Guancheng Wan

Multiplayer Nash Preference Optimization

Eigen-Agent: Adaptive Multi-Agent Scientific Reasoning with Monitor-Based RAG

Beyond Magic Words: Sharpness-Aware Prompt Evolving for Robust Large Language Models with TARE

LatentEvolve: Self-Evolving Test-Time Scaling in Latent Space

Reasoning Self-Evaluation via Trajectory Dynamics Modeling

FD-Bench: A Modular and Fair Benchmark for Data-driven Fluid Simulation

RISE: A Statistical Perspective for Adversarial Attacks against Closed-Source MLLMs

GTD: Dynamic Generation of Multi LLM Agents Communication Topologies with Graph Diffusion Models

Two Lenses are Better Than One: Dual Vector Quantization for Self-Supervised Graph Learning

AURA: Structural and Semantic Calibration for Robust Federated Graph Learning

ThanoRA: Task Heterogeneity-Aware Multi-Task Low-Rank Adaptation

Diagnose, Localize, Align: A Full-Stack Framework for Reliable LLM Multi-Agent Systems under Instruction Conflicts

FedSDR: Federated Graph Learning with Structural Noise Detection and Reconstruction

Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical Reasoning

Energy-Driven Steering: Reducing False Refusals in Large Language Models

MAPO: MIXED ADVANTAGE POLICY OPTIMIZATION

EARTH: Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph

DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning

GHOST: Generalizable One-Shot Federated Graph Learning with Proxy-Based Topology Knowledge Retention

G-Memory: Tracing Hierarchical Memory for Multi-Agent Systems

Energy-based Backdoor Defense Against Federated Graph Learning

HYPERION: Fine-Grained Hypersphere Alignment for Robust Federated Graph Learning

Rethink GraphODE Generalization within Coupled Dynamical System

$S^2$FGL: Spatial Spectral Federated Graph Learning

G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks

Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning

Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning

OASIS: One-Shot Federated Graph Learning via Wasserstein Assisted Knowledge Integration

Don’t Forget the Enjoin: FocalLoRA for Instruction Hierarchical Alignment in Large Language Models

Multi-order Orchestrated Curriculum Distillation for Model-Heterogeneous Federated Graph Learning

EAGLES: Towards Effective, Efficient, and Economical Federated Graph Learning via Unified Sparsification

Federated Disentangled Tuning with Textual Prior Decoupling and Visual Dynamic Adaptation

Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning

FedPHA: Federated Prompt Learning for Heterogeneous Client Adaptation

Splitting with Importance-aware Updating for Heterogeneous Federated Learning with Large Language Models

Cut the Crap: An Economical Communication Pipeline for LLM-based Multi-Agent Systems

MOTION: Multi-Sculpt Evolutionary Coarsening for Federated Continual Graph Learning

Flow Field Reconstruction with Sensor Placement Policy Learning

Divide And Conquer: Efficiently Decoupling Consensus And Divergence For Federated Large Language Model Fine-Tuning