Taewon Yun

According to our database, Taewon Yun authored at least 8 papers between 2024 and 2026.

Collaborative distances:

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

2026

What Makes a Sale? Rethinking End-to-End Seller-Buyer Retail Dynamics with LLM Agents.

Jeonghwan Choi, Jibin Hwang, Gyeonghun Sun, Minjeong Ban, Taewon Yun, Hyeonjae Cheon, Hwanjun Song

CoRR, April, 2026

2025

ReFeed: Multi-dimensional Summarization Refinement with Reflective Reasoning on Feedback.

Taewon Yun, Jihwan Oh, Hyangsuk Min, Yuho Lee, Jihwan Bang, Jason Cai, Hwanjun Song

CoRR, March, 2025

Learning to Summarize from LLM-generated Feedback.

Hwanjun Song, Taewon Yun, Yuho Lee, Jihwan Oh, Gihun Lee, Jason Cai, Hang Su

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

Towards a Holistic and Automated Evaluation Framework for Multi-Level Comprehension of LLMs in Book-Length Contexts.

Yuho Lee, Jiaqi Deng, Nicole Hee-Yeon Kim, Hyangsuk Min, Taewon Yun, Minjeong Ban, Kim Yul, Hwanjun Song

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Learning to Verify Summary Facts with Fine-Grained LLM Feedback.

Jihwan Oh, Jeonghwan Choi, Nicole Hee-Yeon Kim, Taewon Yun, Hwanjun Song

Proceedings of the 31st International Conference on Computational Linguistics, 2025

Towards Multi-dimensional Evaluation of LLM Summarization across Domains and Languages.

Hyangsuk Min, Yuho Lee, Minjeong Ban, Jiaqi Deng, Nicole Hee-Yeon Kim, Taewon Yun, Hang Su, Jason Cai, Hwanjun Song

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

2024

Learning to Summarize from LLM-generated Feedback.

Hwanjun Song, Taewon Yun, Yuho Lee, Gihun Lee, Jason Cai, Hang Su

CoRR, 2024

UniSumEval: Towards Unified, Fine-grained, Multi-dimensional Summarization Evaluation for LLMs.

Yuho Lee, Taewon Yun, Jason Cai, Hang Su, Hwanjun Song

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024