Sukmin Cho

According to our database, Sukmin Cho authored at least 9 papers between 2022 and 2024.

Collaborative distances:

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

2024

Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity.

Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong C. Park

CoRR, 2024

2023

Test-Time Self-Adaptive Small Language Models for Question Answering.

Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong C. Park

CoRR, 2023

Test-Time Self-Adaptive Small Language Models for Question Answering.

Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong Park

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

Improving Zero-shot Reader by Reducing Distractions from Irrelevant Documents in Open-Domain Question Answering.

Sukmin Cho, Jeongyeon Seo, Soyeong Jeong, Jong C. Park

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

Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-ranker.

Sukmin Cho, Soyeong Jeong, Jeongyeon Seo, Jong C. Park

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

2022

Non-Autoregressive Sign Language Production via Knowledge Distillation.

Eui Jun Hwang, Jung-Ho Kim, Sukmin Cho, Jong C. Park

CoRR, 2022

Sign Language Production With Avatar Layering: A Critical Use Case over Rare Words.

Jung-Ho Kim, Eui Jun Hwang, Sukmin Cho, Du Hui Lee, Jong C. Park

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

Augmenting Document Representations for Dense Retrieval with Interpolation and Perturbation.

Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, Jong C. Park

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

Query Generation with External Knowledge for Dense Retrieval.

Sukmin Cho, Soyeong Jeong, Wonsuk Yang, Jong C. Park

Proceedings of Deep Learning Inside Out: The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, 2022