Wing-Lam Mok

According to our database, Wing-Lam Mok authored at least 7 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Curriculum Debiasing: Toward Robust Parameter-Efficient Fine-Tuning Against Dataset Biases.

Mingyu Lee, Yeachan Kim, Wing-Lam Mok, SangKeun Lee

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

C2A: Client-Customized Adaptation for Parameter-Efficient Federated Learning.

Yeachan Kim, Junho Kim, Wing-Lam Mok, Jun-Hyung Park, SangKeun Lee

CoRR, 2024

2023

Improving Bias Mitigation through Bias Experts in Natural Language Understanding.

Eojin Jeon, Mingyu Lee, Juhyeong Park, Yeachan Kim, Wing-Lam Mok, SangKeun Lee

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

SMoP: Towards Efficient and Effective Prompt Tuning with Sparse Mixture-of-Prompts.

Joon-Young Choi, Junho Kim, Jun-Hyung Park, Wing-Lam Mok, SangKeun Lee

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Mitigating Annotation Artifacts in Physical Commonsense Reasoning Benchmark.

Wing-Lam Mok, SungHo Kim

Proceedings of the IEEE International Conference on Big Data, 2023

Client-Customized Adaptation for Parameter-Efficient Federated Learning.

Yeachan Kim, Junho Kim, Wing-Lam Mok, Jun-Hyung Park, SangKeun Lee

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Tutoring Helps Students Learn Better: Improving Knowledge Distillation for BERT with Tutor Network.

Junho Kim, Jun-Hyung Park, Mingyu Lee, Wing-Lam Mok, Joon-Young Choi, SangKeun Lee

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022