for Graph Source Localization with Limited Data

THFlow: A Temporally Hierarchical Flow Matching Framework for 3D Peptide Design

LightThinker: Thinking Step-by-Step Compression

Purest Quantum State Identification

JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework

Language Models Can Predict Their Own Behavior

DeepResonance: Enhancing Multimodal Music Understanding via Music-centric Multi-way Instruction Tuning

Without Paired Labeled Data: End-to-End Self-Supervised Learning for Drone-view Geo-Localization

Fine-Tuning is Subgraph Search: A New Lens on Learning Dynamics

EventVL: Understand Event Streams via Multimodal Large Language Model

Injecting Explainability and Lightweight Design into Weakly Supervised Video Anomaly Detection Systems

Biology-Instructions: A Dataset and Benchmark for Multi-Omics Sequence Understanding Capability of Large Language Models

Backdoor Attack with Invisible Triggers Based on Model Architecture Modification

Language Models as Causal Effect Generators

EMMA: End-to-End Multimodal Model for Autonomous Driving

Exploring Model Kinship for Merging Large Language Models

Post-hoc Study of Climate Microtargeting on Social Media Ads with LLMs: Thematic Insights and Fairness Evaluation

Variational Bayes Gaussian Splatting

DOTA: Distributional Test-Time Adaptation of Vision-Language Models

GALLa: Graph Aligned Large Language Models for Improved Source Code Understanding

LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture

Your Turn: At Home Turning Angle Estimation for Parkinson's Disease Severity Assessment

MediSyn: A Generalist Text-Guided Latent Diffusion Model For Diverse Medical Image Synthesis

Socially Pertinent Robots in Gerontological Healthcare

"What is Different Between These Datasets?" A Framework for Explaining Data Distribution Shifts

Is Pre-training Truly Better Than Meta-Learning?

Improving Image Captioning Descriptiveness by Ranking and LLM-based Fusion

Mitigating Strategy-Selection Bias in Reasoning for More Effective Test-Time Scaling

Virtual Arc Consistency for Linear Constraints in Cost Function Networks

A Multimodal Conversational Assistant for the Characterization of Agricultural Plots from Geospatial Open Data

Program Synthesis via Test-Time Transduction

OpenLens AI: Fully Autonomous Research Agent for Health Infomatics

Difficulty-Aware Agent Orchestration in LLM-Powered Workflows

Abduct, Act, Predict: Scaffolding Causal Inference for Automated Failure Attribution in Multi-Agent Systems

TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning

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

Gender and Political Bias in Large Language Models: A Demonstration Platform

Created by

Haebom

저자

Wenjie Lin, Hange Liu, Xutao Mao, Yingying Zhuang, Jingwei Shi, Xudong Han, Tianyu Shi, Jinrui Yang

개요

ParlAI Vote는 유럽 의회 토론 및 투표를 탐색하고, 투표 예측 및 편향 분석에 대한 거대 언어 모델(LLM)을 테스트하기 위한 대화형 시스템입니다. 이 플랫폼은 토론 주제, 연설, 그리고 명부 투표 결과를 연결하며, 성별, 연령, 국가, 정치 집단과 같은 풍부한 인구 통계 데이터를 포함합니다. 사용자는 토론을 탐색하고, 연결된 연설을 검토하고, 최첨단 LLM의 예측과 실제 투표 결과를 비교하며, 인구 통계 집단별 오류 내역을 확인할 수 있습니다. EuroParlVote 벤치마크와 성별 분류 및 투표 예측이라는 핵심 과제를 시각화하여, ParlAI Vote는 최첨단 LLM의 체계적인 성능 편향을 강조합니다. 이 시스템은 데이터, 모델, 시각적 분석을 단일 인터페이스로 통합하여 결과 재현, 행동 감사 및 반실증적 시나리오 실행의 장벽을 낮춥니다. 입법적 의사 결정에 대한 연구, 교육 및 대중 참여를 지원하는 동시에 정치 분석에서 현재 LLM의 강점과 한계를 명확히 합니다.

시사점, 한계점

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시사점:

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유럽 의회 토론 및 투표 데이터와 최첨단 LLM을 결합하여 투표 예측 및 편향 분석을 위한 강력한 플랫폼 제공.

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LLM의 성능 편향을 시각화하여 투명성 및 책임성 증대.

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연구, 교육 및 대중 참여를 위한 접근성 향상.

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반실증적 시나리오를 통해 LLM의 의사결정 과정 이해 증진.

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한계점:

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플랫폼의 데이터는 유럽 의회에 한정됨.

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LLM의 편향을 완전히 해결하는 방법 제시는 아님.

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플랫폼의 사용 편의성 및 확장성에 대한 추가적인 연구 필요.

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