44 citations · 142 across the 15 of their papers we have counts for
16 papers
Hybrid Retrieval and Multi-stage Text Ranking Solution at TREC 2022 Deep Learning Track
Guangwei Xu, Yangzhao Zhang, Longhui Zhang +3
Large-scale text retrieval technology has been widely used in various practical business scenarios. This paper presents our systems for the TREC 2022 Deep Learning Track. We explai…
Youku-mPLUG: A 10 Million Large-scale Chinese Video-Language Dataset for Pre-training and Benchmarks
Haiyang Xu, Qinghao Ye, Xuan Wu +13
To promote the development of Vision-Language Pre-training (VLP) and multimodal Large Language Model (LLM) in the Chinese community, we firstly release the largest public Chinese h…
Retrieval Oriented Masking Pre-training Language Model for Dense Passage Retrieval
Dingkun Long, Yanzhao Zhang, Guangwei Xu +1
Pre-trained language model (PTM) has been shown to yield powerful text representations for dense passage retrieval task. The Masked Language Modeling (MLM) is a major sub-task of t…
HLATR: Enhance Multi-stage Text Retrieval with Hybrid List Aware Transformer Reranking
Yanzhao Zhang, Dingkun Long, Guangwei Xu +1
Deep pre-trained language models (e,g. BERT) are effective at large-scale text retrieval task. Existing text retrieval systems with state-of-the-art performance usually adopt a ret…
Robust Self-Augmentation for Named Entity Recognition with Meta Reweighting
Linzhi Wu, Pengjun Xie, Jie Zhou +4
Self-augmentation has received increasing research interest recently to improve named entity recognition (NER) performance in low-resource scenarios. Token substitution and mixup a…
Multi-CPR: A Multi Domain Chinese Dataset for Passage Retrieval
Dingkun Long, Qiong Gao, Kuan Zou +7
Passage retrieval is a fundamental task in information retrieval (IR) research, which has drawn much attention recently. In the English field, the availability of large-scale annot…
Identifying Chinese Opinion Expressions with Extremely-Noisy Crowdsourcing Annotations
Xin Zhang, Guangwei Xu, Yueheng Sun +3
Recent works of opinion expression identification (OEI) rely heavily on the quality and scale of the manually-constructed training corpus, which could be extremely difficult to sat…
Parallel Instance Query Network for Named Entity Recognition
Yongliang Shen, Xiaobin Wang, Zeqi Tan +5
Named entity recognition (NER) is a fundamental task in natural language processing. Recent works treat named entity recognition as a reading comprehension task, constructing type-…
AISHELL-NER: Named Entity Recognition from Chinese Speech
Boli Chen, Guangwei Xu, Xiaobin Wang +3
Named Entity Recognition (NER) from speech is among Spoken Language Understanding (SLU) tasks, aiming to extract semantic information from the speech signal. NER from speech is usu…
Prompt-Learning for Fine-Grained Entity Typing
Ning Ding, Yulin Chen, Xu Han +6
As an effective approach to tune pre-trained language models (PLMs) for specific tasks, prompt-learning has recently attracted much attention from researchers. By using \textit{clo…
Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognition
Xin Zhang, Guangwei Xu, Yueheng Sun +2
Crowdsourcing is regarded as one prospective solution for effective supervised learning, aiming to build large-scale annotated training data by crowd workers. Previous studies focu…
Few-NERD: A Few-Shot Named Entity Recognition Dataset
Ning Ding, Guangwei Xu, Yulin Chen +5
Recently, considerable literature has grown up around the theme of few-shot named entity recognition (NER), but little published benchmark data specifically focused on the practica…
Probing BERT in Hyperbolic Spaces
Boli Chen, Yao Fu, Guangwei Xu +4
Recently, a variety of probing tasks are proposed to discover linguistic properties learned in contextualized word embeddings. Many of these works implicitly assume these embedding…
Prototypical Representation Learning for Relation Extraction
Ning Ding, Xiaobin Wang, Yao Fu +7
Recognizing relations between entities is a pivotal task of relational learning. Learning relation representations from distantly-labeled datasets is difficult because of the abund…
Keyphrase Extraction with Dynamic Graph Convolutional Networks and Diversified Inference
Haoyu Zhang, Dingkun Long, Guangwei Xu +3
Keyphrase extraction (KE) aims to summarize a set of phrases that accurately express a concept or a topic covered in a given document. Recently, Sequence-to-Sequence (Seq2Seq) base…
Coupling Distant Annotation and Adversarial Training for Cross-Domain Chinese Word Segmentation
Ning Ding, Dingkun Long, Guangwei Xu +4
Fully supervised neural approaches have achieved significant progress in the task of Chinese word segmentation (CWS). Nevertheless, the performance of supervised models tends to dr…