83 citations · 114 across the 23 of their papers we have counts for
24 papers
CARVS: A Congestion-Aware Algorithm for Online Multi-Agent Pickup-and-Delivery in Human-Collaborative Warehouses
Chaoran Li, Zeyuan Zhao, Shao Zhang
Intelligent warehouse systems have transformed logistics by integrating robots with minimal infrastructure changes, boosting efficiency and optimizing workflows compared to traditi…
Harness-of-Harness: Multi-Day Autonomous Software Development with Continual Improvement
Haoyang Yan, Min-le Su, Hangfan Zhang +6
This paper studies autonomous software development, in which LLM-based coding agents transform high-level requirements into complete, functional, and usable software systems withou…
AgentPanel: Toward a New Paradigm for Human--AI Collaboration in Exploring Scientific Questions
Zhiyao Cui, Qianyi Wang, Haoyang Yan +26
Identifying promising scientific ideas remains an important challenge in research practice. Researchers commonly rely on small-group discussions or one-to-one interactions with a s…
Sequence Pathfinder for Multi-Agent Pickup and Delivery in the Warehouse
Zeyuan Zhao, Chaoran Li, Shao Zhang +1
Multi-Agent Pickup and Delivery (MAPD) is a challenging extension of Multi-Agent Path Finding (MAPF), where agents are required to sequentially complete tasks with fixed-location p…
Context Value Informed In-Context Reinforcement Learning
Wenhao Zhang, Shao Zhang, Xihuai Wang +2
In-context reinforcement learning (ICRL) has emerged as an effective paradigm for test time adaptation to unseen tasks without parameter updates. However, existing ICRL methods can…
Structured In-context Environment Scaling for Large Language Model Reasoning
Peng Yu, Zeyuan Zhao, Shao Zhang +3
Large language models (LLMs) have achieved significant advancements in reasoning capabilities through reinforcement learning (RL) via environmental exploration. As the intrinsic pr…
Audio Turing Test: Benchmarking the Human-likeness of Large Language Model-based Text-to-Speech Systems in Chinese
Xihuai Wang, Ziyi Zhao, Siyu Ren +9
Recent advances in large language models (LLMs) have significantly improved text-to-speech (TTS) systems, enhancing control over speech style, naturalness, and emotional expression…
PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning
Kun Hu, Muning Wen, Xihuai Wang +5
Multi-agent reinforcement learning (MARL) faces challenges in coordinating agents due to complex interdependencies within multi-agent systems. Most MARL algorithms use the simultan…
Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration
Shao Zhang, Xihuai Wang, Wenhao Zhang +10
Agents built on large language models (LLMs) have excelled in turn-by-turn human-AI collaboration but struggle with simultaneous tasks requiring real-time interaction. Latency issu…
Language Games as the Pathway to Artificial Superhuman Intelligence
Ying Wen, Ziyu Wan, Shao Zhang
The evolution of large language models (LLMs) toward artificial superhuman intelligence (ASI) hinges on data reproduction, a cyclical process in which models generate, curate and r…
Mutual Theory of Mind in Human-AI Collaboration: An Empirical Study with LLM-driven AI Agents in a Real-time Shared Workspace Task
Shao Zhang, Xihuai Wang, Wenhao Zhang +6
Theory of Mind (ToM) significantly impacts human collaboration and communication as a crucial capability to understand others. When AI agents with ToM capability collaborate with h…
AceMap: Knowledge Discovery through Academic Graph
Xinbing Wang, Luoyi Fu, Xiaoying Gan +23
The exponential growth of scientific literature requires effective management and extraction of valuable insights. While existing scientific search engines excel at delivering sear…
Aligning Individual and Collective Objectives in Multi-Agent Cooperation
Yang Li, Wenhao Zhang, Jianhong Wang +4
Among the research topics in multi-agent learning, mixed-motive cooperation is one of the most prominent challenges, primarily due to the mismatch between individual and collective…
Human Still Wins over LLM: An Empirical Study of Active Learning on Domain-Specific Annotation Tasks
Yuxuan Lu, Bingsheng Yao, Shao Zhang +5
Large Language Models (LLMs) have demonstrated considerable advances, and several claims have been made about their exceeding human performance. However, in real-world tasks, domai…
Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach
Bin Zhang, Hangyu Mao, Jingqing Ruan +9
The remarkable progress in Large Language Models (LLMs) opens up new avenues for addressing planning and decision-making problems in Multi-Agent Systems (MAS). However, as the numb…
More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering
Bingsheng Yao, Guiming Chen, Ruishi Zou +7
While most existing works on LLM prompting techniques focus only on how to select a better set of data samples inside one single prompt input (In-Context Learning or ICL), why can…
StorySparkQA: Expert-Annotated QA Pairs with Real-World Knowledge for Children's Story-Based Learning
Jiaju Chen, Yuxuan Lu, Shao Zhang +7
Interactive story reading is a common parent-child activity, where parents expect to teach both language skills and real-world knowledge beyond the story. While increasing storytel…
ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination
Xihuai Wang, Shao Zhang, Wenhao Zhang +4
Zero-shot coordination (ZSC) is a new cooperative multi-agent reinforcement learning (MARL) challenge that aims to train an ego agent to work with diverse, unseen partners during d…
Rethinking Human-AI Collaboration in Complex Medical Decision Making: A Case Study in Sepsis Diagnosis
Shao Zhang, Jianing Yu, Xuhai Xu +8
Today's AI systems for medical decision support often succeed on benchmark datasets in research papers but fail in real-world deployment. This work focuses on the decision making o…
Talk2Care: Facilitating Asynchronous Patient-Provider Communication with Large-Language-Model
Ziqi Yang, Xuhai Xu, Bingsheng Yao +6
Despite the plethora of telehealth applications to assist home-based older adults and healthcare providers, basic messaging and phone calls are still the most common communication…
Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination
Yang Li, Shao Zhang, Jichen Sun +5
Securing coordination between AI agent and teammates (human players or AI agents) in contexts involving unfamiliar humans continues to pose a significant challenge in Zero-Shot Coo…
Cooperative Open-ended Learning Framework for Zero-shot Coordination
Yang Li, Shao Zhang, Jichen Sun +4
Zero-shot coordination in cooperative artificial intelligence (AI) remains a significant challenge, which means effectively coordinating with a wide range of unseen partners. Previ…
Melody Infilling with User-Provided Structural Context
Chih-Pin Tan, Alvin W. Y. Su, Yi-Hsuan Yang
This paper proposes a novel Transformer-based model for music score infilling, to generate a music passage that fills in the gap between given past and future contexts. While exist…
DeepShovel: An Online Collaborative Platform for Data Extraction in Geoscience Literature with AI Assistance
Shao Zhang, Yuting Jia, Hui Xu +3
Geoscientists, as well as researchers in many fields, need to read a huge amount of literature to locate, extract, and aggregate relevant results and data to enable future research…