Daily Arxiv

전 세계에서 발간되는 인공지능 관련 논문을 정리하는 페이지 입니다.
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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

FCKT: Fine-Grained Cross-Task Knowledge Transfer with Semantic Contrastive Learning for Targeted Sentiment Analysis

Created by

Haebom

저자

Wei Chen, Zhao Zhang, Meng Yuan, Kepeng Xu, Fuzhen Zhuang

개요

본 논문은 목표 지향적 감정 분석(TSA) 과제를 다룹니다. TSA는 리뷰에서 특정 측면을 식별하고 해당 감정을 결정하는 두 가지 하위 작업으로 구성됩니다. 측면 추출은 감정 예측의 기반을 형성하며, 효과적인 교차 작업 지식 전이를 위해 두 작업 간의 중요한 상호 의존성을 강조합니다. 기존 연구의 대부분은 잠재 공간에서 작업별 특징을 정렬하기 위해 다중 작업 학습 패러다임을 채택하지만, 주로 조잡한 지식 전이에 의존합니다. 이러한 접근 방식은 측면-감정 관계에 대한 세분화된 제어가 부족하며, 관련 측면 내에서 균일한 감정 극성을 가정하는 경우가 많습니다. 이러한 과도한 단순화는 감정을 구분하는 상황적 단서를 무시하여 부정적인 전이로 이어집니다. 이러한 한계를 극복하기 위해 본 논문에서는 TSA에 맞춤화된 세분화된 교차 작업 지식 전이 프레임워크인 FCKT를 제안합니다. FCKT는 측면 수준 정보를 감정 예측에 명시적으로 통합함으로써 세분화된 지식 전이를 달성하여 부정적인 전이를 효과적으로 완화하고 작업 성능을 향상시킵니다. 다양한 기준 및 대규모 언어 모델(LLM)과의 비교를 포함한 세 가지 데이터 세트에 대한 실험은 FCKT의 효과를 보여줍니다. 소스 코드는 https://github.com/cwei01/FCKT 에서 사용할 수 있습니다.

GitHub - cwei01/FCKT: FCKT

FCKT. Contribute to cwei01/FCKT development by creating an account on GitHub.

시사점, 한계점

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시사점:

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TSA에서 세분화된 교차 작업 지식 전이를 위한 새로운 프레임워크인 FCKT 제안.

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측면 수준 정보의 명시적 통합을 통해 부정적인 전이 완화 및 성능 향상.

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다양한 기준 및 LLM과의 비교 실험을 통해 FCKT의 효과성 입증.

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공개된 소스 코드를 통해 재현성 및 확장성 확보.

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한계점:

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제안된 FCKT의 일반화 성능에 대한 추가적인 연구 필요.

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다양한 데이터셋 및 작업에 대한 폭넓은 실험 필요.

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특정 측면과 감정의 상관관계를 더욱 정교하게 모델링하는 방안에 대한 추가 연구 필요.

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