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.

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

OpenS2V-Nexus: A Detailed Benchmark and Million-Scale Dataset for Subject-to-Video Generation

Created by

Haebom

저자

Shenghai Yuan, Xianyi He, Yufan Deng, Yang Ye, Jinfa Huang, Bin Lin, Jiebo Luo, Li Yuan

개요

본 논문은 주어진 내용을 충실히 반영하는 비디오 생성을 목표로 하는 Subject-to-Video (S2V) 생성을 위한 기반 시설인 OpenS2V-Nexus를 제안합니다. OpenS2V-Nexus는 세분화된 벤치마크인 OpenS2V-Eval과 백만 스케일 데이터셋인 OpenS2V-5M으로 구성됩니다. 기존의 전역적이고 조잡한 비디오 평가에 초점을 맞춘 VBench에서 상속받은 S2V 벤치마크와 달리, OpenS2V-Eval은 자연스러운 피사체 외양과 정체성 충실도를 가진 피사체 일관성 있는 비디오를 생성하는 모델의 능력에 중점을 둡니다. 이를 위해 OpenS2V-Eval은 실제 및 합성 테스트 데이터를 포함하는 7가지 주요 S2V 범주에서 180개의 프롬프트를 도입합니다. 또한, 인간의 선호도를 S2V 벤치마크와 정확하게 정렬하기 위해 생성된 비디오에서 피사체 일관성, 자연스러움 및 텍스트 관련성을 개별적으로 정량화하는 세 가지 자동 지표인 NexusScore, NaturalScore 및 GmeScore를 제안합니다. 이를 바탕으로 16개의 대표적인 S2V 모델에 대한 종합적인 평가를 수행하여 다양한 콘텐츠에서 각 모델의 강점과 약점을 강조합니다. 더불어, 5백만 개의 고품질 720P 피사체-텍스트-비디오 트리플로 구성된 최초의 오픈소스 대규모 S2V 생성 데이터셋인 OpenS2V-5M을 생성합니다. 특히, (1) 피사체를 분할하고 비디오 간 연관을 통해 짝 정보를 구축하고 (2) 원시 프레임에 GPT-Image-1을 프롬프트하여 다중 뷰 표현을 합성함으로써 데이터셋에서 피사체 정보 다양성을 보장합니다. OpenS2V-Nexus를 통해 향후 S2V 생성 연구를 가속화하는 강력한 기반 시설을 제공합니다.

시사점, 한계점

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시사점:

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S2V 생성 연구를 위한 세분화된 벤치마크(OpenS2V-Eval)와 대규모 데이터셋(OpenS2V-5M) 제공으로 연구 가속화.

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피사체 일관성, 자연스러움, 텍스트 관련성을 정량화하는 자동 지표(NexusScore, NaturalScore, GmeScore) 제시.

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16개 S2V 모델의 종합적 평가를 통해 각 모델의 강점과 약점 분석 가능.

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오픈소스로 제공되어 S2V 연구의 접근성 향상.

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한계점:

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제안된 지표의 객관성 및 일반화 가능성에 대한 추가 연구 필요.

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데이터셋의 편향성 및 다양성에 대한 추가적인 검토 필요.

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실제 사용자 피드백을 반영한 평가 방식 고려 필요.

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특정 모델이나 데이터셋에 대한 과도한 의존성 가능성.

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