Papers with generation capability
Divide and Conquer: Legal Concept-guided Criminal Court View Generation (2024.findings-emnlp)
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| Challenge: | Existing methods for creating rationales for criminal cases do not pay enough attention to the important legal concepts. |
| Approach: | They propose a legal concept-guided court view generation framework that generates rationales based on predicted legal concepts . they first divide the court view into sub-views, then employ a solver and verifier to generate and select rationale. |
| Outcome: | The proposed model generates coherent and coherent court views on a real-world criminal case dataset. |
Clues Before Answers: Generation-Enhanced Multiple-Choice QA (2022.naacl-main)
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| Challenge: | Multiple-choice question answering (MCQA) uses text-to-text framework . but, there is an under-utilization of the decoder and knowledge that can be decoded . |
| Approach: | They propose a generative multiple-choice question answering model which generates a clue from the question and leverages it to enhance a reader for MCQA. |
| Outcome: | The proposed model outperforms text-to-text models on multiple MCQA datasets. |