237 citations · 1.2k across the 87 of their papers we have counts for
17 papers · 1 filter
Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese
Zhuosheng Zhang, Hanqing Zhang, Keming Chen +4
Although pre-trained models (PLMs) have achieved remarkable improvements in a wide range of NLP tasks, they are expensive in terms of time and resources. This calls for the study o…
Advances in Multi-turn Dialogue Comprehension: A Survey
Zhuosheng Zhang, Hai Zhao
Training machines to understand natural language and interact with humans is an elusive and essential task of artificial intelligence. A diversity of dialogue systems has been desi…
Multi-tasking Dialogue Comprehension with Discourse Parsing
Yuchen He, Zhuosheng Zhang, Hai Zhao
Multi-party dialogue machine reading comprehension (MRC) raises an even more challenging understanding goal on dialogue with more than two involved speakers, compared with the trad…
Structural Characterization for Dialogue Disentanglement
Xinbei Ma, Zhuosheng Zhang, Hai Zhao
Tangled multi-party dialogue contexts lead to challenges for dialogue reading comprehension, where multiple dialogue threads flow simultaneously within a common dialogue record, in…
Tracing Origins: Coreference-aware Machine Reading Comprehension
Baorong Huang, Zhuosheng Zhang, Hai Zhao
Machine reading comprehension is a heavily-studied research and test field for evaluating new pre-trained language models (PrLMs) and fine-tuning strategies, and recent studies hav…
Sentence-aware Contrastive Learning for Open-Domain Passage Retrieval
Bohong Wu, Zhuosheng Zhang, Jinyuan Wang +1
Training dense passage representations via contrastive learning has been shown effective for Open-Domain Passage Retrieval (ODPR). Existing studies focus on further optimizing by i…
Span Fine-tuning for Pre-trained Language Models
Rongzhou Bao, Zhuosheng Zhang, Hai Zhao
Pre-trained language models (PrLM) have to carefully manage input units when training on a very large text with a vocabulary consisting of millions of words. Previous works have sh…
Enhanced Speaker-aware Multi-party Multi-turn Dialogue Comprehension
Xinbei Ma, Zhuosheng Zhang, Hai Zhao
Multi-party multi-turn dialogue comprehension brings unprecedented challenges on handling the complicated scenarios from multiple speakers and criss-crossed discourse relationship…
Smoothing Dialogue States for Open Conversational Machine Reading
Zhuosheng Zhang, Siru Ouyang, Hai Zhao +2
Conversational machine reading (CMR) requires machines to communicate with humans through multi-turn interactions between two salient dialogue states of decision making and questio…
Cross-lingual Transferring of Pre-trained Contextualized Language Models
Zuchao Li, Kevin Parnow, Hai Zhao +4
Though the pre-trained contextualized language model (PrLM) has made a significant impact on NLP, training PrLMs in languages other than English can be impractical for two reasons:…
Graph-free Multi-hop Reading Comprehension: A Select-to-Guide Strategy
Bohong Wu, Zhuosheng Zhang, Hai Zhao
Multi-hop reading comprehension (MHRC) requires not only to predict the correct answer span in the given passage, but also to provide a chain of supporting evidences for reasoning…
Structural Pre-training for Dialogue Comprehension
Zhuosheng Zhang, Hai Zhao
Pre-trained language models (PrLMs) have demonstrated superior performance due to their strong ability to learn universal language representations from self-supervised pre-training…
Fact-driven Logical Reasoning for Machine Reading Comprehension
Siru Ouyang, Zhuosheng Zhang, Hai Zhao
Recent years have witnessed an increasing interest in training machines with reasoning ability, which deeply relies on accurately and clearly presented clue forms. The clues are us…
Advances in Multi-turn Dialogue Comprehension: A Survey
Zhuosheng Zhang, Hai Zhao
Training machines to understand natural language and interact with humans is an elusive and essential task of artificial intelligence. A diversity of dialogue systems has been desi…
Text Compression-aided Transformer Encoding
Zuchao Li, Zhuosheng Zhang, Hai Zhao +4
Text encoding is one of the most important steps in Natural Language Processing (NLP). It has been done well by the self-attention mechanism in the current state-of-the-art Transfo…
Multi-turn Dialogue Reading Comprehension with Pivot Turns and Knowledge
Zhuosheng Zhang, Junlong Li, Hai Zhao
Multi-turn dialogue reading comprehension aims to teach machines to read dialogue contexts and solve tasks such as response selection and answering questions. The major challenges…
SG-Net: Syntax Guided Transformer for Language Representation
Zhuosheng Zhang, Yuwei Wu, Junru Zhou +3
Understanding human language is one of the key themes of artificial intelligence. For language representation, the capacity of effectively modeling the linguistic knowledge from th…