activity
20212026
most citedFirst Target and Opinion then Polarity: Enhancing Target-opinion Correlation for Aspect Sentiment Triplet Extraction

28 citations · 49 across the 14 of their papers we have counts for

collaborators

14 papers

cs.IR2026

Multi Interests for Joint Search-Recommendation Modeling

Xiangchen Pan, Wei Wei, Huakang Niu +1

Search and recommendation are crucial for understanding user preferences. More and more studies are attempting to jointly model search behavior and recommendation behavior, by inte…

cs.CL2024★ 4 cited

Improving the Robustness of Large Language Models via Consistency Alignment

Yukun Zhao, Lingyong Yan, Weiwei Sun +6

Large language models (LLMs) have shown tremendous success in following user instructions and generating helpful responses. Nevertheless, their robustness is still far from optimal…

cs.IR2024★ 1 cited

MA4DIV: Multi-Agent Reinforcement Learning for Search Result Diversification

Yiqun Chen, Jiaxin Mao, Yi Zhang +7

Search result diversification (SRD), which aims to ensure that documents in a ranking list cover a broad range of subtopics, is a significant and widely studied problem in Informat…

cs.CL2023

DiQAD: A Benchmark Dataset for End-to-End Open-domain Dialogue Assessment

Yukun Zhao, Lingyong Yan, Weiwei Sun +5

Dialogue assessment plays a critical role in the development of open-domain dialogue systems. Existing work are uncapable of providing an end-to-end and human-epistemic assessment…

cs.CL2023★ 2 cited

Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method

Yukun Zhao, Lingyong Yan, Weiwei Sun +6

Large Language Models (LLMs) have shown great potential in Natural Language Processing (NLP) tasks. However, recent literature reveals that LLMs generate nonfactual responses inter…

cs.IR2023

Pretrained Language Model based Web Search Ranking: From Relevance to Satisfaction

Canjia Li, Xiaoyang Wang, Dongdong Li +6

Search engine plays a crucial role in satisfying users' diverse information needs. Recently, Pretrained Language Models (PLMs) based text ranking models have achieved huge success…

cs.IR2023

Layout-aware Webpage Quality Assessment

Anfeng Cheng, Yiding Liu, Weibin Li +6

Identifying high-quality webpages is fundamental for real-world search engines, which can fulfil users' information need with the less cognitive burden. Early studies of \emph{webp…

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★ 4 cited

Approximated Doubly Robust Search Relevance Estimation

Lixin Zou, Changying Hao, Hengyi Cai +6

Extracting query-document relevance from the sparse, biased clickthrough log is among the most fundamental tasks in the web search system. Prior art mainly learns a relevance judgm…

cs.IR2022★ 5 cited

A Simple yet Effective Framework for Active Learning to Rank

Qingzhong Wang, Haifang Li, Haoyi Xiong +7

While China has become the biggest online market in the world with around 1 billion internet users, Baidu runs the world largest Chinese search engine serving more than hundreds of…

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.IR2021★ 1 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.IR2021★ 4 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★ 28 cited

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…