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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。

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

Integrating Large Language Model for Improved Causal Discovery

Created by

Haebom

作者

Taiyu Ban, Lyuzhou Chen, Derui Lyu, Xiangyu Wang, Qinrui Zhu, Qiang Tu, Huanhuan Chen

概要

本論文は,観測データから因果グラフモデルの構造を回復する過程が科学的シナリオにおける因果的発見に不可欠であるが困難な課題であることを扱う。既存のドメイン固有の因果発見は、専門家の検証または事前分析に依存して信頼性を高めますが、専門家の資源の不足により制限があります。この論文は、大規模言語モデル（LLM）を活用してデータインフラストラクチャの学習を導く自律的な専門家の役割を果たす可能性を提供します。しかし、LLMベースの推論の不正確さのために、LLMを因果発見に統合することは困難です。これを解決するために、エラー許容LLMベースの因果発見フレームワークを提案します。エラー許容メカニズムは、潜在的な不正確さを十分に考慮して3つの側面で設計されています。 LLMベースの推論プロセスでは、精度中心プロンプト戦略は因果分析を信頼できる範囲に制限します。次に、知識構造変換は、LLMから導出された因果的声明を構造的因果的相互作用と整列させます。構造学習の過程で、データへの適合度とLLMから導出された辞書情報の遵守をバランスよく考慮して、辞書情報の不正確さを解決します。 8つの実際の因果構造の評価は、提案されたLLMベースのアプローチがデータベースの因果発見を改善し、不正確なLLMベースの事前情報の堅牢性を示しています。コードはhttps://github.com/tyMadara/LLM-CDで確認できます。

GitHub - tyMadara/LLM-CD

Contribute to tyMadara/LLM-CD development by creating an account on GitHub.

Takeaways、Limitations

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Takeaways： LLMを利用したエラー許容因果発見フレームワークを提示し、データ駆動型因果発見の精度と効率を向上させました。実際のデータセットを通じて、提案された方法の効果と堅牢性を検証しました。

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Limitations：提案されたフレームワークのパフォーマンスはLLMのパフォーマンスに依存し、LLMの誤った推論が依然としてエラーを引き起こす可能性があります。様々なドメインと複雑な因果構造の一般化性能に関するさらなる研究が必要である。使用されるLLMの種類とサイズによっては、パフォーマンスの違いが発生する可能性があります。

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