Can LLMs Effectively Leverage Graph Structural Information through
Prompts, and Why?

Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?

28 September 2023

Jiaqi Ma

Papers citing "Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?"

8 / 8 papers shown

Title
CATP-LLM: Empowering Large Language Models for Cost-Aware Tool Planning Duo Wu J. Wang Yuan Meng Yanning Zhang Le Sun Zhi Wang 96 0 0 25 Nov 2024
Graph Linearization Methods for Reasoning on Graphs with Large Language Models Christos Xypolopoulos Guokan Shang Xiao Fei Giannis Nikolentzos Hadi Abdine Iakovos Evdaimon Michail Chatzianastasis Giorgos Stamou Michalis Vazirgiannis 19 1 0 25 Oct 2024
GraphText: Graph Reasoning in Text Space Jianan Zhao Le Zhuo Yikang Shen Meng Qu Kai Liu Michael M. Bronstein Zhaocheng Zhu Jian Tang 102 37 0 02 Oct 2023
Can we trust the evaluation on ChatGPT? Rachith Aiyappa Jisun An Haewoon Kwak Yong-Yeol Ahn ELM ALM LLMAG AI4MH LRM 106 76 0 22 Mar 2023
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 2,712 0 24 May 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 315 8,261 0 28 Jan 2022
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 264 1,798 0 14 Dec 2020
Grale: Designing Networks for Graph Learning Jonathan J. Halcrow A. Mosoi Sam Ruth Bryan Perozzi GNN 63 43 0 23 Jul 2020