2 citations · 4 across the 6 of their papers we have counts for
6 papers
AMAP Agentic Planning Technical Report
AMAP AI Agent Team, Yulan Hu, Xiangwen Zhang +22
We present STAgent, an agentic large language model tailored for spatio-temporal understanding, designed to solve complex tasks such as constrained point-of-interest discovery and…
No More Stale Feedback: Co-Evolving Critics for Open-World Agent Learning
Zhicong Li, Lingjie Jiang, Yulan Hu +7
Critique-guided reinforcement learning (RL) has emerged as a powerful paradigm for training LLM agents by augmenting sparse outcome rewards with natural-language feedback. However,…
NGENT: Next-Generation AI Agents Must Integrate Multi-Domain Abilities to Achieve Artificial General Intelligence
Zhicong Li, Hangyu Mao, Jiangjin Yin +4
This paper argues that the next generation of AI agent (NGENT) should integrate across-domain abilities to advance toward Artificial General Intelligence (AGI). Although current AI…
DMQR-RAG: Diverse Multi-Query Rewriting for RAG
Zhicong Li, Jiahao Wang, Zhishu Jiang +7
Large language models often encounter challenges with static knowledge and hallucinations, which undermine their reliability. Retrieval-augmented generation (RAG) mitigates these i…
Exploring the Limitations of Mamba in COPY and CoT Reasoning
Ruifeng Ren, Zhicong Li, Yong Liu
Transformers have become the backbone of modern Large Language Models (LLMs); however, their inference overhead grows linearly with the sequence length, posing challenges for model…
Understanding Fairness Surrogate Functions in Algorithmic Fairness
Wei Yao, Zhanke Zhou, Zhicong Li +2
It has been observed that machine learning algorithms exhibit biased predictions against certain population groups. To mitigate such bias while achieving comparable accuracy, a pro…