Exploring the Potential of Large Language Models in Generating Code-Tracing Questions for Introductory Programming Courses

1 code implementation • 23 Oct 2023 • Aysa Xuemo Fan, Ranran Haoran Zhang, Luc Paquette, Rui Zhang

In this paper, we explore the application of large language models (LLMs) for generating code-tracing questions in introductory programming courses.

ConEntail: An Entailment-based Framework for Universal Zero and Few Shot Classification with Supervised Contrastive Pretraining

1 code implementation • 14 Oct 2022 • Ranran Haoran Zhang, Aysa Xuemo Fan, Rui Zhang

To fill these gaps, we propose ConEntail, a new framework for universal zero and few shot classification with supervised contrastive pretraining.

Classification Natural Language Inference +2

Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction

1 code implementation • Findings of the Association for Computational Linguistics 2020 • Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan, Heng Ji, Daojian Zeng, Fei Cheng, Daisuke Kawahara, Sadao Kurohashi

We propose a novel Sequence-to-Unordered-Multi-Tree (Seq2UMTree) model to minimize the effects of exposure bias by limiting the decoding length to three within a triplet and removing the order among triplets.

Joint Entity and Relation Extraction Relation