Papers by Yoonsang Lee
Crafting In-context Examples according to LMs’ Parametric Knowledge (2024.findings-naacl)
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| Challenge: | In-context examples can improve the performance of knowledge-rich tasks such as question answering by triggering a language model to surface information stored in its parametric knowledge. |
| Approach: | They propose to construct in-context example sets based on model's parametric knowledge by prompting models with 'unknown' examples. |
| Outcome: | The proposed model can perform better on in-context examples in three multi-answer question answering datasets, and prompting with ‘unknown’ examples decreases the performance. |
Disentangling Questions from Query Generation for Task-Adaptive Retrieval (2024.findings-emnlp)
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| Challenge: | Existing work generates synthetic queries from domain-specific documents to jointly train the retriever. |
| Approach: | They propose a query generator that better adapts to wide search intents expressed in the BeIR benchmark. |
| Outcome: | The proposed query generator outperforms baselines and existing models on tasks with underexplored intents while using a query generator 47 times smaller than the previous state-of-the-art. |