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.

DNN-Based Precoding in RIS-Aided mmWave MIMO Systems With Practical Phase Shift

Holistic Tokenizer for Autoregressive Image Generation

MAGIC: Mask-Guided Diffusion Inpainting with Multi-Level Perturbations and Context-Aware Alignment for Few-Shot Anomaly Generation

Order Acquisition Under Competitive Pressure: A Rapidly Adaptive Reinforcement Learning Approach for Ride-Hailing Subsidy Strategies

Towards a Playground to Democratize Experimentation and Benchmarking of AI Agents for Network Troubleshooting

AC-DiT: Adaptive Coordination Diffusion Transformer for Mobile Manipulation

GPU-based complete search for nonlinear minimization subject to bounds

Text Detoxification: Data Efficiency, Semantic Preservation and Model Generalization

On-Policy Optimization of ANFIS Policies Using Proximal Policy Optimization

Robotic Manipulation by Imitating Generated Videos Without Physical Demonstrations

LD-RPS: Zero-Shot Unified Image Restoration via Latent Diffusion Recurrent Posterior Sampling

Horus: A Protocol for Trustless Delegation Under Uncertainty

Visual Anagrams Reveal Hidden Differences in Holistic Shape Processing Across Vision Models

Diversity Conscious Refined Random Forest

GLU Attention Improve Transformer

Implicit Reward as the Bridge: A Unified View of SFT and DPO Connections

CRISP-SAM2: SAM2 with Cross-Modal Interaction and Semantic Prompting for Multi-Organ Segmentation

Treatment, evidence, imitation, and chat

EFRame: Deeper Reasoning via Exploration-Filter-Replay Reinforcement Learning Framework

Towards Understanding the Cognitive Habits of Large Reasoning Models

SEAL: Vision-Language Model-Based Safe End-to-End Cooperative Autonomous Driving with Adaptive Long-Tail Modeling

Inside you are many wolves: Using cognitive models to interpret value trade-offs in LLMs

AI and Agile Software Development: From Frustration to Success -- XP2025 Workshop Summary

Position: Machine Learning Conferences Should Establish a "Refutations and Critiques" Track

Why Do Open-Source LLMs Struggle with Data Analysis? A Systematic Empirical Study

NOVA: Navigation via Object-Centric Visual Autonomy for High-Speed Target Tracking in Unstructured GPS-Denied Environments

Comparative Evaluation of ChatGPT and DeepSeek Across Key NLP Tasks: Strengths, Weaknesses, and Domain-Specific Performance

RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models

Human2LocoMan: Learning Versatile Quadrupedal Manipulation with Human Pretraining

Casper: Inferring Diverse Intents for Assistive Teleoperation with Vision Language Models

Discrete Diffusion in Large Language and Multimodal Models: A Survey

Robust Molecular Property Prediction via Densifying Scarce Labeled Data

LearnAlign: Reasoning Data Selection for Reinforcement Learning in Large Language Models Based on Improved Gradient Alignment

AutoMind: Adaptive Knowledgeable Agent for Automated Data Science

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Towards Practical Alzheimer's Disease Diagnosis: A Lightweight and Interpretable Spiking Neural Model

The Geometries of Truth Are Orthogonal Across Tasks

TrajFlow: Multi-modal Motion Prediction via Flow Matching

Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning

Making a Pipeline Production-Ready: Challenges and Lessons Learned in the Healthcare Domain

FinBERT2: A Specialized Bidirectional Encoder for Bridging the Gap in Finance-Specific Deployment of Large Language Models

Recommender systems, stigmergy, and the tyranny of popularity

HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion

SLAC: Simulation-Pretrained Latent Action Space for Whole-Body Real-World RL

RewardAnything: Generalizable Principle-Following Reward Models

BiMa: Towards Biases Mitigation for Text-Video Retrieval via Scene Element Guidance

A Quantum Information Theoretic Approach to Tractable Probabilistic Models

Playing with Transformer at 30+ FPS via Next-Frame Diffusion

SC-LoRA: Balancing Efficient Fine-tuning and Knowledge Preservation via Subspace-Constrained LoRA

Deep Retrieval at CheckThat! 2025: Identifying Scientific Papers from Implicit Social Media Mentions via Hybrid Retrieval and Re-Ranking

Extended Inductive Reasoning for Personalized Preference Inference from Behavioral Signals

Better Safe Than Sorry? Overreaction Problem of Vision Language Models in Visual Emergency Recognition

Adaptive Inference-Time Scaling via Cyclic Diffusion Search

Domain Adaptation of VLM for Soccer Video Understanding

Towards Universal Semantics With Large Language Models

ReviewInstruct: A Review-Driven Multi-Turn Conversations Generation Method for Large Language Models

An Exploration of Default Images in Text-to-Image Generation

Aggregating Concepts of Fairness and Accuracy in Prediction Algorithms

PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks

Enhancing Satellite Object Localization with Dilated Convolutions and Attention-aided Spatial Pooling

Explainable Coarse-to-Fine Ancient Manuscript Duplicates Discovery

Rewriting Pre-Training Data Boosts LLM Performance in Math and Code

The Role of Open-Source LLMs in Shaping the Future of GeoAI

EasyEdit2: An Easy-to-use Steering Framework for Editing Large Language Models

AI for the Open-World: the Learning Principles

Towards Explainable Fusion and Balanced Learning in Multimodal Sentiment Analysis

TerraMind: Large-Scale Generative Multimodality for Earth Observation

NativQA Framework: Enabling LLMs with Native, Local, and Everyday Knowledge

Breach in the Shield: Unveiling the Vulnerabilities of Large Language Models

Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical Systems

Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward

EAP4EMSIG -- Enhancing Event-Driven Microscopy for Microfluidic Single-Cell Analysis

UNITYAI-GUARD: Pioneering Toxicity Detection Across Low-Resource Indian Languages

CMD-HAR: Cross-Modal Disentanglement for Wearable Human Activity Recognition

Construction Identification and Disambiguation Using BERT: A Case Study of NPN

PVChat: Personalized Video Chat with One-Shot Learning

Neural Discrete Token Representation Learning for Extreme Token Reduction in Video Large Language Models

MASS: Mathematical Data Selection via Skill Graphs for Pretraining Large Language Models

Long Context Modeling with Ranked Memory-Augmented Retrieval

Probing Latent Subspaces in LLM for AI Security: Identifying and Manipulating Adversarial States

Language Models can Self-Improve at State-Value Estimation for Better Search

Offline RLAIF: Piloting VLM Feedback for RL via SFO

Integrating Biological and Machine Intelligence: Attention Mechanisms in Brain-Computer Interfaces

Graded Neural Networks

Do LLMs Understand the Safety of Their Inputs? Training-Free Moderation via Latent Prototypes

FairFare: A Tool for Crowdsourcing Rideshare Data to Empower Labor Organizers

Federated Continual Learning: Concepts, Challenges, and Solutions

UniForm: A Unified Multi-Task Diffusion Transformer for Audio-Video Generation

Code Simulation as a Proxy for High-order Tasks in Large Language Models

An Efficient Local Search Approach for Polarized Community Discovery in Signed Networks

Learning Traffic Anomalies from Generative Models on Real-Time Observations

Explainable AI for Mental Health Emergency Returns: Integrating LLMs with Predictive Modeling

In-Context Meta LoRA Generation

Rethinking Table Instruction Tuning

Autonomous Microscopy Experiments through Large Language Model Agents

Static Segmentation by Tracking: A Label-Efficient Approach for Fine-Grained Specimen Image Segmentation

Random weights of DNNs and emergence of fixed points

On the Expressiveness and Length Generalization of Selective State-Space Models on Regular Languages

Mask Approximation Net: A Novel Diffusion Model Approach for Remote Sensing Change Captioning

Enhancing Long Video Generation Consistency without Tuning

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 과제를 포함합니다. 측면 추출은 감정 예측의 기반을 형성하며, 효과적인 교차 과제 지식 전이를 위해 두 과제 간의 중요한 의존성을 강조합니다. 기존 연구의 대부분은 잠재 공간에서 과제별 특징을 정렬하기 위해 다중 과제 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 단순화는 감정을 구분하는 상황적 단서를 무시하여 부정적인 전이로 이어집니다. 이러한 한계를 극복하기 위해, 본 논문에서는 TSA에 맞춘 세분화된 교차 과제 지식 전이 프레임워크인 FCKT를 제안합니다. FCKT는 측면 수준 정보를 감정 예측에 명시적으로 통합함으로써 세분화된 지식 전이를 달성하고, 부정적인 전이를 효과적으로 완화하며 과제 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 확인할 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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목표 지향적 감정 분석(TSA)에서 측면 추출과 감정 예측 간의 상호 의존성을 명확히 제시하고, 이를 바탕으로 효과적인 교차 과제 지식 전이 방법을 제시합니다.

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기존의 조잡한 지식 전이 방식의 한계를 극복하고, 측면-감정 관계에 대한 세분화된 제어를 가능하게 하는 FCKT 프레임워크를 제안합니다.

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다양한 데이터셋과 기준 모델들에 대한 실험을 통해 FCKT의 우수성을 검증합니다.

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공개된 소스 코드를 통해 재현성을 확보합니다.

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한계점:

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제안된 FCKT 프레임워크의 성능 향상이 특정 데이터셋에 국한될 가능성이 있습니다. 다양한 도메인 및 언어에 대한 추가적인 실험이 필요합니다.

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FCKT의 복잡성 및 계산 비용에 대한 분석이 부족합니다. 더욱 효율적인 구현 방안에 대한 연구가 필요할 수 있습니다.

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특정 측면에 대한 감정의 다양성을 완벽하게 포착하지 못할 수 있습니다. 더욱 정교한 측면-감정 상호작용 모델링이 필요할 수 있습니다.

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