87 citations · 390 across the 41 of their papers we have counts for
12 papers · 1 filter
Text2Analysis: A Benchmark of Table Question Answering with Advanced Data Analysis and Unclear Queries
Xinyi He, Mengyu Zhou, Xinrun Xu +9
Tabular data analysis is crucial in various fields, and large language models show promise in this area. However, current research mostly focuses on rudimentary tasks like Text2SQL…
Professional Network Matters: Connections Empower Person-Job Fit
Hao Chen, Lun Du, Yuxuan Lu +6
Online recruitment platforms typically employ Person-Job Fit models in the core service that automatically match suitable job seekers with appropriate job positions. While existing…
TAP4LLM: Table Provider on Sampling, Augmenting, and Packing Semi-structured Data for Large Language Model Reasoning
Yuan Sui, Jiaru Zou, Mengyu Zhou +4
Table reasoning tasks have shown remarkable progress with the development of large language models (LLMs), which involve interpreting and drawing conclusions from tabular data base…
Text-to-Image Generation for Abstract Concepts
Jiayi Liao, Xu Chen, Qiang Fu +5
Recent years have witnessed the substantial progress of large-scale models across various domains, such as natural language processing and computer vision, facilitating the express…
SoTaNa: The Open-Source Software Development Assistant
Ensheng Shi, Fengji Zhang, Yanlin Wang +6
Software development plays a crucial role in driving innovation and efficiency across modern societies. To meet the demands of this dynamic field, there is a growing need for an ef…
On Manipulating Signals of User-Item Graph: A Jacobi Polynomial-based Graph Collaborative Filtering
Jiayan Guo, Lun Du, Xu Chen +5
Collaborative filtering (CF) is an important research direction in recommender systems that aims to make recommendations given the information on user-item interactions. Graph CF h…
Enabling and Analyzing How to Efficiently Extract Information from Hybrid Long Documents with LLMs
Chongjian Yue, Xinrun Xu, Xiaojun Ma +6
Large Language Models (LLMs) demonstrate exceptional performance in textual understanding and tabular reasoning tasks. However, their ability to comprehend and analyze hybrid text,…
GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking
Jiayan Guo, Lun Du, Hengyu Liu +3
Large language models~(LLM) like ChatGPT have become indispensable to artificial general intelligence~(AGI), demonstrating excellent performance in various natural language process…
Causal-Based Supervision of Attention in Graph Neural Network: A Better and Simpler Choice towards Powerful Attention
Hongjun Wang, Jiyuan Chen, Lun Du +3
Recent years have witnessed the great potential of attention mechanism in graph representation learning. However, while variants of attention-based GNNs are setting new benchmarks…
Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond
Ensheng Shi, Yanlin Wang, Hongyu Zhang +4
Recently, fine-tuning pre-trained code models such as CodeBERT on downstream tasks has achieved great success in many software testing and analysis tasks. While effective and preva…
Homophily-oriented Heterogeneous Graph Rewiring
Jiayan Guo, Lun Du, Wendong Bi +6
With the rapid development of the World Wide Web (WWW), heterogeneous graphs (HG) have explosive growth. Recently, heterogeneous graph neural network (HGNN) has shown great potenti…
Robust Mid-Pass Filtering Graph Convolutional Networks
Jincheng Huang, Lun Du, Xu Chen +3
Graph convolutional networks (GCNs) are currently the most promising paradigm for dealing with graph-structure data, while recent studies have also shown that GCNs are vulnerable t…