most citedHarnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

151 citations · 163 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2023

SMURF-THP: Score Matching-based UnceRtainty quantiFication for Transformer Hawkes Process

Zichong Li, Yanbo Xu, Simiao Zuo +4

Transformer Hawkes process models have shown to be successful in modeling event sequence data. However, most of the existing training methods rely on maximizing the likelihood of e…

cs.CL2023

Graph Reasoning for Question Answering with Triplet Retrieval

Shiyang Li, Yifan Gao, Haoming Jiang +5

Answering complex questions often requires reasoning over knowledge graphs (KGs). State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which ar…

cs.CL20233 cited

CCGen: Explainable Complementary Concept Generation in E-Commerce

Jie Huang, Yifan Gao, Zheng Li +7

We propose and study Complementary Concept Generation (CCGen): given a concept of interest, e.g., "Digital Cameras", generating a list of complementary concepts, e.g., 1) Camera Le…

cs.CL2023151 cited

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

Jingfeng Yang, Hongye Jin, Ruixiang Tang +5

This paper presents a comprehensive and practical guide for practitioners and end-users working with Large Language Models (LLMs) in their downstream natural language processing (N…

cs.CL20239 cited

HomoDistil: Homotopic Task-Agnostic Distillation of Pre-trained Transformers

Chen Liang, Haoming Jiang, Zheng Li +3

Knowledge distillation has been shown to be a powerful model compression approach to facilitate the deployment of pre-trained language models in practice. This paper focuses on tas…