Exploring the benefits of training expert language models over instruction tuning J Jang, S Kim, S Ye, D Kim, L Logeswaran, M Lee, K Lee, M Seo International Conference on Machine Learning, 14702-14729, 2023 | 35 | 2023 |
Flask: Fine-grained language model evaluation based on alignment skill sets S Ye, D Kim, S Kim, H Hwang, S Kim, Y Jo, J Thorne, J Kim, M Seo arXiv preprint arXiv:2307.10928, 2023 | 26 | 2023 |
Selfee: Iterative self-revising llm empowered by self-feedback generation S Ye, Y Jo, D Kim, S Kim, H Hwang, M Seo Blog post, 2023 | 25 | 2023 |
The cot collection: Improving zero-shot and few-shot learning of language models via chain-of-thought fine-tuning S Kim, SJ Joo, D Kim, J Jang, S Ye, J Shin, M Seo arXiv preprint arXiv:2305.14045, 2023 | 24 | 2023 |
Guess the instruction! flipped learning makes language models stronger zero-shot learners S Ye, D Kim, J Jang, J Shin, M Seo arXiv preprint arXiv:2210.02969, 2022 | 15 | 2022 |
Guess the instruction! making language models stronger zero-shot learners S Ye, D Kim, J Jang, J Shin, M Seo arXiv preprint arXiv:2210.02969, 2022 | 12 | 2022 |
Retrieval of soft prompt enhances zero-shot task generalization S Ye, J Jang, D Kim, Y Jo, M Seo arXiv preprint arXiv:2210.03029, 2022 | 11 | 2022 |
How Well Do Large Language Models Truly Ground? H Lee, S Joo, C Kim, J Jang, D Kim, KW On, M Seo arXiv preprint arXiv:2311.09069, 2023 | 2 | 2023 |
Self-Explore to Avoid the Pit: Improving the Reasoning Capabilities of Language Models with Fine-grained Rewards H Hwang, D Kim, S Kim, S Ye, M Seo arXiv preprint arXiv:2404.10346, 2024 | | 2024 |
Semiparametric Token-Sequence Co-Supervision H Lee, D Kim, J Jun, S Joo, J Jang, KW On, M Seo arXiv preprint arXiv:2403.09024, 2024 | | 2024 |
Efficiently Enhancing Zero-Shot Performance of Instruction Following Model via Retrieval of Soft Prompt S Ye, J Jang, D Kim, Y Jo, M Seo Findings of the Association for Computational Linguistics: EMNLP 2023, 12288 …, 2023 | | 2023 |