221 citations · 587 across the 23 of their papers we have counts for
6 papers · 1 filter
Precise Zero-Shot Dense Retrieval without Relevance Labels
Luyu Gao, Xueguang Ma, Jimmy Lin +1
While dense retrieval has been shown effective and efficient across tasks and languages, it remains difficult to create effective fully zero-shot dense retrieval systems when no re…
Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer
Zhengbao Jiang, Luyu Gao, Jun Araki +4
Systems for knowledge-intensive tasks such as open-domain question answering (QA) usually consist of two stages: efficient retrieval of relevant documents from a large corpus and d…
PAL: Program-aided Language Models
Luyu Gao, Aman Madaan, Shuyan Zhou +5
Large language models (LLMs) have recently demonstrated an impressive ability to perform arithmetic and symbolic reasoning tasks, when provided with a few examples at test time ("f…
RARR: Researching and Revising What Language Models Say, Using Language Models
Luyu Gao, Zhuyun Dai, Panupong Pasupat +8
Language models (LMs) now excel at many tasks such as few-shot learning, question answering, reasoning, and dialog. However, they sometimes generate unsupported or misleading conte…
Long Document Re-ranking with Modular Re-ranker
Luyu Gao, Jamie Callan
Long document re-ranking has been a challenging problem for neural re-rankers based on deep language models like BERT. Early work breaks the documents into short passage-like chunk…
Tevatron: An Efficient and Flexible Toolkit for Dense Retrieval
Luyu Gao, Xueguang Ma, Jimmy Lin +1
Recent rapid advancements in deep pre-trained language models and the introductions of large datasets have powered research in embedding-based dense retrieval. While several good r…