7 papers
Scaling Behavior of Single LLM-Driven Multi-Agent Systems
Jialing Li, Zhouhong Gu, Yin Cai +1
The burgeoning field of LLM-based Multi-Agent Systems (MAS) promises to tackle complex tasks through collaborative intelligence, yet fundamental questions regarding their scaling b…
ClarEval: A Benchmark for Evaluating Clarification Skills of Code Agents under Ambiguous Instructions
Jialin Li, Yuan Wu, Yi Chang
To integrate seamlessly into real-world software engineering, Code Agents must evolve from passive instruction followers into proactive collaborative partners. However, current eva…
Reaching Agreement Among Reasoning LLM Agents
Chaoyi Ruan, Yiliang Wang, Ziji Shi +1
Multi-agent systems have extended the capability of agentic AI. Instead of single inference passes, multiple agents perform collective reasoning to derive high quality answers. How…
Refining Critical Thinking in LLM Code Generation: A Faulty Premise-based Evaluation Framework
Jialin Li, Jinzhe Li, Gengxu Li +2
With the advancement of code generation capabilities in large language models (LLMs), their reliance on input premises has intensified. When users provide inputs containing faulty…
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
Zhouhong Gu, Xiaoxuan Zhu, Yin Cai +12
Large language model based multi-agent systems have demonstrated significant potential in social simulation and complex task resolution domains. However, current frameworks face cr…
DynaServe: Unified and Elastic Execution for Dynamic Disaggregated LLM Serving
Chaoyi Ruan, Yinhe Chen, Dongqi Tian +4
LLM inference must meet strict latency SLOs (e.g., 100 ms P99 time-between-tokens) while maximizing goodput. Yet, real-world variability in prompt and response lengths skews comput…