74 citations · 272 across the 12 of their papers we have counts for
12 papers
GLS-CSC: A Simple but Effective Strategy to Mitigate Chinese STM Models' Over-Reliance on Superficial Clue
Yanrui Du, Sendong Zhao, Yuhan Chen +5
Pre-trained models have achieved success in Chinese Short Text Matching (STM) tasks, but they often rely on superficial clues, leading to a lack of robust predictions. To address t…
Don't Ignore Dual Logic Ability of LLMs while Privatizing: A Data-Intensive Analysis in Medical Domain
Yanrui Du, Sendong Zhao, Muzhen Cai +4
Extensive studies have been devoted to privatizing general-domain Large Language Models (LLMs) as Domain-Specific LLMs via feeding specific-domain data. However, these privatizatio…
Dense Text Retrieval based on Pretrained Language Models: A Survey
Wayne Xin Zhao, Jing Liu, Ruiyang Ren +1
Text retrieval is a long-standing research topic on information seeking, where a system is required to return relevant information resources to user's queries in natural language.…
DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine
Yifu Qiu, Hongyu Li, Yingqi Qu +5
In this paper, we present DuReader_retrieval, a large-scale Chinese dataset for passage retrieval. DuReader_retrieval contains more than 90K queries and over 8M unique passages fro…
RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking
Ruiyang Ren, Yingqi Qu, Jing Liu +5
In various natural language processing tasks, passage retrieval and passage re-ranking are two key procedures in finding and ranking relevant information. Since both the two proced…
PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrieval
Ruiyang Ren, Shangwen Lv, Yingqi Qu +6
Recently, dense passage retrieval has become a mainstream approach to finding relevant information in various natural language processing tasks. A number of studies have been devot…
RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering
Yingqi Qu, Yuchen Ding, Jing Liu +6
In open-domain question answering, dense passage retrieval has become a new paradigm to retrieve relevant passages for finding answers. Typically, the dual-encoder architecture is…
DuReader_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World Applications
Hongxuan Tang, Hongyu Li, Jing Liu +3
Machine reading comprehension (MRC) is a crucial task in natural language processing and has achieved remarkable advancements. However, most of the neural MRC models are still far…
CoKE: Contextualized Knowledge Graph Embedding
Quan Wang, Pingping Huang, Haifeng Wang +6
Knowledge graph embedding, which projects symbolic entities and relations into continuous vector spaces, is gaining increasing attention. Previous methods allow a single static emb…
Adaptations of ROUGE and BLEU to Better Evaluate Machine Reading Comprehension Task
An Yang, Kai Liu, Jing Liu +2
Current evaluation metrics to question answering based machine reading comprehension (MRC) systems generally focus on the lexical overlap between the candidate and reference answer…
Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification
Yizhong Wang, Kai Liu, Jing Liu +5
Machine reading comprehension (MRC) on real web data usually requires the machine to answer a question by analyzing multiple passages retrieved by search engine. Compared with MRC…
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications
Wei He, Kai Liu, Jing Liu +10
This paper introduces DuReader, a new large-scale, open-domain Chinese ma- chine reading comprehension (MRC) dataset, designed to address real-world MRC. DuReader has three advanta…