Daily Arxiv

世界中で発行される人工知能関連の論文をまとめるページです。
このページはGoogle Geminiを活用して要約し、非営利で運営しています。
論文の著作権は著者および関連機関にあり、共有する際は出典を明記してください。

Emotions as Ambiguity-aware Ordinal Representations

From Tabula Rasa to Emergent Abilities: Discovering Robot Skills via Real-World Unsupervised Quality-Diversity

Enhancing Model Privacy in Federated Learning with Random Masking and Quantization

Scaling Laws for Task-Stratified Knowledge in Post-Training Quantized Large Language Models

Principled Detection of Hallucinations in Large Language Models via Multiple Testing

Vocoder-Projected Feature Discriminator

ControlEchoSynth: Boosting Ejection Fraction Estimation Models via Controlled Video Diffusion

Explain Before You Answer: A Survey on Compositional Visual Reasoning

Time-Aware One Step Diffusion Network for Real-World Image Super-Resolution

PediatricsMQA: a Multi-modal Pediatrics Question Answering Benchmark

VideoEraser: Concept Erasure in Text-to-Video Diffusion Models

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives

GeoSAM2: Unleashing the Power of SAM2 for 3D Part Segmentation

Input-Time Scaling

LinguaSafe: A Comprehensive Multilingual Safety Benchmark for Large Language Models

A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models

StreetViewAI: Making Street View Accessible Using Context-Aware Multimodal AI

Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs

From Imitation to Optimization: A Comparative Study of Offline Learning for Autonomous Driving

R-Zero: Self-Evolving Reasoning LLM from Zero Data

Human-Centered Human-AI Interaction (HC-HAII): A Human-Centered AI パースペクティブ

GTPO: Trajectory-Based Policy Optimization in Large Language Models

Contrastive Multi-Task Learning with Solvent-Aware Augmentation for Drug Discovery

A Large-Scale Benchmark of Cross-Modal Learning for Histology and Gene Expression in Spatial Transcriptomics

Invisible Architectures of Thought: Toward a New Science of AI as Cognitive Infrastructure

Revisiting Pre-trained Language Models for Vulnerability Detection

MegaScience: Pushing the Frontiers of Post-Training Datasets for Science Reasoning

Scaling Decentralized Learning with FLock

SegQuant: A Semantics-Aware and Generalizable Quantization Framework for Diffusion Models

Apple Intelligence Foundation Language Models: Tech Report 2025

Optimistic Exploration for Risk-Averse Constrained Reinforcement Learning

PyVision: Agentic Vision with Dynamic Tooling

DATABench: Evaluating Dataset Auditing in Deep Learning from an Adversarial Perspective

RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation

Analyzing Character Representation in Media Content using Multimodal Foundation Model: Effectiveness and Trust

MEraser: An Effective Fingerprint Erasure Approach for Large Language Models

CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval

DreamActor-H1: High-Fidelity Human-Product Demonstration Video Generation via Motion-designed Diffusion Transformers

Pseudo-Simulation for Autonomous Driving

BinConv: A Neural Architecture for Ordinal Encoding in Time-Series Forecasting

FaceEditTalker: Controllable Talking Head Generation with Facial Attribute Editing

EnvInjection: Environmental Prompt Injection Attack to Multi-modal Web Agents

X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Real

Heat Diffusion Models - Interpixel Attention Mechanism

Bidirectional Task-Motion Planning Based on Hierarchical Reinforcement Learning for Strategic Confrontation

Multi-Type Context-Aware Conversational Recommender Systems via Mixture-of-Experts

Pricing AI Model Accuracy

Evaluating the Fitness of Ontologies for the Task of Question Generation

Utility-Focused LLM Annotation for Retrieval and Retrieval-Augmented Generation

PGAD: Prototype-Guided Adaptive Distillation for Multi-Modal Learning in AD Diagnosis

Constructing a Norm for Children's Scientific Drawing: Distribution Features Based on Semantic Similarity of Large Language Models

An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model

Efficient PINNs via Multi-Head Unimodular Regularization of the Solutions Space

Statistical learning does not always entail knowledge

Score-based Generative Diffusion Models for Social Recommendations

PromptKeeper: Safeguarding System Prompts for LLMs

X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models

Understanding Fairness-Accuracy Trade-offs in Machine Learning Models: Does Promoting Fairness Undermine Performance?

GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language モデル

Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning

Training with Explanations Alone: A New Paradigm to Prevent Shortcut Learning

Generation of Geodesics with Actor-Critic Reinforcement Learning to Predict Midpoints

TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes

HoneyBee: A Scalable Modular Framework for Creating Multimodal Oncology Datasets with Foundational Embedding Models

StepWiser: Stepwise Generative Judges for Wiser Reasoning

AniME: Adaptive Multi-Agent Planning for Long Animation Generation

AppAgent-Pro: A Proactive GUI Agent System for Multidomain Information Integration and User Assistance

AI Chaperones Are (Really) All You Need to Prevent Parasocial Relationships with Chatbots

Nemori: Self-Organizing Agent Memory Inspired by Cognitive Science

General agents contain world models

Approximate Lifted Model Construction

Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search

Synthesizing High-Quality Programming Tasks with LLM-based Expert and Student Agents

Preference Elicitation for Multi-objective Combinatorial Optimization with Active Learning and Maximum Likelihood Estimation

Reference-Aligned Retrieval-Augmented Question Answering over Heterogeneous Proprietary Documents

Demonstrating specification gaming in reasoning models

AirRAG: Autonomous Strategic Planning and Reasoning Steer Retrieval Augmented Generation

Think Smart、Act SMARL！ Analyzing Probabilistic Logic Shields for Multi-Agent Reinforcement Learning

From Evidence to Decision: Exploring Evaluative AI

CODA: Coordinating the Cerebrum and Cerebellum for a Dual-Brain Computer Use Agent with Decoupled Reinforcement Learning

Discrete-Guided Diffusion for Scalable and Safe Multi-Robot Motion Planning

Patch Progression Masked Autoencoder with Fusion CNN Network for Classifying Evolution Between Two Pairs of 2D OCT Slices

DeepScholar-Bench: A Live Benchmark and Automated Evaluation for Generative Research Synthesis

Large Language Models (LLMs) for Electronic Design Automation (EDA)

Symphony: A Decentralized Multi-Agent Framework for Scalable Collective Intelligence

HPC Digital Twins for Evaluating Scheduling Policies, Incentive Structures and their Impact on Power and Cooling

Decomposing Behavioral Phase Transitions in LLMs: Order Parameters for Emergent Misalignment

Cross-Platform E-Commerce Product Categorization and Recategorization: A Multimodal Hierarchical Classification Approach

Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation

MathBuddy: A Multimodal System for Affective Math Tutoring

Diffusion Language Models Know the Answer Before Decoding

GLSim: Detecting Object Hallucinations in LVLMs via Global-Local Similarity

Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation

WaveHiT-SR: Hierarchical Wavelet Network for Efficient Image Super-Resolution

The Next Layer: Augmenting Foundation Models with Structure-Preserving and Attention-Guided Learning for Local Patches to Global Context Awareness in Computational Pathology

Logical Reasoning with Outcome Reward Models for Test-Time Scaling

The Information Dynamics of Generative Diffusion

AI-Powered Detection of Inappropriate Language in Medical School Curricula

Generative AI for Testing of Autonomous Driving Systems: A Survey

Multispectral LiDAR data for extracting tree points in urban and suburban areas

Emotions as Ambiguity-aware Ordinal Representations

Created by

Haebom

作者

Jingyao Wu, Matthew Barthet, David Melhart, Georgios N. Yannakakis

概要

本論文は、感情認識の分野における感情の曖昧さと動的な特性を同時に考慮する新しい枠組みである「あいまいさ認識順序感情表現」を提案します。既存の研究が感情のあいまいさを無視したり静的変数として扱ったりするのとは異なり、本研究は感情のあいまいさを時間の経過とともに変化率でモデル化するアプローチを提案している。 RECOLAとGameVibeの2つの感情データセットを使用して、制限された（覚醒、Valence）および制限されていない（没入度の）継続的な感情追跡のための提案された方法を評価しました。その結果,順序感情表現は無限のラベルで従来の曖昧性認識モデルより優れた性能を示し,Concordance Correlation Coefficient(CCC)とSigned Differential Agreement(SDA)スコアで最高の性能を達成し,感情追跡のダイナミクスをモデル化するのに有効であることを示した。限られたラベルの場合、順序感情表現はSDAで優れた性能を示し、注釈付き感情追跡の相対的な変化を捉える能力が優れていることを示しています。

Takeaways、Limitations

•

Takeaways:

◦

感情のあいまいさと動的特性を同時に考慮する新しい感情認識フレームワークの提示

◦

順序感情表現が制限されていない感情ラベル（例えば、没入度）では、従来の方法より優れた性能を示す

◦

順序感情表現が制限された感情ラベル（例えば、覚醒、Valence）での相対的な変化捕捉能力に優れる

◦

感情データの曖昧さを効果的にモデル化する新しいアプローチの提示

•

Limitations:

◦

提案されたフレームワークの性能評価は、特定のデータセット（RECOLA、GameVibe）に限定されています。他のデータセットへの一般化可能性検証が必要

◦

さまざまな種類の感情の一般化の可能性に関するさらなる研究が必要

◦

感情のあいまいさを変化率でのみモデル化する限界。他の要因（個人差、状況要因など）を考慮したより包括的なモデルが必要

Made with Slashpage