76 citations · 139 across the 25 of their papers we have counts for
14 papers · 1 filter
CLIMB: Confidence-Guided Complementary Evidence for Multimodal Retrieval-Augmented Generation
Hang Gao, Wujiang Xu, Zhixing Zhang +3
Multimodal large language models (MLLMs) have shown strong visual reasoning abilities, but knowledge-intensive visual question answering often requires external textual evidence be…
Opera: A Verbal Critic Framework for Long-horizon Coding Agents
Kai Mei, Zhiyuan Hu, Yutong Dai +7
Long-horizon coding agents need timely corrections, yet feedback can be ineffective or even harmful when it misjudges ongoing work or fails to address the underlying problem. Exist…
Beyond Solo and Consistency: Vindicating Multi-Agent Debate via Conditional Progressive Pruning
Ruosong Ye, Caiqi Zhang, Jiahao Li +9
Large Language Model (LLM) based Multi-Agent Debate (MAD) is one of the most effective test time scaling techniques. Through multi-round communication, agents complement each other…
MemGym: a Long-Horizon Memory Environment for LLM Agents
Wujiang Xu, Yu Wang, Kai Mei +8
Memory is a central capability for LLM agents operating across long-horizon tasks. Existing memory benchmarks predominantly evaluate retention of personalized information in multi-…
AEL: Evolving Agent Harness in Open-Ended Environments
Wujiang Xu, Jiaojiao Han, Minghao Guo +4
LLM Agents Harnesses are hand-designed and stay fixed, so agents accumulate experience but never learn how to use it: which memories to retrieve, when retrieved evidence is mislead…
Pooling and Semantic Shift: The Fundamental Challenges in Long Text Embedding and Retrieval
Hang Gao, Wujiang Xu, Kai Mei +1
Transformer-based embedding models frequently exhibit geometric pathologies, such as anisotropy and length-induced representation collapse, which can degrade downstream retrieval p…
R-WoM: Retrieval-augmented World Model For Computer-use Agents
Kai Mei, Jiang Guo, Shuaichen Chang +4
Large Language Models (LLMs) can serve as world models to enhance agent decision-making in digital environments by simulating future states and predicting action outcomes, potentia…
iAgent: LLM Agent as a Shield between User and Recommender Systems
Wujiang Xu, Yunxiao Shi, Zujie Liang +6
Traditional recommender systems usually take the user-platform paradigm, where users are directly exposed under the control of the platform's recommendation algorithms. However, th…
A-MEM: Agentic Memory for LLM Agents
Wujiang Xu, Zujie Liang, Kai Mei +3
While large language model (LLM) agents can effectively use external tools for complex real-world tasks, they require memory systems to leverage historical experiences. Current mem…
Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding
Mingyu Jin, Kai Mei, Wujiang Xu +5
Large language models (LLMs) have achieved remarkable success in contextual knowledge understanding. In this paper, we show that these concentrated massive values consistently emer…
AutoFlow: Automated Workflow Generation for Large Language Model Agents
Zelong Li, Shuyuan Xu, Kai Mei +6
Recent advancements in Large Language Models (LLMs) have shown significant progress in understanding complex natural language. One important application of LLM is LLM-based AI Agen…
AIOS Compiler: LLM as Interpreter for Natural Language Programming and Flow Programming of AI Agents
Shuyuan Xu, Zelong Li, Kai Mei +1
Since their inception, programming languages have trended towards greater readability and lower barriers for programmers. Following this trend, natural language can be a promising…
Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?
Mingyu Jin, Qinkai Yu, Jingyuan Huang +10
Large language models (LLMs) have shown remarkable performances across a wide range of tasks. However, the mechanisms by which these models encode tasks of varying complexities rem…
What if LLMs Have Different World Views: Simulating Alien Civilizations with LLM-based Agents
Zhaoqian Xue, Beichen Wang, Suiyuan Zhu +5
This study introduces "CosmoAgent," an innovative artificial intelligence system that utilizes Large Language Models (LLMs) to simulate complex interactions between human and extra…