Papers with ODQA models
Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints (2021.acl-short)
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| Challenge: | Adaptive Computation (AC) has been shown to be effective in improving the efficiency of Open-Domain Question Answering systems. |
| Approach: | They propose an AC method that can be applied to an existing ODQA model and can be trained efficiently on a single GPU. |
| Outcome: | The proposed method improves upon a state-of-the-art model on two datasets and is more accurate than previous AC methods due to the stronger base ODQA model. |
A Survey for Efficient Open Domain Question Answering (2023.acl-long)
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| Challenge: | Open domain question answering (ODQA) is a longstanding task that can answer factoid questions without explicit evidence in natural language processing (NLP). |
| Approach: | They propose to use open domain question answering to answer factual questions from a large knowledge corpus without explicit evidence. |
| Outcome: | The proposed models can answer factoid questions from a large knowledge corpus without explicit evidence. |