37 citations · 85 across the 38 of their papers we have counts for
7 papers · 1 filter
Benchmarking Agentic Workflow Generation
Shuofei Qiao, Runnan Fang, Zhisong Qiu +6
Large Language Models (LLMs), with their exceptional ability to handle a wide range of tasks, have driven significant advancements in tackling reasoning and planning tasks, wherein…
Graph-guided Cross-composition Feature Disentanglement for Compositional Zero-shot Learning
Yuxia Geng, Runkai Zhu, Jiaoyan Chen +7
Disentanglement of visual features of primitives (i.e., attributes and objects) has shown exceptional results in Compositional Zero-shot Learning (CZSL). However, due to the featur…
Knowledge Mechanisms in Large Language Models: A Survey and Perspective
Mengru Wang, Yunzhi Yao, Ziwen Xu +10
Understanding knowledge mechanisms in Large Language Models (LLMs) is crucial for advancing towards trustworthy AGI. This paper reviews knowledge mechanism analysis from a novel ta…
Agent Planning with World Knowledge Model
Shuofei Qiao, Runnan Fang, Ningyu Zhang +7
Recent endeavors towards directly using large language models (LLMs) as agent models to execute interactive planning tasks have shown commendable results. Despite their achievement…
KnowAgent: Knowledge-Augmented Planning for LLM-Based Agents
Yuqi Zhu, Shuofei Qiao, Yixin Ou +7
Large Language Models (LLMs) have demonstrated great potential in complex reasoning tasks, yet they fall short when tackling more sophisticated challenges, especially when interact…
EasyInstruct: An Easy-to-use Instruction Processing Framework for Large Language Models
Yixin Ou, Ningyu Zhang, Honghao Gui +9
In recent years, instruction tuning has gained increasing attention and emerged as a crucial technique to enhance the capabilities of Large Language Models (LLMs). To construct hig…
AutoAct: Automatic Agent Learning from Scratch for QA via Self-Planning
Shuofei Qiao, Ningyu Zhang, Runnan Fang +5
Language agents have achieved considerable performance on various complex question-answering tasks by planning with external tools. Despite the incessant exploration in this field,…