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。
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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。

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

NLKI: A lightweight Natural Language Knowledge Integration Framework for Improving Small VLMs in Commons VQA Tasks

Interact-Custom: Customized Human Object Interaction Image Generation

A Self-Supervised Mixture-of-Experts Framework for Multi-behavior Recommendation

MIDAS: Multimodal Interactive Digital-humAn Synthesis via Real-time Autoregressive Video Generation

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

Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks

STDiff: A State Transition Diffusion Framework for Time Series Imputation in Industrial Systems

LLMs Can't Handle Peer Pressure: Crumbling under Multi-Agent Social Interactions

Graph-R1: Incentivizing the Zero-Shot Graph Learning Capability in LLMs via Explicit Reasoning

Modality-Specific Speech Enhancement and Noise-Adaptive Fusion for Acoustic and Body-Conduction Microphone Framework

Humans Perceive Wrong Narratives from AI Reasoning Texts

SpecVLM: Enhancing Speculative Decoding of Video LLMs via Verifier-Guided Token Pruning

Pareto Actor-Critic for Communication and Computation Co-Optimization in Non-Cooperative Federated Learning Services

Learning to Drive Ethically: Embedding Moral Reasoning into Autonomous Driving

Generative AI Against Poaching: Latent Composite Flow Matching for Wildlife Conservation

Privacy-Aware Detection of Fake Identity Documents: Methodology, Benchmark, and Improved Algorithms (FakeIDet2)

Beyond the Rosetta Stone: Unification Forces in Generalization Dynamics

Steering Towards Fairness: Mitigating Political Bias in LLMs

Dynamic Context Compression for Efficient RAG

Irredundant $k$-Fold Cross-Validation

Prompt Engineering and the Effectiveness of Large Language Models in Enhancing Human Productivity

A Highly Clean Recipe Dataset with Ingredient States Annotation for State Probing Task

Entropy-Memorization Law: Evaluating Memorization Difficulty of Data in LLMs

The Joys of Categorical Conformal Prediction

Adversarial Manipulation of Reasoning Models using Internal Representations

Agent-to-Agent Theory of Mind: Testing Interlocutor Awareness among Large Language Models

A Hybrid Artificial Intelligence Method for Estimating Flicker in Power Systems (Changes are marked)

GLProtein: Global-and-Local Structure Aware Protein Representation Learning

Program Semantic Inequivalence Game with Large Language Models

DSO: Aligning 3D Generators with Simulation Feedback for Physical Soundness

Improving Quantization with Post-Training Model Expansion

Safe and Efficient Social Navigation through Explainable Safety Regions Based on Topological Features

A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing

Federated nnU-Net for Privacy-Preserving Medical Image Segmentation

ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation

Enhancing Automated Loop Invariant Generation for Complex Programs with Large Language Models

RevPRAG: Revealing Poisoning Attacks in Retrieval-Augmented Generation through LLM Activation Analysis

Categorical Data Clustering via Value Order Estimated Distance Metric Learning

Application of AI to formal methods - an analysis of current trends

Reconsidering the Performance of GAE in Link Prediction

See then Tell: Enhancing Key Information Extraction with Vision Grounding

Enhancing Natural Language Inference Performance with Knowledge Graph for COVID-19 Automated Fact-Checking in Indonesian Language

Puppet-Master: Scaling Interactive Video Generation as a Motion Prior for Part-Level Dynamics

FFHFlow: Diverse and Uncertainty-Aware Dexterous Grasp Generation via Flow Variational Inference

SoAy: A Solution-based LLM API-using Methodology for Academic Information Seeking

Investigating the Robustness of Counterfactual Learning to Rank Models: A Reproducibility Study

Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off

Network Formation and Dynamics Among Multi-LLMs

NetGPT: Generative Pretrained Transformer for Network Traffic

OLKAVS: An Open Large-Scale Korean Audio-Visual Speech Dataset

Explainability of Text Processing and Retrieval Methods: A Survey

The Ramon Llull's Thinking Machine for Automated Ideation

RLMR: Reinforcement Learning with Mixed Rewards for Creative Writing

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

MSARL: Decoupling Reasoning and Tool Use with Multi-Small-Agent Reinforcement Learning

Automated Algorithmic Discovery for Gravitational-Wave Detection Guided by LLM-Informed Evolutionary Monte Carlo Tree Search

Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess

Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground

Possible Principles for Aligned Structure Learning Agents

OptiMUS-0.3: Using Large Language Models to Model and Solve Optimization Problems at Scale

Prompt-to-Product: Generative Assembly via Bimanual Manipulation

OnGoal: Tracking and Visualizing Conversational Goals in Multi-Turn Dialogue with Large Language Models

Mixture of Contexts for Long Video Generation

FakeParts: a New Family of AI-Generated DeepFakes

Enabling Equitable Access to Trustworthy Financial Reasoning

Veritas: Generalizable Deepfake Detection via Pattern-Aware Reasoning

Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop

Inference-Time Alignment Control for Diffusion Models with Reinforcement Learning Guidance

ChainReaction! Structured Approach with Causal Chains as Intermediate Representations for Improved and Explainable Causal Video Question Answering

Train-Once Plan-Anywhere Kinodynamic Motion Planning via Diffusion Trees

ExpertSim: Fast Particle Detector Simulation Using Mixture-of-Generative-Experts

WoW-Bench: Evaluating Fine-Grained Acoustic Perception in Audio-Language Models via Marine Mammal Vocalizations

ProactiveEval: A Unified Evaluation Framework for Proactive Dialogue Agents

Research Challenges in Relational Database Management Systems for LLM Queries

Quantum Verifiable Rewards for Post-Training Qiskit Code Assistant

AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning

JADES: A Universal Framework for Jailbreak Assessment via Decompositional Scoring

Learning Primitive Embodied World Models: Towards Scalable Robotic Learning

Multi-Agent Penetration Testing AI for the Web

Uncertainty Aware-Predictive Control Barrier Functions: Safer Human Robot Interaction through Probabilistic Motion Forecasting

Exploring Machine Learning and Language Models for Multimodal Depression Detection

Speech Emotion Recognition via Entropy-Aware Score Selection

Surfel-based 3D Registration with Equivariant SE(3) Features

Evaluating Compositional Generalisation in VLMs and Diffusion Models

Safer Skin Lesion Classification with Global Class Activation Probability Map Evaluation and SafeML

Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI

Signs of Struggle: Spotting Cognitive Distortions across Language and Register

Turning the Spell Around: Lightweight Alignment Amplification via Rank-One Safety Injection

Looking Beyond the Obvious: A Survey on Abstract Concept Recognition for Video Understanding

SKGE-SWIN: End-To-End Autonomous Vehicle Waypoint Prediction and Navigation Using Skip Stage Swin Transformer

Occlusion Robustness of CLIP for Military Vehicle Classification

SeqVLM: Proposal-Guided Multi-View Sequences Reasoning via VLM for Zero-Shot 3D Visual Grounding

Provable Benefits of In-Tool Learning for Large Language Models

${C}^{3}$-GS: Learning Context-aware, Cross-dimension, Cross-scale Feature for Generalizable Gaussian Splatting

Rethinking Testing for LLM Applications: Characteristics, Challenges, and a Lightweight Interaction Protocol

EEGDM: Learning EEG Representation with Latent Diffusion Model

Generative Annotation for ASR Named Entity Correction

MobileCLIP2: Improving Multi-Modal Reinforced Training

Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning

Possible Principles for Aligned Structure Learning Agents

Created by

Haebom

作者

Lancelot Da Costa, Tom a\v{s} Gaven\v{c}iak, David Hyland, Mandana Samiei, Cristian Dragos-Manta, Candice Pattisapu, Adeel Razi, Karl Friston

概要

本論文では、自然知能の基本原理の説明に基づいて、拡張可能で整列した人工知能（AI）開発のためのロードマップを紹介します。スケーラブルなソートされたAIへの可能なルートは、人工エージェントが私たちの好みを含む世界の良いモデルを学ぶことを可能にすることです。この目的のための主な目的は、世界と他のエージェントの世界モデルを表す方法を学習するエージェントを作成することです。これは、構造学習（別名因果表現学習またはモデル発見）に属する問題です。この論文では、これらの目標を念頭に置いて、構造学習と整列の問題とともに私たちを前進させる原則を提示し、数学、統計、認知科学全体のさまざまなアイデアをまとめます。 1）重要な知識、情報幾何学、およびモデルの縮小が構造学習における重要な役割を議論し、広範な自然世界を学習するためのコア構造モジュールを提案します。 2）構造学習と心理論を介してソートされたエージェントに向かう方法を概略的に説明します。例として、他のエージェントの不幸を最小限に抑えるために慎重に行動するように規定するアシモフのロボット工学の3原則を数学的に概略的に説明します。さらに、ソートへの改善されたアプローチを提案して、この例を補完します。これらの観察は、既存の整列構造学習システムを拡張したり、新しいシステムを設計したりするのに役立つ人工知能を開発するためのガイドラインになる可能性があります。

Takeaways、Limitations

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Takeaways：自然知能に基づいたスケーラブルなソートされたAI開発のためのロードマップ提示、構造学習、心理論によるソートされたエージェント開発スキームの提示、アシモフのロボット工学の3原則を数学的にモデル化し、改善されたソート方式を提案する。コア知識、情報幾何学、モデル縮小の重要性を強調する。

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Limitations：提示されたロードマップはまだ理論的なステップであり、実際の実装と検証が必要です。アシモフのロボット工学の3原則を単純化された例として使用して、実際の複雑な状況への適用可能性に関するさらなる研究が必要です。具体的な構造学習アルゴリズムとシステム設計の詳細な説明の欠如様々な世界モデルと好みを効果的に表現し学習する方法に関するさらなる研究の必要性

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