Papers by Jisoo Mok
Exploring the Potential of LLMs as Personalized Assistants: Dataset, Evaluation, and Analysis (2025.acl-long)
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| Challenge: | Personalized AI assistants are a challenging application that intertwines multiple problems in LLM research. |
| Approach: | They propose a Llama-3.2-based automated evaluation model that matches human preferences to a conversational dataset. |
| Outcome: | HiCUPID provides a conversational dataset tailored for personalization . the evaluation model closely mirrors human preferences, the researchers show . |
Large-scale Lifelong Learning of In-context Instructions and How to Tackle It (2023.acl-long)
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| Challenge: | In-context instruction learning is a method to improve the target PLM’s instance- and task-level generalization performance as it observes more tasks. |
| Approach: | They propose to fine-tune a Pre-trained Language Model (PLM) on a set of tasks with in-context instructions and to extend this property to a scenario in which tasks are fed to the target PLM in a sequential manner. |
| Outcome: | The proposed method achieves noticeable improvements in both types of generalization, nearly reaching the upper bound performance obtained through joint training. |
Verbal-R3: Verbal Reranker as the Missing Bridge between Retrieval and Reasoning (2026.acl-long)
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| Challenge: | Existing paradigms of Retrieval-Augmented Generation (RAG) are suboptimal due to exposure bias, a mismatch between pre-training data distribution and retrieved information. |
| Approach: | They propose to bridge retrieval results and the LLM’s reasoning ability through Verbal Annotations, analytic narratives that explicitly articulate the logical connection between a search query and retrieved contexts. |
| Outcome: | The proposed framework achieves state-of-the-art performance on complex Question Answering benchmarks validating the effectiveness of the proposed framework. |