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.

Maximizing Confidence Alone Improves Reasoning

Pre-training for Recommendation Unlearning

FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control

On the performance of machine-learning-assisted Monte Carlo in sampling from simple statistical physics models

Agent-UniRAG: A Trainable Open-Source LLM Agent Framework for Unified Retrieval-Augmented Generation Systems

Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems

Train with Perturbation, Infer after Merging: A Two-Stage Framework for Continual Learning

SplitLoRA: Balancing Stability and Plasticity in Continual Learning Through Gradient Space Splitting

Skywork Open Reasoner 1 Technical Report

Speculative Decoding Meets Quantization: Compatibility Evaluation and Hierarchical Framework Design

DORAEMON: Decentralized Ontology-aware Reliable Agent with Enhanced Memory Oriented Navigation

Cross-modal RAG: Sub-dimensional Retrieval-Augmented Text-to-Image Generation

CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation

Scaling Up Liquid-Resistance Liquid-Capacitance Networks for Efficient Sequence Modeling

Is Attention Required for Transformer Inference? Explore Function-preserving Attention Replacement

VietASR: Achieving Industry-level Vietnamese ASR with 50-hour labeled data and Large-Scale Speech Pretraining

Hume: Introducing System-2 Thinking in Visual-Language-Action Model

DeSocial: Blockchain-based Decentralized Social Networks

Subgroups Matter for Robust Bias Mitigation

Hybrid Disagreement-Diversity Active Learning for Bioacoustic Sound Event Detection

Automatic Transmission for LLM Tiers: Optimizing Cost and Accuracy in Large Language Models

The challenge of hidden gifts in multi-agent reinforcement learning

Retrieval Visual Contrastive Decoding to Mitigate Object Hallucinations in Large Vision-Language Models

Risk-aware Direct Preference Optimization under Nested Risk Measure

Surrogate-Assisted Evolutionary Reinforcement Learning Based on Autoencoder and Hyperbolic Neural Network

A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control

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

Reality Check: A New Evaluation Ecosystem Is Necessary to Understand AI's Real World Effects

How We Won the ISLES'24 Challenge by Preprocessing

SP2RINT: Spatially-Decoupled Physics-Inspired Progressive Inverse Optimization for Scalable, PDE-Constrained Meta-Optical Neural Network Training

Seek-CAD: A Self-refined Generative Modeling for 3D Parametric CAD Using Local Inference via DeepSeek

Rethinking the Sampling Criteria in Reinforcement Learning for LLM Reasoning: A Competence-Difficulty Alignment Perspective

OrionBench: A Benchmark for Chart and Human-Recognizable Object Detection in Infographics

EarthSE: A Benchmark Evaluating Earth Scientific Exploration Capability for Large Language Models

CASS: Nvidia to AMD Transpilation with Data, Models, and Benchmark

Beyond Face Swapping: A Diffusion-Based Digital Human Benchmark for Multimodal Deepfake Detection

Edge-First Language Model Inference: Models, Metrics, and Tradeoffs

Smaller, Smarter, Closer: The Edge of Collaborative Generative AI

YESciEval: Robust LLM-as-a-Judge for Scientific Question Answering

DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models

Articulatory Feature Prediction from Surface EMG during Speech Production

Exploring Spatiotemporal Emotional Synchrony in Dyadic Interactions: The Role of Speech Conditions in Facial and Vocal Affective Alignment

LEXam: Benchmarking Legal Reasoning on 340 Law Exams

Neural Networks as Universal Finite-State Machines: A Constructive Deterministic Finite Automaton Theory

The Geometry of ReLU Networks through the ReLU Transition Graph

RepCali: High Efficient Fine-tuning Via Representation Calibration in Latent Space for Pre-trained Language Models

Fusing Bidirectional Chains of Thought and Reward Mechanisms A Method for Enhancing Question-Answering Capabilities of Large Language Models for Chinese Intangible Cultural Heritage

Multimodal Survival Modeling in the Age of Foundation Models

Burger: Robust Graph Denoising-augmentation Fusion and Multi-semantic Modeling in Social Recommendation

The Aloe Family Recipe for Open and Specialized Healthcare LLMs

To Judge or not to Judge: Using LLM Judgements for Advertiser Keyphrase Relevance at eBay

LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection

CoordField: Coordination Field for Agentic UAV Task Allocation In Low-altitude Urban Scenarios

Learning to Reason under Off-Policy Guidance

A Combinatorial Theory of Dropout: Subnetworks, Graph Geometry, and Generalization

Error Broadcast and Decorrelation as a Potential Artificial and Natural Learning Mechanism

Carbon-Efficient 3D DNN Acceleration: Optimizing Performance and Sustainability

Agentic Knowledgeable Self-awareness

Are Domain Generalization Benchmarks with Accuracy on the Line Misspecified?

MiZero: The Shadowy Defender Against Text Style Infringements

Firm or Fickle? Evaluating Large Language Models Consistency in Sequential Interactions

LoTUS: Large-Scale Machine Unlearning with a Taste of Uncertainty

Temporal Relation Extraction in Clinical Texts: A Span-based Graph Transformer Approach

LEAVS: An LLM-based Labeler for Abdominal CT Supervision

From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration

Enhancing Retrieval for ESGLLM via ESG-CID -- A Disclosure Content Index Finetuning Dataset for Mapping GRI and ESRS

DynaCode: A Dynamic Complexity-Aware Code Benchmark for Evaluating Large Language Models in Code Generation

Aligning Text to Image in Diffusion Models is Easier Than You Think

Can LLMs Reason About Program Semantics? A Comprehensive Evaluation of LLMs on Formal Specification Inference

BatteryLife: A Comprehensive Dataset and Benchmark for Battery Life Prediction

Bridging Critical Gaps in Convergent Learning: How Representational Alignment Evolves Across Layers, Training, and Distribution Shifts

ExpandR: Teaching Dense Retrievers Beyond Queries with LLM Guidance

Audio Visual Segmentation Through Text Embeddings

Privacy-Aware Joint DNN Model Deployment and Partitioning Optimization for Collaborative Edge Inference Services

Learning to Reason from Feedback at Test-Time

ParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generation

STeCa: Step-level Trajectory Calibration for LLM Agent Learning

GSQ-Tuning: Group-Shared Exponents Integer in Fully Quantized Training for LLMs On-Device Fine-tuning

Enhancing Semi-supervised Learning with Zero-shot Pseudolabels

DELMAN: Dynamic Defense Against Large Language Model Jailbreaking with Model Editing

Multilingual Encoder Knows more than You Realize: Shared Weights Pretraining for Extremely Low-Resource Languages

Jailbreaking to Jailbreak

Behavior-Regularized Diffusion Policy Optimization for Offline Reinforcement Learning

Position: Scaling LLM Agents Requires Asymptotic Analysis with LLM Primitives

CodeSteer: Symbolic-Augmented Language Models via Code/Text Guidance

Toward universal steering and monitoring of AI models

SPRI: Aligning Large Language Models with Context-Situated Principles

MedRAX: Medical Reasoning Agent for Chest X-ray

Adaptive Exploration for Multi-Reward Multi-Policy Evaluation

Wake-Informed 3D Path Planning for Autonomous Underwater Vehicles Using A* and Neural Network Approximations

Fast Large Language Model Collaborative Decoding via Speculation

A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers

Joint Localization and Activation Editing for Low-Resource Fine-Tuning

KBQA-o1: Agentic Knowledge Base Question Answering with Monte Carlo Tree Search

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability

Chain of Grounded Objectives: Bridging Process and Goal-oriented Prompting for Code Generation

Re-ranking Using Large Language Models for Mitigating Exposure to Harmful Content on Social Media Platforms

Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment

Tensor Product Attention Is All You Need

VideoRAG: Retrieval-Augmented Generation over Video Corpus

Distribution-aware Fairness Learning in Medical Image Segmentation From A Control-Theoretic Perspective

Created by

Haebom

저자

Yujin Oh, Pengfei Jin, Sangjoon Park, Sekeun Kim, Siyeop Yoon, Kyungsang Kim, Jin Sung Kim, Xiang Li, Quanzheng Li

개요

불균형적인 의료 데이터 획득으로 인해 인구 통계적 속성(예: 나이, 성별, 인종)과 임상적 요인(예: 질병 중증도)에서 발생하는 편향으로 인해 의료 영상 분할에서의 공정성을 보장하는 것이 중요합니다. 본 논문에서는 최적 제어 이론에서 영감을 받은 Distribution-aware Mixture of Experts (dMoE)를 제시합니다. dMoE의 기본 메커니즘에 대한 포괄적인 분석을 제공하고 의료 영상 분할에서 이질적인 분포에 적응하는 dMoE의 역할을 명확히 합니다. 또한, 다양한 의료 영상 분석 작업에 걸쳐 광범위한 적용 가능성을 보여주기 위해 여러 네트워크 아키텍처에 dMoE를 통합합니다. 인구 통계적 및 임상적 요인을 통합함으로써 dMoE는 두 개의 2D 벤치마크 데이터 세트와 하나의 3D 사내 데이터 세트에서 최첨단 성능을 달성합니다. 본 연구 결과는 불균형 분포에서 편향을 완화하는 데 있어 dMoE의 효과를 강조하며, 공정성 학습 패러다임 내에서 제어 이론과 의료 영상 분할을 연결하는 유망한 접근 방식을 제공합니다. 소스 코드는 https://github.com/tvseg/dMoE에서 이용 가능합니다.

GitHub - tvseg/dMoE

Contribute to tvseg/dMoE development by creating an account on GitHub.

시사점, 한계점

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시사점:

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최적 제어 이론에 기반한 dMoE 모델을 통해 의료 영상 분할에서의 공정성 문제 해결에 새로운 접근 방식을 제시합니다.

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인구 통계적 및 임상적 요인을 고려하여 불균형 데이터 분포로 인한 편향을 완화하는 효과적인 방법을 제시합니다.

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다양한 네트워크 아키텍처에 적용 가능한 범용성을 보여줍니다.

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2D 및 3D 의료 영상 데이터에서 최첨단 성능을 달성합니다.

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공개된 소스 코드를 통해 재현성과 추가 연구를 용이하게 합니다.

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한계점:

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본 논문에서 사용된 데이터셋의 일반화 가능성에 대한 추가 연구가 필요합니다.

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다른 유형의 편향(예: 알고리즘 편향)에 대한 dMoE의 효과에 대한 추가 연구가 필요합니다.

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대규모 데이터셋에 대한 dMoE의 성능 및 효율성 평가가 필요합니다.

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실제 임상 환경에서의 적용 가능성에 대한 추가적인 검증이 필요합니다.

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