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.
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.
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.