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

Generative Framework for Personalized Persuasion: Inferring Causal, Counterfactual, and Latent Knowledge

Created by

Haebom

저자

Donghuo Zeng, Roberto Legaspi, Yuewen Sun, Xinshuai Dong, Kazushi Ikeda, Peter Spirtes, Kun Zhang

개요

본 논문은 최적의 시스템 반응이 인과 및 반실제적 지식에 기반한 적응적 전략에서 나온다는 가설을 제시합니다. 반실제 추론을 통해 가상 시나리오를 생성하여 대안적인 시스템 반응의 효과를 검토하고, 인과적 발견을 통해 시스템 동작을 지배하는 기저 인과 구조에 의해 알려진 전략을 식별하여 이 과정을 향상시킵니다. 또한 사용자-시스템 상호 작용에 영향을 미칠 수 있는 심리적 구성 요소와 관찰 불가능한 노이즈를 잠재 요인으로 고려하여 효과적으로 추정하는 방법을 제시합니다. 인과적 발견을 사용하여 사용자 및 시스템 발화 간의 전략 수준 인과 관계를 식별하고, 개인화된 반실제 대화 생성을 안내합니다. 사용자 발화 전략을 인과적 요인으로 모델링하여 시스템 전략을 반실제적 행동으로 취급할 수 있도록 합니다. 또한 반실제 데이터를 기반으로 시스템 반응 선택 정책을 최적화합니다. 사회적 선(social good)에 대한 실제 데이터 세트를 사용한 결과, 설득력 있는 시스템 결과가 크게 향상되었으며, 누적 보상이 증가하여 인과적 발견이 개인화된 반실제 추론을 안내하고 설득력 있는 대화 시스템의 대화 정책을 최적화하는 데 효과적임을 확인했습니다.

시사점, 한계점

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시사점:

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인과적 발견과 반실제 추론을 결합하여 설득력 있는 대화 시스템의 성능을 향상시킬 수 있음을 보여줍니다.

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개인화된 반실제 대화 생성을 통해 사용자에게 최적화된 시스템 반응을 제공할 수 있습니다.

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실제 데이터 세트를 사용한 실험 결과를 통해 제안된 방법의 효과성을 검증했습니다.

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사용자-시스템 상호 작용에 대한 심리적 요인과 노이즈를 고려하여 모델의 현실성을 높였습니다.

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한계점:

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사용된 데이터 세트의 특성에 따라 일반화 성능이 제한될 수 있습니다.

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잠재 요인의 추정 및 모델링에 대한 자세한 설명이 부족할 수 있습니다.

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다른 유형의 대화 시스템에 대한 적용 가능성 및 일반화 가능성에 대한 추가 연구가 필요합니다.

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인과적 발견 과정의 복잡성 및 계산 비용에 대한 논의가 필요합니다.

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