Papers by Kelvin Han
Generating Complex Question Decompositions in the Face of Distribution Shifts (2025.naacl-long)
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| Challenge: | Question decomposition has been found to improve large language models’ (LLMs) performance on complex question answering (QA) however, performance on the task remains dominated by supervised approaches, suggesting room for making LLMs better decomposers. |
| Approach: | They propose to generate synthetic decomposition data with only five annotated examples by extending recent advances in using LLM-as-judge and for reranking in novel ways. |
| Outcome: | The proposed approach generates synthetic decomposition data with only five examples over two benchmark datasets. |
Generating Questions from Wikidata Triples (2022.lrec-1)
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| Challenge: | Existing methods for question generation from knowledge bases rely on extensive pre- and post-processing of the input triple. |
| Approach: | They revisit KBQG using pre training, a new (triple, question) dataset and taking question type into account and provide a more extended KBqg dataset. |
| Outcome: | The proposed approach outperforms existing methods in a standard and in 'zero-shot' setting. |
Multilingual Generation and Answering of Questions from Texts and Knowledge Graphs (2023.findings-emnlp)
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| Challenge: | Existing methods for QG-QA are limited to English, but can be used in other languages. |
| Approach: | They propose to bring multilinguality to multimodal QG-QA by using Brazilian Portuguese and Russian data. |
| Outcome: | The proposed approach outperforms a baseline on English and can handle both languages. |