12 citations · 26 across the 8 of their papers we have counts for
8 papers
L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering
Xinzhou Jin, Jintang Li, Liang Chen +6
Graph neural networks (GNNs) have recently emerged as an effective approach to model neighborhood signals in collaborative filtering. Towards this research line, graph contrastive…
CodeR: Issue Resolving with Multi-Agent and Task Graphs
Dong Chen, Shaoxin Lin, Muhan Zeng +14
GitHub issue resolving recently has attracted significant attention from academia and industry. SWE-bench is proposed to measure the performance in resolving issues. In this paper,…
Using LLM to select the right SQL Query from candidates
Zhenwen Li, Tao Xie
Text-to-SQL models can generate a list of candidate SQL queries, and the best query is often in the candidate list, but not at the top of the list. An effective re-rank method can…
Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment
Jie Zhu, Leye Wang, Xiao Han +2
The size of deep learning models in artificial intelligence (AI) software is increasing rapidly, hindering the large-scale deployment on resource-restricted devices (e.g., smartpho…
OlaGPT: Empowering LLMs With Human-like Problem-Solving Abilities
Yuanzhen Xie, Tao Xie, Mingxiong Lin +7
In most current research, large language models (LLMs) are able to perform reasoning tasks by generating chains of thought through the guidance of specific prompts. However, there…
Reliability Assurance for Deep Neural Network Architectures Against Numerical Defects
Linyi Li, Yuhao Zhang, Luyao Ren +2
With the widespread deployment of deep neural networks (DNNs), ensuring the reliability of DNN-based systems is of great importance. Serious reliability issues such as system failu…