Papers by Joonkee Kim
Re3val: Reinforced and Reranked Generative Retrieval (2024.findings-eacl)
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| Challenge: | generative retrieval models encode pointers to information in a corpus as an index within the model’s parameters. |
| Approach: | They propose a generative retrieval model that leverages contextual information to rerank retrieved page titles and utilizes REINFORCE to maximize rewards generated by constrained decoding. |
| Outcome: | The proposed model can't be tuned for the downstream readers as decoding the page title is a non-differentiable operation. |
HARE: Explainable Hate Speech Detection with Step-by-Step Reasoning (2023.findings-emnlp)
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| Challenge: | Recent benchmarks have attempted to identify and explain hate speech but lack the reasoning to supervise detection models. |
| Approach: | They propose a framework that uses large language models to fill in the gaps in hate speech explanations by using existing annotations. |
| Outcome: | The proposed framework outperforms baselines on SBIC and Implicit Hate using model-generated data and improves generalization to unseen datasets. |