2 citations · 2 across the 7 of their papers we have counts for
8 papers
Beyond Explicit Edges: Robust Reasoning over Noisy and Sparse Knowledge Graphs
Hang Gao, Dimitris N. Metaxas
GraphRAG is increasingly adopted for converting unstructured corpora into graph structures to enable multi-hop reasoning. However, standard graph algorithms rely heavily on static…
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…
LiteCUA: Computer as MCP Server for Computer-Use Agent on AIOS
Kai Mei, Xi Zhu, Hang Gao +2
We present AIOS 1.0, a novel platform designed to advance computer-use agent (CUA) capabilities through environmental contextualization. While existing approaches primarily focus o…
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…
Auto-Prompt Generation is Not Robust: Prompt Optimization Driven by Pseudo Gradient
Zeru Shi, Zhenting Wang, Yongye Su +5
While automatic prompt generation methods have recently received significant attention, their robustness remains poorly understood. In this paper, we introduce PertBench, a compreh…
Task-Aligned Tool Recommendation for Large Language Models
Hang Gao, Yongfeng Zhang
By augmenting Large Language Models (LLMs) with external tools, their capacity to solve complex problems has been significantly enhanced. However, despite ongoing advancements in t…
Vector Retrieval with Similarity and Diversity: How Hard Is It?
Hang Gao, Dong Deng, Yongfeng Zhang
Dense vector retrieval is an important building block of modern machine learning systems, underlying applications ranging from semantic search to retrieval-augmented generation and…
INMS: Memory Sharing for Large Language Model based Agents
Hang Gao, Yongfeng Zhang
While Large Language Model (LLM) based agents excel at complex tasks, their performance in open-ended scenarios is often constrained by isolated operation and reliance on static da…