most citedBOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

9 citations · 14 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE20241 cited

Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents

Kexun Zhang, Weiran Yao, Zuxin Liu +13

Large language model (LLM) agents have shown great potential in solving real-world software engineering (SWE) problems. The most advanced open-source SWE agent can resolve over 27%…

cs.IR2024

Personalized Multi-task Training for Recommender System

Liangwei Yang, Zhiwei Liu, Jianguo Zhang +5

In the vast landscape of internet information, recommender systems (RecSys) have become essential for guiding users through a sea of choices aligned with their preferences. These s…

cs.CL20242 cited

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets

Zuxin Liu, Thai Hoang, Jianguo Zhang +14

The advancement of function-calling agent models requires diverse, reliable, and high-quality datasets. This paper presents APIGen, an automated data generation pipeline designed t…

cs.CL20242 cited

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases

Rithesh Murthy, Liangwei Yang, Juntao Tan +15

The deployment of Large Language Models (LLMs) and Large Multimodal Models (LMMs) on mobile devices has gained significant attention due to the benefits of enhanced privacy, stabil…

cs.AI20239 cited

BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents

Zhiwei Liu, Weiran Yao, Jianguo Zhang +12

The massive successes of large language models (LLMs) encourage the emerging exploration of LLM-augmented Autonomous Agents (LAAs). An LAA is able to generate actions with its core…