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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。
Self-Questioning Language Models
Beyond risk: A proto-framework for assessing the societal impact of AI systems
Supervised Dynamic Dimension Reduction with Deep Neural Network
EmoSteer-TTS: Fine-Grained and Training-Free Emotion-Controllable Text-to-Speech via Activation Steering
LLMs Have a Heart of Stone: Demystifying the Soft Thinking Ability of Large Reasoning Models
Industrial LLM-based Code Optimization under Regulation: A Mixture-of-Agents Approach
Reliable Evaluation Protocol for Low-Precision Retrieval
Landsat30-AU: A Vision-Language Dataset for Australian Landsat Imagery
Tool-integrated Reinforcement Learning for Repo Deep Search
CauKer: classification time series foundation models can be pretrained on synthetic data only
Context-Adaptive Multi-Prompt Embedding with Large Language Models for Vision-Language Alignment
DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
HyCodePolicy: Hybrid Language Controllers for Multimodal Monitoring and Decision in Embodied Agents
Entity Representation Learning Through Onsite-Offsite Graph for Pinterest Ads
Evaluating User Experience in Conversational Recommender Systems: A Systematic Review Across Classical and LLM-Powered Approaches
Spatial-Frequency Aware for Object Detection in RAW Image
Learning Pivoting Manipulation with Force and Vision Feedback Using Optimization-based Demonstrations
NCCR: to Evaluate the Robustness of Neural Networks and Adversarial Examples
ChartM$^3$: Benchmarking Chart Editing with Multimodal Instructions
From Entanglement to Alignment: Representation Space Decomposition for Unsupervised Time Series Domain Adaptation
EcoTransformer: Attention without Multiplication
Bob's Confetti: Phonetic Memorization Attacks in Music and Video Generation
SDBench: A Comprehensive Benchmark Suite for Speaker Diarization
True Multimodal In-Context Learning Needs Attention to the Visual Context
Gauge Flow Models
Zero-Shot Neural Architecture Search with Weighted Response Correlation
The Dark Side of LLMs: Agent-based Attacks for Complete Computer Takeover
CAVGAN: Unifying Jailbreak and Defense of LLMs via Generative Adversarial Attacks on their Internal Representations
VOTE: Vision-Language-Action Optimization with Trajectory Ensemble Voting
A Comparative Study of Specialized LLMs as Dense Retrievers
Sign Spotting Disambiguation using Large Language Models
UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields
Thought Anchors: Which LLM Reasoning Steps Matter?
UITron-Speech: Towards Automated GUI Agents Based on Speech Instructions
15,500 Seconds: Lean UAV Classification Using EfficientNet and Lightweight Fine-Tuning
AtmosMJ: Revisiting Gating Mechanism for AI Weather Forecasting Beyond the Year Scale
On the Fundamental Impossibility of Hallucination Control in Large Language Models
Multi-Modal Multi-Task Federated Foundation Models for Next-Generation Extended Reality Systems: Towards Privacy-Preserving Distributed Intelligence in AR/VR/MR
Text-Only Reasoning Unleashes Zero-Shot Multimodal Evaluators
CAIN: Hijacking LLM-Humans Conversations via Malicious System Prompts
Explain Less, Understand More: Jargon Detection via Personalized Parameter-Efficient Fine-tuning
What Lives? A meta-analysis of diverse opinions on the definition of life
A Generative Neural Annealer for Black-Box Combinatorial Optimization
GRILL: Gradient Signal Restoration in Ill-Conditioned Layers to Enhance Adversarial Attacks on Autoencoders
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
Mj\"olnir: A Deep Learning Parametrization Framework for Global Lightning Flash Density
RGB-Event based Pedestrian Attribute Recognition: A Benchmark Dataset and An Asymmetric RWKV Fusion Framework
ProtoECGNet: Case-Based Interpretable Deep Learning for Multi-Label ECG Classification with Contrastive Learning
Beyond Wide-Angle Images: Structure-to-Detail Video Portrait Correction via Unsupervised Spatiotemporal Adaptation
CITRAS: Covariate-Informed Transformer for Time Series Forecasting
Rubric Is All You Need: Enhancing LLM-based Code Evaluation With Question-Specific Rubrics
Empirical Analysis of Sim-and-Real Cotraining of Diffusion Policies for Planar Pushing from Pixels
SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild
NuPlanQA: A Large-Scale Dataset and Benchmark for Multi-View Driving Scene Understanding in Multi-Modal Large Language Models
The Impact of Item-Writing Flaws on Difficulty and Discrimination in Item Response Theory
Through the Magnifying Glass: Adaptive Perception Magnification for Hallucination-Free VLM Decoding
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Pull-Based Query Scheduling for Goal-Oriented Semantic Communication
Accelerating Focal Search in Multi-Agent Path Finding with Tighter Lower Bounds
RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks
UltraSTF: Ultra-Compact Model for Large-Scale Spatio-Temporal Forecasting
PTQ1.61: Push the Real Limit of Extremely Low-Bit Post-Training Quantization Methods for Large Language Models
Foundation Model of Electronic Medical Records for Adaptive Risk Estimation
Tool Unlearning for Tool-Augmented LLMs
Vision without Images: End-to-End Computer Vision from Single Compressive Measurements
How Do Generative Models Draw a Software Engineer? A Case Study on Stable Diffusion Bias
3DTTNet: Multimodal Fusion-Based 3D Traversable Terrain Modeling for Off-Road Environments
DOGR: Towards Versatile Visual Document Grounding and Referring
Real-World Offline Reinforcement Learning from Vision Language Model フィードバック
Causality-Driven Audits of Model Robustness
AUTALIC: A Dataset for Anti-AUTistic Ableist Language In Context
Beyond Adapter Retrieval: Latent Geometry-Preserving Composition via Sparse Task Projection
Pyhgf: A neural network library for predictive coding
Human Bias in the Face of AI: Examining Human Judgment Against Text Labeled as AI Generated
AVG-LLaVA: An Efficient Large Multimodal Model with Adaptive Visual Granularity
Parse Trees Guided LLM Prompt Compression
One Model, Any Conjunctive Query: Graph Neural Networks for Answering Queries over Incomplete Knowledge Graphs
A Value Based Parallel Update MCTS Method for Multi-Agent Cooperative Decision Making of Connected and Automated Vehicles
Fairness Definitions in Language Models Explained
CityLight: A Neighborhood-inclusive Universal Model for Coordinated City-scale Traffic Signal Control
Time Evidence Fusion Network: Multi-source View in Long-Term Time Series Forecasting
Long-Term Visual Object Tracking with Event Cameras: An Associative Memory Augmented Tracker and A Benchmark Dataset
Hulk: A Universal Knowledge Translator for Human-Centric Tasks
From Cluster Assumption to Graph Convolution: Graph-based Semi-Supervised Learning Revisited
Environmental Sound Classification on An Embedded Hardware Platform
Data Dependency Inference for Industrial Code Generation Based on UML Sequence Diagrams
InqEduAgent: Adaptive AI Learning Partners with Gaussian Process Augmentation
SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning with LLM-Based Agents
RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization
Higher Gauge Flow Models
Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models
IS-Bench: Evaluating Interactive Safety of VLM-Driven Embodied Agents in Daily Household Tasks
SLR: Automated Synthesis for Scalable Logical Reasoning
The SWE-Bench Illusion: When State-of-the-Art LLMs Remember Instead of Reason
APOLLO: Automated LLM and Lean Collaboration for Advanced Formal Reasoning
Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets
Learning to Inference Adaptively for Multimodal Large Language Models
Efficient rule induction by ignoring pointless rules
Why the Agent Made that Decision: Contrastive Explanation Learning for Reinforcement Learning
Evaluating Detection Thresholds: The Impact of False Positives and Negatives on Super-Resolution Ultrasound Localization Microscopy
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RAILGUN: A Unified Convolutional Policy for Multi-Agent Path Finding Across Different Environments and Tasks
Created by
Haebom
作者
Yimin Tang, Xiao Xiong, Jingyi Xi, Jiaoyang Li, Erdem B{\i}y{\i}k, Sven Koenig
概要
本論文は、複数のエージェント経路探索（MAPF）問題の最初の集中型学習ベースのポリシーであるRAILGUNを提示します。従来の分散型学習ベースの方法とは異なり、RAILGUNはCNNベースのアーキテクチャを活用してマップベースのポリシーとして設計されており、さまざまなマップサイズとエージェント数を一般化できます。ルールベースの方法から収集された軌跡データを用いて指導学習方式でモデルを訓練し、様々な実験結果を通じて既存の方法より優れた性能と優れたゼロショット一般化性能を示すことを立証する。
Takeaways、Limitations
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Takeaways:
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多数のエージェント経路探索問題に対する最初の集中型学習ベースのポリシーの提示
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マップベースのポリシーにより、さまざまなマップサイズとエージェント数の一般化の可能性を実証
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ゼロショット一般化性能が優れていることを実験的に検証
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従来の方法に比べて優れた性能を達成
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Limitations:
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ルールベースの方法から収集されたデータを使用する指導学習方式に依存
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RAILGUNのアーキテクチャと訓練プロセスの詳細な説明の欠如（追加情報が必要）
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他のタイプのMAPF問題(動的環境など)の一般化パフォーマンス検証の欠如
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