Daily Arxiv

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Dataforge: A Data Agent Platform for Autonomous Data Engineering

CSP4SDG: Constraint and Information-Theory Based Role Identification in Social Deduction Games with LLM-Enhanced Inference

Chasing Consistency: Quantifying and Optimizing Human-Model Alignment in Chain-of-Thought Reasoning

Evaluating Implicit Biases in LLM Reasoning through Logic Grid Puzzles

MALinZero: Efficient Low-Dimensional Search for Mastering Complex Multi-Agent Planning

When Object-Centric World Models Meet Policy Learning: From Pixels to Policies, and Where It Breaks

Maestro: Learning to Collaborate via Conditional Listwise Policy Optimization for Multi-Agent LLMs

ScRPO: From Errors to Insights

An Epistemic Perspective on Agent Awareness

Klear-AgentForge: Forging Agentic Intelligence through Posttraining Scaling

Self-Abstraction from Grounded Experience for Plan-Guided Policy Refinement

Unveiling Modality Bias: Automated Sample-Specific Analysis for Multimodal Misinformation Benchmarks

An Empirical Study of Reasoning Steps in Thinking Code LLMs

Can a Small Model Learn to Look Before It Leaps? Dynamic Learning and Proactive Correction for Hallucination Detection

DiagnoLLM: A Hybrid Bayesian Neural Language Framework for Interpretable Disease Diagnosis

Anchors in the Machine: Behavioral and Attributional Evidence of Anchoring Bias in LLMs

CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization

From Prompts to Power: Measuring the Energy Footprint of LLM Inference

SMAGDi: Socratic Multi Agent Interaction Graph Distillation for Efficient High Accuracy Reasoning

Evidence-Bound Autonomous Research (EviBound): A Governance Framework for Eliminating False Claims

On the Brittleness of CLIP Text Encoders

NVIDIA Nemotron Nano V2 VL

Improving Diagnostic Performance on Small and Imbalanced Datasets Using Class-Based Input Image Composition

Retrofitters, pragmatists and activists: Public interest litigation for accountable automated decision-making

Text to Robotic Assembly of Multi Component Objects using 3D Generative AI and Vision Language Models

The Future of Generative AI in Software Engineering: A Vision from Industry and Academia in the European GENIUS Project

AURA: A Reinforcement Learning Framework for AI-Driven Adaptive Conversational Surveys

Grounded in Reality: Learning and Deploying Proactive LLM from Offline Logs

USF-MAE: Ultrasound Self-Supervised Foundation Model with Masked Autoencoding

CompressionAttack: Exploiting Prompt Compression as a New Attack Surface in LLM-Powered Agents

Every Activation Boosted: Scaling General Reasoner to 1 Trillion Open Language Foundation

Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics

What Can String Probability Tell Us About Grammaticality?

Fine-Tuning MedGemma for Clinical Captioning to Enhance Multimodal RAG over Malaysia CPGs

Learning to Navigate Socially Through Proactive Risk Perception

Policy-as-Prompt: Turning AI Governance Rules into Guardrails for AI Agents

A Mega-Study of Digital Twins Reveals Strengths, Weaknesses and Opportunities for Further Improvement

Amortized Latent Steering: Low-Cost Alternative to Test-Time Optimization

Amulet: a Python Library for Assessing Interactions Among ML Defenses and Risks

LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence

AI Agentic Vulnerability Injection And Transformation with Optimized Reasoning

What Matters in Data for DPO?

Chain-of-Query: Unleashing the Power of LLMs in SQL-Aided Table Understanding via Multi-Agent Collaboration

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving

Advanced Hybrid Transformer LSTM Technique with Attention and TS Mixer for Drilling Rate of Penetration Prediction

Learning Dynamics of Meta-Learning in Small Model Pretraining

GAITEX: Human motion dataset of impaired gait and rehabilitation exercises using inertial and optical sensors

To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks

NMIXX: Domain-Adapted Neural Embeddings for Cross-Lingual eXploration of Finance

ZERO: Industry-ready Vision Foundation Model with Multi-modal Prompts

Conformal Information Pursuit for Interactively Guiding Large Language Models

Less Greedy Equivalence Search

Progressive Inference-Time Annealing of Diffusion Models for Sampling from Boltzmann Densities

Know What You Don't Know: Uncertainty Calibration of Process Reward Models

Conformal Prediction Adaptive to Unknown Subpopulation Shifts

ProRefine: Inference-Time Prompt Refinement with Textual Feedback

Learning of Population Dynamics: Inverse Optimization Meets JKO Scheme

RCCDA: Adaptive Model Updates in the Presence of Concept Drift under a Constrained Resource Budget

Optimizing Anytime Reasoning via Budget Relative Policy Optimization

Taskmaster Deconstructed: A Quantitative Look at Tension, Volatility, and Viewer Ratings

XBreaking: Understanding how LLMs security alignment can be broken

Pogobot: an Open-Source, Low-Cost Robot for Swarm Robotics and Programmable Active Matter

Large language models as uncertainty-calibrated optimizers for experimental discovery

AIRepr: An Analyst-Inspector Framework for Evaluating Reproducibility of LLMs in Data Science

InterFeedback: Unveiling Interactive Intelligence of Large Multimodal Models via Human Feedback

Analyzing limits for in-context learning

Activation-Informed Merging of Large Language Models

iTool: Reinforced Fine-Tuning with Dynamic Deficiency Calibration for Advanced Tool Use

MMDocIR: Benchmarking Multimodal Retrieval for Long Documents

Cognitive Edge Computing: A Comprehensive Survey on Optimizing Large Models and AI Agents for Pervasive Deployment

TOBUGraph: Knowledge Graph-Based Retrieval for Enhanced LLM Performance Beyond RAG

CTPD: Cross-Modal Temporal Pattern Discovery for Enhanced Multimodal Electronic Health Records Analysis

Affordance-based Robot Manipulation with Flow Matching

FunOTTA: On-the-Fly Adaptation on Cross-Domain Fundus Image via Stable Test-time Training

Tactical Decision Making for Autonomous Trucks by Deep Reinforcement Learning with Total Cost of Operation Based Reward

Characterizing the Training Dynamics of Private Fine-tuning with Langevin diffusion

Learning for Interval Prediction of Electricity Demand: A Cluster-based Bootstrapping Approach

The Less Intelligent the Elements, the More Intelligent the Whole. Or, Possibly Not?

Monitor-Generate-Verify (MGV): Formalising Metacognitive Theory for Language Model Reasoning

Outbidding and Outbluffing Elite Humans: Mastering Liar's Poker via Self-Play and Reinforcement Learning

A Proprietary Model-Based Safety Response Framework for AI Agents

Orion-MSP: Multi-Scale Sparse Attention for Tabular In-Context Learning

Inverse Knowledge Search over Verifiable Reasoning: Synthesizing a Scientific Encyclopedia from a Long Chains-of-Thought Knowledge Base

From Observability Data to Diagnosis: An Evolving Multi-agent System for Incident Management in Cloud Systems

How Do AI Agents Do Human Work? Comparing AI and Human Workflows Across Diverse Occupations

String Seed of Thought: Prompting LLMs for Distribution-Faithful and Diverse Generation

HugAgent: Benchmarking LLMs for Simulation of Individualized Human Reasoning

Internal World Models as Imagination Networks in Cognitive Agents

Open Agent Specification (Agent Spec): A Unified Representation for AI Agents

Bilinear relational structure fixes reversal curse and enables consistent model editing

Introducing LongCat-Flash-Thinking: A Technical Report

AI Through the Human Lens: Investigating Cognitive Theories in Machine Psychology

Wider or Deeper? Scaling LLM Inference-Time Compute with Adaptive Branching Tree Search

Retrieval Augmented Diffusion Model for Structure-informed Antibody Design and Optimization

Joint Verification and Refinement of Language Models for Safety-Constrained Planning

TimeSearch-R: Adaptive Temporal Search for Long-Form Video Understanding via Self-Verification Reinforcement Learning

DGTN: Graph-Enhanced Transformer with Diffusive Attention Gating Mechanism for Enzyme DDG Prediction

On Flow Matching KL Divergence

MM-STFlowNet: A Transportation Hub-Oriented Multi-Mode Passenger Flow Prediction Method via Spatial-Temporal Dynamic Graph Modeling

Created by

Haebom

저자

Ronghui Zhang, Wenbin Xing, Mengran Li, Zihan Wang, Junzhou Chen, Xiaolei Ma, Zhiyuan Liu, Zhengbing He

개요

광저우난 기차역의 실제 데이터 세트를 사용한 실험을 통해 다양한 교통 수단 간의 상호 의존성을 고려하여 대규모 교통 허브에서 여러 수집 및 분배 모드의 공동 관리를 최적화하는 데 필수적인 정확하고 세련된 승객 흐름 예측을 위한 포괄적인 다중 모드 예측 프레임워크인 MM-STFlowNet을 제안합니다. MM-STFlowNet은 신호 분해 및 합성곱 기술을 사용하는 통합 시간적 특징 처리 전략, 다양한 교통 모드 간의 상세한 공간-시간적 의존성을 포착하는 공간-시간 동적 그래프 합성곱 순환 네트워크(STDGCRN), 적응적 채널 어텐션 메커니즘, 그리고 다양한 외부 요인을 통합하는 자기 어텐션 메커니즘을 포함합니다. 특히 피크 시간대에 최첨단 성능을 달성하여 교통 허브 관리에 귀중한 통찰력을 제공합니다.

시사점, 한계점

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시사점:

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다중 교통 모드 간의 상호 의존성을 고려한 승객 흐름 예측 프레임워크 제시

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공간-시간적 동적 그래프 모델링을 통한 정확도 향상

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피크 시간대 예측 성능 향상

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실제 데이터 기반의 검증을 통해 실용성 입증

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한계점:

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제시된 모델의 일반화 성능에 대한 추가적인 검증 필요

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사용된 데이터셋의 특수성으로 인한 다른 지역 또는 허브로의 일반화 가능성 제한

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외부 요인의 종류 및 데이터 품질에 대한 의존성

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모델의 복잡성으로 인한 계산 비용 증가 가능성

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