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。

Language Models are Injective and Hence Invertible

Learning to Detect Unknown Jailbreak Attacks in Large Vision-Language Models

Latent Diffusion Model without Variational Autoencoder

Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning

CBF-RL: Safety Filtering Reinforcement Learning in Training with Control Barrier Functions

Architecture Is All You Need: Diversity-Enabled Sweet Spots for Robust Humanoid Locomotion

LeapFactual: Reliable Visual Counterfactual Explanation Using Conditional Flow Matching

Knowledge-based Visual Question Answer with Multimodal Processing, Retrieval and Filtering

STANCE: Motion Coherent Video Generation Via Sparse-to-Dense Anchored Encoding

MedTrust-RAG: Evidence Verification and Trust Alignment for Biomedical Question Answering

Beyond One World: Benchmarking Super Heros in Role-Playing Across Multiversal Contexts

Static Sandboxes Are Inadequate: Modeling Societal Complexity Requires Open-Ended Co-Evolution in LLM-Based Multi-Agent Simulations

Deflanderization for Game Dialogue: Balancing Character Authenticity with Task Execution in LLM-based NPCs

ConsintBench: Evaluating Language Models on Real-World Consumer Intent Understanding

Max It or Miss It: Benchmarking LLM On Solving Extremal Problems

Phenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging

When Does Supervised Training Pay Off? The Hidden Economics of Object Detection in the Era of Vision-Language Models

The Curious Case of Factual (Mis)Alignment between LLMs' Short- and Long-Form Answers

A Vision for Access Control in LLM-based Agent Systems

Audit-of-Understanding: Posterior-Constrained Inference for Mathematical Reasoning in Language Models

Formally Verified Certification of Unsolvability of Temporal Planning Problems

DICE: Structured Reasoning in LLMs through SLM-Guided Chain-of-Thought Correction

MSDM: Generating Task-Specific Pathology Images with a Multimodal Conditioned Diffusion Model for Cell and Nuclei Segmentation

Synthetic Series-Symbol Data Generation for Time Series Foundation Models

SDAR: A Synergistic Diffusion-AutoRegression Paradigm for Scalable Sequence Generation

Online automatic code generation for robot swarms: LLMs and self-organizing hierarchy

A New Digital Divide? Coder Worldviews, the Slop Economy, and Democracy in the Age of AI

Audit the Whisper: Detecting Steganographic Collusion in Multi-Agent LLMs

Creative synthesis of kinematic mechanisms

Market-Driven Subset Selection for Budgeted Training

Mini-vec2vec: Scaling Universal Geometry Alignment with Linear Transformations

A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation

TimeEmb: A Lightweight Static-Dynamic Disentanglement Framework for Time Series Forecasting

Learning Generalizable Shape Completion with SIM(3) Equivariance

Dolphin v1.0 Technical Report

A Measurement Study of Model Context Protocol Ecosystem

Diffusion Models are Kelly Gamblers

RHYTHM: Reasoning with Hierarchical Temporal Tokenization for Human Mobility

Semantic Representation Attack against Aligned Large Language Models

Chiplet-Based RISC-V SoC with Modular AI Acceleration

Accurate and Efficient Low-Rank Model Merging in Core Space

The 1st Solution for 7th LSVOS RVOS Track: SaSaSa2VA

Graph Coloring for Multi-Task Learning

Robust LLM Training Infrastructure at ByteDance

RPG: A Repository Planning Graph for Unified and Scalable Codebase Generation

Communications to Circulations: Real-Time 3D Wind Field Prediction Using 5G GNSS Signals and Deep Learning

Why and How Auxiliary Tasks Improve JEPA Representations

Creativity Benchmark: A benchmark for marketing creativity for large language models

SpikingBrain: Spiking Brain-inspired Large Models

Robust Pan-Cancer Mitotic Figure Detection with YOLOv12

BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design

A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers

FlowDet: Overcoming Perspective and Scale Challenges in Real-Time End-to-End Traffic Detection

Epistemic Trade-Off: An Analysis of the Operational Breakdown and Ontological Limits of "Certainty-Scope" in AI

ZeST: an LLM ベースの Zero-Shot Traversability Navigation for Unknown Environments

Interpretable Decision-Making for End-to-End Autonomous Driving

A Systematic Approach to Predict the Impact of Cybersecurity Vulnerabilities Using LLMs

Limitations of Normalization in Attention Mechanism

Breaking the Exploration Bottleneck: Rubric-Scaffolded Reinforcement Learning for General LLM Reasoning

The GPT-4o Shock Emotional Attachment to AI Models and Its Impact on Regulatory Acceptance: A Cross-Cultural Analysis of the Immediate Transition from GPT-4o to GPT-5

CorrSteer: Generation-Time LLM Steering via Correlated Sparse Autoencoder Features

VimoRAG: Video-based Retrieval-augmented 3D Motion Generation for Motion Language Models

SegDAC: Improving Visual Reinforcement Learning by Extracting Dynamic Objectc-Centric Representations from Pretrained Vision Models

VGGSounder: Audio-Visual Evaluations for Foundation Models

Evolution of AI Agent Registry Solutions: Centralized, Enterprise, and Distributed Approaches

CAPO: Towards Enhancing LLM Reasoning through Generative Credit Assignment

FGBench: A Dataset and Benchmark for Molecular Property Reasoning at Functional Group-Level in Large Language Models

SketchMind: A Multi-Agent Cognitive Framework for Assessing Student-Drawn Scientific Sketches

A Multi-Stage Hybrid CNN-Transformer Network for Automated Pediatric Lung Sound Classification

From Individual Learning to Market Equilibrium: Correcting Structural and Parametric Biases in RL Simulations of Economic Models

ReDi: Rectified Discrete Flow

Adaptive Policy Synchronization for Scalable Reinforcement Learning

From Sequence to Structure: Uncovering Substructure Reasoning in Transformers

Multimodal Fusion at Three Tiers: Physics-Driven Data Generation and Vision-Language Guidance for Brain Tumor Segmentation

Controlling What You Share: Assessing Language Model Adherence to Privacy Preferences

DP-Fusion: Token-Level Differentially Private Inference for Large Language Models

AI-Generated Video Detection via Perceptual Straightening

From Cradle to Cane: A Two-Pass Framework for High-Fidelity Lifespan Face Aging

Client Clustering Meets Knowledge Sharing: Enhancing Privacy and Robustness in Personalized Peer-to-Peer Learning

ADA-DPM: A Neural Descriptors-based Adaptive Noise Filtering Strategy for SLAM

GeNIE: A Generalizable Navigation System for In-the-Wild Environments

From Multimodal Perception to Strategic Reasoning: A Survey on AI-Generated Game Commentary

Every Rollout Counts: Optimal Resource Allocation for Efficient Test-Time Scaling

PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation

Code Execution as Grounded Supervision for LLM Reasoning

Denoising the Future: Top-p Distributions for Moving Through Time

HauntAttack: When Attack Follows Reasoning as a Shadow

RoboRefer: Towards Spatial Referring with Reasoning in Vision-Language Models for Robotics

Infinity Parser: Layout Aware Reinforcement Learning for Scanned Document Parsing

VisuRiddles: Fine-grained Perception is a Primary Bottleneck for Multimodal Large Language Models in Abstract Visual Reasoning

CoVoMix2: Advancing Zero-Shot Dialogue Generation with Fully Non-Autoregressive Flow Matching

KG-TRACES: Enhancing Large Language Models with Knowledge Graph-constrained Trajectory Reasoning and Attribution Supervision

SATA-BENCH: Select All That Apply Benchmark for Multiple Choice Questions

REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewards

VERINA: Benchmarking Verifiable Code Generation

RocqStar: Leveraging Similarity-driven Retrieval and Agentic Systems for Rocq generation

The quest for the GRAph Level autoEncoder (GRALE)

Efficient Large Language Model Inference with Neural Block Linearization

DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning

Leveraging Importance Sampling to Detach Alignment Modules from Large Language Models

Online automatic code generation for robot swarms: LLMs and self-organizing hierarchy

Created by

Haebom

作者

Weixu Zhu, Marco Dorigo, Mary Katherine Heinrich

概要

最近導入された自己組織神経システム（SoNS）は、ロボット群集に1）行動設計の容易さと2）群集構成と集団環境の全体的な推定を提供し、ロボット群集のためのオンライン自動コード生成の実装を容易にします。 6台の実際のロボットと30台以上のロボットを使ったシミュレーション試験で、SoNSで強化されたロボット群集が止まると、外部LLMによってリアルタイムで生成されたコードを自動的に要求して実行し、85%の成功率でミッションを果たすことを示す。

Takeaways、Limitations

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Takeaways：

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自己組織神経システム（SoNS）によるロボット群集の行動設計が容易になる。

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群集の構成と環境の全体的な推定を可能にする。

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オンライン自動コード生成の実装を容易にします。

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LLMを活用して、詰まった状況で動的に問題を解決する能力を示します。

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実際のロボットとシミュレーション環境の両方で成功した結果を示します。

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Limitations:

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成功率が85％で、100％ではない。

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外部LLM依存性の存在。

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論文に具体的なLimitationsへの言及はありません。（ただし、要約で提示された情報のみを考慮）

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