Papers with Natural Question
Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval (2022.acl-long)
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| Challenge: | Recent research shows that fine-tuning dense retrievers to realize their capacity requires carefully designed fine-cuning techniques. |
| Approach: | They propose a pre-training architecture that learns to condense information into the dense vector through LM pre-training and a coCondenser architecture which adds an unsupervised corpus-level contrastive loss to warm up the passage embedding space. |
| Outcome: | The proposed architecture reduces the need for heavy data engineering and large batch training. |
Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study (2023.emnlp-main)
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Boxin Wang, Wei Ping, Peng Xu, Lawrence McAfee, Zihan Liu, Mohammad Shoeybi, Yi Dong, Oleksii Kuchaiev, Bo Li, Chaowei Xiao, Anima Anandkumar, Bryan Catanzaro
| Challenge: | a recent study shows that retrieval-augmented LMs can improve text generation quality and accuracy. |
| Approach: | They propose a model that reproduces RETRO parameters while retrieving a text corpus . they find RETRO outperforms GPT on text generation with less repetition . |
| Outcome: | The proposed model outperforms standard retrieval-augmented GPT and retrieval augmented GTP on text generation and accuracy tasks. |