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Multi-agent Adaptive Mechanism Design

이 논문이 다루는 핵심 문제는 “주체가 에이전트들의 사전 신념을 전혀 모르는 상황에서, 어떻게 하면 에이전트들이 진실된 정보를 제공하도록 유도하면서도 전체 비용을 최소화할 수 있는가”라는 질문이다. 전통적인 메커니즘 설계에서는 사전 분포가 주어지면 최적의 인센티브 구조를 설계할 수 있지만, 실제 환경에서는 이러한 사전 정보가 부재하거나 변동성이 크다. 저자들은 이를 해결하기 위해 두 분야—메커니즘 설계와 온라인 학습—의 아이디어를 융합한다. 먼저, DRAM은 매 라운드마다 에이전트들의 보고를 관찰하고, 이를 바탕으로 베이지안 추정

Multi-agent Adaptive Mechanism Design

Multi-Rigid-Body Approximation of Human Hands with Application to Digital Twin

NeuralRemaster: Phase-Preserving Diffusion for Structure-Aligned Generation

Optimal Software Pipelining and Warp Specialization for Tensor Core GPUs

Pix2NPHM: Learning to Regress NPHM Reconstructions From a Single Image

PULSE: A Unified Multi-Task Architecture for Cardiac Segmentation, Diagnosis, and Few-Shot Cross-Modality Clinical Adaptation

Quantifying Uncertainty in Machine Learning-Based Pervasive Systems: Application to Human Activity Recognition

Refusal Steering: Fine-grained Control over LLM Refusal Behaviour for Sensitive Topics

SALVE: Sparse Autoencoder-Latent Vector Editing for Mechanistic Control of Neural Networks

Seismology modeling agent: A smart assistant for geophysical researchers

SpidR-Adapt: A Universal Speech Representation Model for Few-Shot Adaptation

Step-Tagging: Toward controlling the generation of Language Reasoning Models through step monitoring

Strategic Self-Improvement for Competitive Agents in AI Labour Markets

The Dead Salmons of AI Interpretability

Thermal RGB Fusion for Micro-UAV Wildfire Perimeter Tracking with Minimal Comms

ThinkTrap: Denial-of-Service Attacks against Black-box LLM Services via Infinite Thinking

TrafficSimAgent: A Hierarchical Agent Framework for Autonomous Traffic Simulation with MCP Control

Unified Interactive Multimodal Moment Retrieval via Cascaded Embedding-Reranking and Temporal-Aware Score Fusion

Universal Hirschberg for Width Bounded Dynamic Programs

VLM in a flash: I/O-Efficient Sparsification of Vision-Language Model via Neuron Chunking

When to compute in space

Measuring What Matters: Scenario-Driven Evaluation for Trajectory Predictors in Autonomous Driving

State Space Models for Bioacoustics: A comparative Evaluation with Transformers

TrajMoE: Scene-Adaptive Trajectory Planning with Mixture of Experts and Reinforcement Learning

Large Language Models as Discounted Bayesian Filters

Mitigating Gender Bias in Depression Detection via Counterfactual Inference

Enabling Conversational Behavior Reasoning Capabilities in Full-Duplex Speech

iOS as Acceleration

Mechanistic Interpretability of GPT-2: Lexical and Contextual Layers in Sentiment Analysis

Neural Networks for Predicting Permeability Tensors of 2D Porous Media: Comparison of Convolution- and Transformer-based Architectures

MindFuse: Towards GenAI Explainability in Marketing Strategy Co-Creation

Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges

Evidence-Driven Decision Support for AI Model Selection in Research Software Engineering

MatKV: Trading Compute for Flash Storage in LLM Inference

Parallel Multi-Circuit Quantum Feature Fusion in Hybrid Quantum-Classical Convolutional Neural Networks for Breast Tumor Classification

Shortest Paths on Convex Polyhedral Surfaces

System Report for CCL25-Eval Task 10: Prompt-Driven Large Language Model Merge for Fine-Grained Chinese Hate Speech Detection

A Systematic Characterization of LLM Inference on GPUs

AI-Trader: Benchmarking Autonomous Agents in Real-Time Financial Markets

BlendedNet++: A Large-Scale Blended Wing Body Aerodynamics Dataset and Benchmark

CAPTURE: A Benchmark and Evaluation for LVLMs in CAPTCHA Resolving

Constant-Time Motion Planning with Manipulation Behaviors

Data-Free Pruning of Self-Attention Layers in LLMs

Dora: QoE-Aware Hybrid Parallelism for Distributed Edge AI

From Wearables to Warnings: Predicting Pain Spikes in Patients with Opioid Use Disorder

Informing Acquisition Functions via Foundation Models for Molecular Discovery

Interpretable Link Prediction in AI-Driven Cancer Research: Uncovering Co-Authorship Patterns

LinkedOut: Linking World Knowledge Representation Out of Video LLM for Next-Generation Video Recommendation

MMRAG-RFT: Two-stage Reinforcement Fine-tuning for Explainable Multi-modal Retrieval-augmented Generation

Multi-LLM Collaboration for Medication Recommendation

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