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Daily Arxiv
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。
CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics
Ada-TransGNN: An Air Quality Prediction Model Based On Adaptive Graph Convolutional Networks
Unlearning as Ablation: Toward a Falsifiable Benchmark for Generative Scientific Discovery
Consistent Opponent Modeling of Static Opponents in Imperfect-Information Games
Finding Outliers in a Haystack: Anomaly Detection for Large Pointcloud Scenes
Agentic AI for Software: thoughts from Software Engineering community
Mind the (Language) Gap: Towards Probing Numerical and Cross-Lingual Limits of LVLMs
Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning
Dream to Chat: Model-based Reinforcement Learning on Dialogues with User Belief Modeling
A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems
Generative Artificial Intelligence and Agents in Research and Teaching
CALR: Corrective Adaptive Low-Rank Decomposition for Efficient Large Language Model Layer Compression
Comparative Analysis of UAV Path Planning Algorithms for Efficient Navigation in Urban 3D Environments
Retrieval Enhanced Feedback via In-context Neural Error-book
From Confidence to Collapse in LLM Factual Robustness
On Task Vectors and Gradients
Learning in Repeated Multi-Objective Stackelberg Games with Payoff Manipulation
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model
DLLMQuant: Quantizing Diffusion-based Large Language Models
LLM-Enhanced Linear Autoencoders for Recommendation
Leveraging GNN to Enhance MEF Method in Predicting ENSO
Uncertainty-Guided Face Matting for Occlusion-Aware Face Transformation
New Kid in the Classroom: Exploring Student Perceptions of AI Coding Assistants
Large Language Model-Based Framework for Explainable Cyberattack Detection in Automatic Generation Control Systems
SKA-Bench: A Fine-Grained Benchmark for Evaluating Structured Knowledge Understanding of LLMs
Apple Intelligence Foundation Language Models: Tech Report 2025
SE-VLN: A Self-Evolving Vision-Language Navigation Framework Based on Multimodal Large Language Models
Demographic-aware fine-grained classification of pediatric wrist fractures
Krul: Efficient State Restoration for Multi-turn Conversations with Dynamic Cross-layer KV Sharing
Solar Altitude Guided Scene Illumination
An Agentic System for Rare Disease Diagnosis with Traceable Reasoning
Spectra-to-Structure and Structure-to-Spectra Inference Across the Periodic Table
UAD: Unsupervised Affordance Distillation for Generalization in Robotic Manipulation
Debate-to-Detect: Reformulating Misinformation Detection as a Real-World Debate with Large Language Models
EVM-Fusion: An Explainable Vision Mamba Architecture with Neural Algorithmic Fusion
RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection
Revisiting SSL for sound event detection: complementary fusion and adaptive post-processing
Concept-Guided Interpretability via Neural Chunking
Unveiling the Landscape of LLM Deployment in the Wild: An Empirical Study
An Ontology-Driven Graph RAG for Legal Norms: A Hierarchical, Temporal, and Deterministic Approach
Prefill-level Jailbreak: A Black-Box Risk Analysis of Large Language Models
Video CLIP Model for Multi-View Echocardiography Interpretation
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Disease Detection from Retinal Fundus Images
M$^2$IV: Towards Efficient and Fine-grained Multimodal In-Context Learning via Representation Engineering
Noise-based reward-modulated learning
Faster Parameter-Efficient Tuning with Token Redundancy Reduction
UniGenX: a unified generative foundation model that couples sequence, structure and function to accelerate scientific design across proteins, molecules and materials
Collaborative Evaluation of Deepfake Text with Deliberation-Enhancing Dialogue Systems
Large Language Models Badly Generalize across Option Length, Problem Types, and Irrelevant Noun Replacements
TableTalk: Scaffolding Spreadsheet Development with a Language Agent
StagFormer: Time Staggering Transformer Decoding for RunningLayers In Parallel
Provably-Safe Neural Network Training Using Hybrid Zonotope Reachability Analysis
Generative Artificial Intelligence-Supported Pentesting: A Comparison between Claude Opus, GPT-4, and Copilot
Safe Multiagent Coordination via Entropic Exploration
TL-Training: A Task-Feature-Based Framework for Training Large Language Models in Tool Use
Cultural Dimensions of AI Perception: Charting Expectations, Risks, Benefits, Tradeoffs, and Value in Germany and China
CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers
Perception Gaps in Risk, Benefit, and Value Between Experts and Public Challenge Socially Accepted AI
Hierarchical Object-Oriented POMDP Planning for Object Rearrangement
From Intents to Conversations: Generating Intent-Driven Dialogues with Contrastive Learning for Multi-Turn Classification
Secure Reinforcement Learning via Shuffle Privacy Model
Overcoming label shift with target-aware federated learning
Benchmarking XAI Explanations with Human-Aligned Evaluations
HonestCyberEval: An AI Cyber Risk Benchmark for Automated Software Exploitation
Leveraging Multi-facet Paths for Heterogeneous Graph Representation Learning
GeNet: A Multimodal LLM-Based Co-Pilot for Network Topology and Configuration
ChatGPT Doesn't Trust Chargers Fans: Guardrail Sensitivity in Context
Ego-Foresight: Self-supervised Learning of Agent-Aware Representations for Improved RL
Exploring the Robustness of Language Models for Tabular Question Answering via Attention Analysis
Learning county from pixels: corn yield prediction with attention-weighted multiple instance learning
Memory augment is All You Need for image restoration
Rethinking Distribution Shifts: Empirical Analysis and Inductive Modeling for Tabular Data
DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models
Beyond Discriminant Patterns: On the Robustness of Decision Rule Ensembles
Bayesian Deep Learning for Segmentation for Autonomous Safe Planetary Landing
ST-Raptor: LLM-Powered Semi-Structured Table Question Answering
Route-and-Execute: Auditable Model-Card Matching and Specialty-Level Deployment
LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence
Response and Prompt Evaluation to Prevent Parasocial Relationships with Chatbots
Profile-Aware Maneuvering: A Dynamic Multi-Agent System for Robust GAIA Problem Solving by AWorld
Multi-Agent LLMs as Ethics Advocates for AI-Based Systems
Feature-Guided Neighbor Selection for Non-Expert Evaluation of Model Predictions
Architecting Clinical Collaboration: Multi-Agent Reasoning Systems for Multimodal Medical VQA
MRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation
Jigsaw-Puzzles: From Seeing to Understanding to Reasoning in Vision-Language Models
The Influence of Human-inspired Agentic Sophistication in LLM-driven Strategic Reasoners
YuLan-OneSim: Towards the Next Generation of Social Simulator with Large Language Models
Consensus in Motion: A Case of Dynamic Rationality of Sequential Learning in Probability Aggregation
Can Large Language Models Act as Ensembler for Multi-GNNs?
Pessimistic Iterative Planning with RNNs for Robust POMDPs
Safe Reinforcement Learning in Black-Box Environments via Adaptive Shielding
Integrating Large Language Model for Improved Causal Discovery
A Survey on Causal Discovery: Theory and Practice
Generative Interfaces for Language Models
Interpolating Speaker Identities in Embedding Space for Data Expansion
VibeVoice Technical Report
LSD-3D: Large-Scale 3D Driving Scene Generation with Geometry Grounding
Understanding Tool-Integrated Reasoning
Emotions as Ambiguity-aware Ordinal Representations
Real-Time Model Checking for Closed-Loop Robot Reactive Planning
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Dream to Chat: Model-based Reinforcement Learning on Dialogues with User Belief Modeling
Created by
Haebom
作者
Yue Zhao, Xiaoyu Wang, Dan Wang, Zhonglin Jiang, Qingqing Gu, Teng Chen, Ningyuan Xi, Jinxian Qu, Yong Chen, Luo Ji
概要
本論文は、ロボティクス、ゲーム、自律走行などで広く活用されているワールドモデルを自然言語処理、特に対話システムに適用した研究です。会話ワールドモデルを構築し、ユーザーの感情、感情、意図、そして将来の発話を予測することを目指します。 POMDP(Partially Observable Markov Decision Process)を定義して、感情、感情、意図をユーザーの信念としてモデル化し、情報のボトルネックを最大化して解決する方法を提案します。これらのユーザー信念モデリングに基づいて、モデルベースの強化学習フレームワークを会話システムに適用して、DreamCUBという新しいフレームワークを提示します。実験の結果、事前訓練された会話ワールドモデルは、感情の分類と感情の識別で最先端のパフォーマンスを達成し、政策、批評家、会話ワールドモデルの組み合わせ訓練によって会話の品質も向上しました。さらなる分析は、提案された方法が適切なナビゲーション - 活用バランスを維持し、共感会話などのドメイン外シナリオへの遷移性能も優れていることを示しています。
Takeaways、Limitations
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Takeaways:
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会話システムにワールドモデルを適用し、ユーザーの感情、感情、意図を効果的に予測しモデリングできる新しいフレームワーク(DreamCUB)を提示。
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感情分類と感情識別における最先端のパフォーマンスを達成
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会話品質の向上とナビゲーション - 活用の適切なバランスを維持します。
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ドメイン外シナリオへの優れた遷移性能
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Limitations:
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この論文で提示されているDreamCUBフレームワークの実際の実装とスケーラビリティの詳細は不足しています。
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さまざまな会話タイプと規模の一般化パフォーマンスの追加検証が必要です。
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POMDPベースのユーザ信念モデリングの限界と改善の方向性に関する議論の欠如
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情報ボトルネック最大化戦略の具体的なアルゴリズムとパラメータ設定の詳細な説明の欠如
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