Multi-Agent Systems

AgentArk
AgentArk

Distills multi-agent debate into one LLM through reasoning-enhanced fine-tuning, trajectory-based augmentation, and process-aware distillation. NeurIPS 2026.

Sep 24, 2026

MASCOT: Towards Multi-Agent Socio-Collaborative Companion Systems
MASCOT: Towards Multi-Agent Socio-Collaborative Companion Systems

MASCOT is a multi-agent framework for socio-collaborative companions that uses bi-level optimization—persona-aware behavioral alignment and collaborative dialogue optimization—to counter persona collapse and social sycophancy, improving role consistency and reducing redundant dialogue.

Sep 1, 2026

AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent
AgentArk: Distilling Multi-Agent Intelligence into a Single LLM Agent

Distills multi-agent debate into one LLM through reasoning-enhanced fine-tuning, trajectory-based augmentation, and process-aware distillation, moving computation from inference to training.

Feb 3, 2026

Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems
Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems

We propose a framework for developing topology-aware Multi-Agent Systems (MAS), emphasizing agent selection, structure profiling, and topology synthesis, to enhance coordination and efficiency in complex task.

Jul 4, 2025

Large Language Model Agent: A Survey on Methodology, Applications and Challenges

A methodology-centered survey of LLM agents, connecting agent architectures, collaboration, and evolution with evaluation, tools, applications, and open challenges.

Mar 27, 2025

AgentReview

First LLM-based peer review simulation framework that disentangles latent factors driving reviewer decisions. Reveals a 37.1% variation in paper decisions due to reviewer biases. EMNLP 2024 Oral.

Nov 12, 2024

CompeteAI
CompeteAI

Studies competition dynamics among LLM-based agents in a simulated virtual town with restaurant and customer agents. Reveals emergent behaviors and strategic patterns aligned with market and sociological theories. ICML 2024 Oral.

May 1, 2024

CompeteAI: Understanding the Competition Behaviors in Large Language Model-based Agents
CompeteAI: Understanding the Competition Behaviors in Large Language Model-based Agents

This work studies the competition dynamics among LLM-based agents, revealing emergent behaviors and strategic patterns in multi-agent systems....

Apr 30, 2024