most citedPre-trained Language Model for Web-scale Retrieval in Baidu Search

4 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.IR2022

PILE: Pairwise Iterative Logits Ensemble for Multi-Teacher Labeled Distillation

Lianshang Cai, Linhao Zhang, Dehong Ma +6

Pre-trained language models have become a crucial part of ranking systems and achieved very impressive effects recently. To maintain high performance while keeping efficient comput…

cs.IR2022

Incorporating Explicit Knowledge in Pre-trained Language Models for Passage Re-ranking

Qian Dong, Yiding Liu, Suqi Cheng +4

Passage re-ranking is to obtain a permutation over the candidate passage set from retrieval stage. Re-rankers have been boomed by Pre-trained Language Models (PLMs) due to their ov…

cs.IR20211 cited

Pre-trained Language Model based Ranking in Baidu Search

Lixin Zou, Shengqiang Zhang, Hengyi Cai +8

As the heart of a search engine, the ranking system plays a crucial role in satisfying users' information demands. More recently, neural rankers fine-tuned from pre-trained languag…

cs.IR20214 cited

Pre-trained Language Model for Web-scale Retrieval in Baidu Search

Yiding Liu, Guan Huang, Jiaxiang Liu +7

Retrieval is a crucial stage in web search that identifies a small set of query-relevant candidates from a billion-scale corpus. Discovering more semantically-related candidates in…

cs.CL2021

First Target and Opinion then Polarity: Enhancing Target-opinion Correlation for Aspect Sentiment Triplet Extraction

Lianzhe Huang, Peiyi Wang, Sujian Li +5

Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from a sentence, including target entities, associated sentiment polarities, and opinion spans which rationalize…