Papers by Jianxi Gao
CRAFT: Training-Free Cascaded Retrieval for Tabular QA (2026.acl-long)
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| Challenge: | Existing methods for open-domain table question answering require retraining or fine-tuning on new datasets. |
| Approach: | They propose a zero-shot, cascaded retrieval approach that uses a sparse retrieval model to filter a subset of candidates before applying more expensive dense models as re-rankers. |
| Outcome: | The proposed method outperforms state-of-the-art retrieval models on the NQ-Tables dataset. |
Inferring from Logits: Exploring Best Practices for Decoding-Free Generative Candidate Selection (2025.acl-long)
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| Challenge: | Existing work has been using decoding-free candidate selection methods to obtain candidate probability from initial output logits over vocabulary. |
| Approach: | They propose to evaluate a set of tasks using decoding-free candidate selection methods on a comprehensive set of questions. |
| Outcome: | The proposed methods are evaluated on a set of tasks including five multiple-choice QA tasks with a small candidate pool and four clinical decision tasks with 10k+ options. |