Papers by Eunyee Koh
RaDA: Retrieval-augmented Web Agent Planning with LLMs (2024.findings-acl)
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| Challenge: | Agents powered by large language models inherit important limitations such as the restricted context length, dependency on human-engineered exemplars, and insufficient generalization. |
| Approach: | They propose a novel planning method for Web agents that disentangles planning into two stages: for a new given task, it decomposes tasks into high-level subtasks; and then iteratively synthesizes actions based on dynamically retrieved exemplars. |
| Outcome: | The proposed method decomposes tasks into high-level subtasks and iteratively synthesizes actions based on dynamically retrieved exemplars. |
“It doesn’t look good for a date”: Transforming Critiques into Preferences for Conversational Recommendation Systems (2021.emnlp-main)
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| Challenge: | Conversational recommendation systems (CRSs) aim to refine options over multiple turns of a conversation, but they are not as flexible as real conversations. |
| Approach: | They propose a method for transforming a user critique into a positive preference . they use a large neural language model to perform critique-to-preference transformation . |
| Outcome: | The proposed method improves recommendations in restaurant domain using a new dataset of restaurant critiques. |