most citedEnhancing Automated Software Traceability by Transfer Learning from Open-World Data

4 citations · 7 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2023

A Quantitative Review on Language Model Efficiency Research

Meng Jiang, Hy Dang, Lingbo Tong

Language models (LMs) are being scaled and becoming powerful. Improving their efficiency is one of the core research topics in neural information processing systems. Tay et al. (20…

cs.CL2023

Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions

Zhihan Zhang, Wenhao Yu, Zheng Ning +2

Contrast consistency, the ability of a model to make consistently correct predictions in the presence of perturbations, is an essential aspect in NLP. While studied in tasks such a…

cs.CL2023

Large Language Models are Built-in Autoregressive Search Engines

Noah Ziems, Wenhao Yu, Zhihan Zhang +1

Document retrieval is a key stage of standard Web search engines. Existing dual-encoder dense retrievers obtain representations for questions and documents independently, allowing…

cs.IR2022

On the Relationship Between Counterfactual Explainer and Recommender

Gang Liu, Zhihan Zhang, Zheng Ning +1

Recommender systems employ machine learning models to learn from historical data to predict the preferences of users. Deep neural network (DNN) models such as neural collaborative…

cs.LG20223 cited

Heterogeneous Line Graph Transformer for Math Word Problems

Zijian Hu, Meng Jiang

This paper describes the design and implementation of a new machine learning model for online learning systems. We aim at improving the intelligent level of the systems by enabling…

cs.SE20224 cited

Enhancing Automated Software Traceability by Transfer Learning from Open-World Data

Jinfeng Lin, Amrit Poudel, Wenhao Yu +3

Software requirements traceability is a critical component of the software engineering process, enabling activities such as requirements validation, compliance verification, and sa…