2 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
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…