16 citations · 20 across the 5 of their papers we have counts for
5 papers
CAT-probing: A Metric-based Approach to Interpret How Pre-trained Models for Programming Language Attend Code Structure
Nuo Chen, Qiushi Sun, Renyu Zhu +3
Code pre-trained models (CodePTMs) have recently demonstrated significant success in code intelligence. To interpret these models, some probing methods have been applied. However,…
A Neural Network Architecture for Program Understanding Inspired by Human Behaviors
Renyu Zhu, Lei Yuan, Xiang Li +2
Program understanding is a fundamental task in program language processing. Despite the success, existing works fail to take human behaviors as reference in understanding programs.…
A More Compact Object Detector Head Network with Feature Enhancement and Relational Reasoning
Wenchao Zhang, Chong Fu, Xiangshi Chang +3
Modeling implicit feature interaction patterns is of significant importance to object detection tasks. However, in the two-stage detectors, due to the excessive use of hand-crafted…
Looking Beyond Sentence-Level Natural Language Inference for Downstream Tasks
Anshuman Mishra, Dhruvesh Patel, Aparna Vijayakumar +3
In recent years, the Natural Language Inference (NLI) task has garnered significant attention, with new datasets and models achieving near human-level performance on it. However, t…
Disentangling User Interest and Conformity for Recommendation with Causal Embedding
Yu Zheng, Chen Gao, Xiang Li +3
Recommendation models are usually trained on observational interaction data. However, observational interaction data could result from users' conformity towards popular items, whic…