14 citations · 18 across the 8 of their papers we have counts for
9 papers
Cowork-Gym: Synthesizing Interactive Work Environments at Scale
Anni Zou, Cheng Chen, Jiaji Deng +18
Cowork agents navigate dependencies across tools and files while adapting to changing user requirements and edits to shared workspaces. Scaling such environments requires maintaini…
CuES: A Curiosity-driven and Environment-grounded Synthesis Framework for Agentic RL
Shinji Mai, Yunpeng Zhai, Ziqian Chen +5
Large language model based agents are increasingly deployed in complex, tool augmented environments. While reinforcement learning provides a principled mechanism for such agents to…
AgentEvolver: Towards Efficient Self-Evolving Agent System
Yunpeng Zhai, Shuchang Tao, Cheng Chen +10
Autonomous agents powered by large language models (LLMs) have the potential to significantly enhance human productivity by reasoning, using tools, and executing complex tasks in d…
Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
Lipeng Xie, Sen Huang, Zhuo Zhang +9
Conventional reward modeling relies on gradient descent over neural weights, creating opaque, data-hungry "black boxes." We propose a paradigm shift from implicit to explicit rewar…
BriLLM: Brain-inspired Large Language Model
Hai Zhao, Hongqiu Wu, Dongjie Yang +2
We introduce BriLLM, a brain-inspired large language model that fundamentally redefines the foundations of machine learning through its implementation of Signal Fully-connected flo…
DOCBENCH: A Benchmark for Evaluating LLM-based Document Reading Systems
Anni Zou, Wenhao Yu, Hongming Zhang +5
Recently, there has been a growing interest among large language model (LLM) developers in LLM-based document reading systems, which enable users to upload their own documents and…
MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning
Xiangru Tang, Anni Zou, Zhuosheng Zhang +5
Large language models (LLMs), despite their remarkable progress across various general domains, encounter significant barriers in medicine and healthcare. This field faces unique c…
Generalizable Chain-of-Thought Prompting in Mixed-task Scenarios with Large Language Models
Anni Zou, Zhuosheng Zhang, Hai Zhao +1
Large language models (LLMs) have unveiled remarkable reasoning capabilities by exploiting chain-of-thought (CoT) prompting, which generates intermediate reasoning chains to serve…
Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification
Anni Zou, Zhuosheng Zhang, Hai Zhao
Commonsense fact verification, as a challenging branch of commonsense question-answering (QA), aims to verify through facts whether a given commonsense claim is correct or not. Ans…