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

PMOA-TTS: Introducing the PubMed Open Access Textual Times Series Corpus

Created by

Haebom

저자

Shahriar Noroozizadeh, Sayantan Kumar, George H. Chen, Jeremy C. Weiss

개요

PMOA-TTS는 124,699개의 PubMed Open Access (PMOA) 증례 보고서를 LLM 기반 파이프라인을 통해 구조화된 (사건, 시간) 타임라인으로 변환한 최초의 공개 데이터셋입니다. Llama 3.3과 DeepSeek R1을 사용하여 단일 환자 증례 보고서를 식별하고, 프롬프트 기반 추출을 통해 560만 개 이상의 타임스탬프가 찍힌 임상 사건을 추출했습니다. 임상의가 큐레이션한 참조 집합을 사용하여 이벤트 일치율(코사인 유사도 임계값 0.1에서 80% 일치), 시간 일치도(c-index > 0.90), 타임스탬프 정렬을 위한 AULTC(Area Under the Log-Time CDF) 세 가지 지표로 타임라인의 품질을 평가했습니다. 추출된 타임라인의 임베딩은 생존 예측 작업에서 최대 0.82 ± 0.01의 시간 의존적 일치 지수를 달성하여 시간적으로 구조화된 서술의 예측 값을 보여줍니다. PMOA-TTS는 생의학 NLP에서 타임라인 추출, 시간 추론 및 종단 연구 모델링을 위한 확장 가능한 기반을 제공합니다. 데이터셋은 https://huggingface.co/datasets/snoroozi/pmoa-tts 에서 이용 가능합니다.

snoroozi/pmoa-tts · 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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대규모의 공개적으로 이용 가능한 시간 주석이 달린 임상 서술 데이터셋을 제공합니다.

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LLM 기반 파이프라인을 활용하여 시간 정보 추출의 확장성을 입증합니다.

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추출된 타임라인의 높은 정확도와 생존 예측에서의 예측력을 보여줍니다.

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생의학 NLP 분야에서 시간 추론 및 종단 연구 모델링 연구에 기여할 수 있습니다.

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한계점:

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LLM 기반 접근 방식의 신뢰도 및 일반화 성능에 대한 추가 연구가 필요할 수 있습니다.

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데이터셋의 품질 평가에 사용된 참조 집합의 규모와 대표성에 대한 논의가 필요합니다.

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다양한 임상 설정 및 환자 인구에 대한 데이터셋의 일반화 성능에 대한 추가 검증이 필요합니다.

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