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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。
Benchmarking LLM Causal Reasoning with Scientifically Validated Relationships
TIGeR: Tool-Integrated Geometric Reasoning in Vision-Language Models for Robotics
Mining the Mind: What 100M Beliefs Reveal About Frontier LLM Knowledge
Open ASR Leaderboard: Towards Reproducible and Transparent Multilingual and Long-Form Speech Recognition Evaluation
Emotionally Vulnerable Subtype of Internet Gaming Disorder: Measuring and Exploring the Pathology of Problematic Generative AI Use
Explaining raw data complexity to improve satellite onboard processing
Foundations of LLM Knowledge Materialization: Termination, Reproducibility, Robustness
Incremental Summarization for Customer Support via Progressive Note-Taking and Agent Feedback
SDAR: A Synergistic Diffusion-AutoRegression Paradigm for Scalable Sequence Generation
A Multimodal GUI Architecture for Interfacing with LLM-Based Conversational Assistants
Distributional Semantics Tracing: A Framework for Explaining Hallucinations in Large Language Models
DACP: Domain-Adaptive Continual Pre-Training of Large Language Models for Phone Conversation Summarization
High-Fidelity Synthetic ECG Generation via Mel-Spectrogram Informed Diffusion Training
Provable Speech Attributes Conversion via Latent Independence
Chronological Thinking in Full-Duplex Spoken Dialogue Language Models
Paper2Video: Automatic Video Generation from Scientific Papers
MacroBench: A Novel Testbed for Web Automation Scripts via Large Language Models
Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models
Generalized Orders of Magnitude for Scalable, Parallel, High-Dynamic-Range Computation
LogAction: Consistent Cross-system Anomaly Detection through Logs via Active Domain Adaptation
Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models
More Than One Teacher: Adaptive Multi-Guidance Policy Optimization for Diverse Exploration
Learning to Reason for Hallucination Span Detection
Panorama: Fast-Track Nearest Neighbors
Feature Identification via the Empirical NTK
OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction
Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning
Real-time Noise Detection and Classification in Single-Channel EEG: A Lightweight Machine Learning Approach for EMG, White Noise, and EOG Artifacts
The Sandbox Configurator: A Framework to Support Technical Assessment in AI Regulatory Sandboxes
CORE-3D: Context-aware Open-vocabulary Retrieval by Embeddings in 3D
PARL-MT: Learning to Call Functions in Multi-Turn Conversation with Progress Awareness
Defending MoE LLMs against Harmful Fine-Tuning via Safety Routing Alignment
Learn the Ropes, Then Trust the Wins: Self-imitation with Progressive Exploration for Agentic Reinforcement Learning
InfiR2: A Comprehensive FP8 Training Recipe for Reasoning-Enhanced Language Models
MORPH: Shape-agnostic PDE Foundation Models
Spiffy: Multiplying Diffusion LLM Acceleration via Lossless Speculative Decoding
Evaluating LLM-Generated Versus Human-Authored Responses in Role-Play Dialogues
Audio-Conditioned Diffusion LLMs for ASR and Deliberation Processing
Hierarchical Reinforcement Learning with Low-Level MPC for Multi-Agent Control
ProtoMedX: Towards Explainable Multi-Modal Prototype Learning for Bone Health Classification
From Correction to Mastery: Reinforced Distillation of Large Language Model Agents
Reproducible workflow for online AI in digital health
HiChunk: Evaluating and Enhancing Retrieval-Augmented Generation with Hierarchical Chunking
FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification
TalkPlayData 2: An Agentic Synthetic Data Pipeline for Multimodal Conversational Music Recommendation
A Survey of Reinforcement Learning for Large Reasoning Models
X-Teaming Evolutionary M2S: Automated Discovery of Multi-turn to Single-turn Jailbreak Templates
Barycentric Neural Networks and Length-Weighted Persistent Entropy Loss: A Green Geometric and Topological Framework for Function Approximation
Scaling Performance of Large Language Model Pretraining
Towards Methane Detection Onboard Satellites
AEGIS: Automated Co-Evolutionary Framework for Guarding Prompt Injections Schema
Middo: Model-Informed Dynamic Data Optimization for Enhanced LLM Fine-Tuning via Closed-Loop Learning
Safe-Control: A Safety Patch for Mitigating Unsafe Content in Text-to-Image Generation Models
Condition Weaving Meets Expert Modulation: Towards Universal and Controllable Image Generation
Long Chain-of-Thought Reasoning Across Languages
MAHL: Multi-Agent LLM-Guided Hierarchical Chiplet Design with Adaptive Debugging
MCPSecBench: A Systematic Security Benchmark and Playground for Testing Model Context Protocols
MInDI-3D: Iterative Deep Learning in 3D for Sparse-view Cone Beam Computed Tomography
MAViS: A Multi-Agent Framework for Long-Sequence Video Storytelling
CoCoA: Collaborative Chain-of-Agents for Parametric-Retrieved Knowledge Synergy
Can Small-Scale Data Poisoning Exacerbate Dialect-Linked Biases in Large Language Models?
Distilling a Small Utility-Based Passage Selector to Enhance Retrieval-Augmented Generation
From Feedback to Checklists: Grounded Evaluation of AI-Generated Clinical Notes
Controllable Hybrid Captioner for Improved Long-form Video Understanding
Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks
Understanding Teen Overreliance on AI Companion Chatbots Through Self-Reported Reddit Narratives
ERR@HRI 2.0 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Conversations
Efficiency-Effectiveness Reranking FLOPs for LLM-based Rerankers
Truth, Trust, and Trouble: Medical AI on the Edge
LLMs on a Budget? Say HOLA
The Role of Model Confidence on Bias Effects in Measured Uncertainties for Vision-Language Models
A Survey of Foundation Models for IoT: Taxonomy and Criteria-Based Analysis
Breaking the Reviewer: Assessing the Vulnerability of Large Language Models in Automated Peer Review Under Textual Adversarial Attacks
Not All Clients Are Equal: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients
Rethinking Losses for Diffusion Bridge Samplers
Think With Videos For Agentic Long-Video Understanding
ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning
Intention-Conditioned Flow Occupancy Models
Product of Experts for Visual Generation
Modality-Balancing Preference Optimization of Large Multimodal Models by Adversarial Negative Mining
Dissecting Logical Reasoning in LLMs: A Fine-Grained Evaluation and Supervision Study
Tug-of-war between idioms' figurative and literal interpretations in LLMs
MAGREF: Masked Guidance for Any-Reference Video Generation with Subject Disentanglement
GL-PGENet: A Parameterized Generation Framework for Robust Document Image Enhancement
CAST: Contrastive Adaptation and Distillation for Semi-Supervised Instance Segmentation
Trans-EnV: A Framework for Evaluating the Linguistic Robustness of LLMs Against English Varieties
The Shape of Adversarial Influence: Characterizing LLM Latent Spaces with Persistent Homology
BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases
Inference-time Alignment in Continuous Space
STOPA: A Database of Systematic VariaTion Of DeePfake Audio for Open-Set Source Tracing and Attribution
Search Wisely: Mitigating Sub-optimal Agentic Searches By Reducing Uncertainty
Watch your steps: Dormant Adversarial Behaviors that Activate upon LLM Finetuning
LLINBO: Trustworthy LLM-in-the-Loop Bayesian Optimization
Logic Jailbreak: Efficiently Unlocking LLM Safety Restrictions Through Formal Logical Expression
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
Hakim: Farsi Text Embedding Model
Understanding In-context Learning of Addition via Activation Subspaces
Evaluating Evaluation Metrics - The Mirage of Hallucination Detection
T-VEC: A Telecom-Specific Vectorization Model with Enhanced Semantic Understanding via Deep Triplet Loss Fine-Tuning
Hallucination Detection in LLMs with Topological Divergence on Attention Graphs
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Mining the Mind: What 100M Beliefs Reveal About Frontier LLM Knowledge
Created by
Haebom
作者
Shrestha Ghosh, Luca Giordano, Yujia Hu, Tuan-Phong Nguyen, Simon Razniewski
概要
LLMはNLPとAIの作業に革新をもたらし、特にリアルな知識が重要な役割を果たしています。本稿では、GPT-4.1ベースのGPTKB v1.5（1億の知識）を活用して、最先端のLLMの現実的な知識を深く分析します。以前のベンチマークよりも精度が低く、既存の知識ベースとかなりの違いが見られ、矛盾、曖昧さ、幻覚などの主な問題が発見されました。
Takeaways、Limitations
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最先端LLMの現実的な知識の詳細な分析の実行
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GPT-4.1のリアルな知識ベースであるGPTKB v1.5の活用
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モデルの精度が既存のベンチマークより低く、既存の知識ベースとの差があることを発見
•
不一致、曖昧さ、幻覚などの問題を特定
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今後のリアルなLLM知識の研究機会を提示
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