activity
20192023
most citedHybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion

226 citations · 482 across the 28 of their papers we have counts for

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Showing 2021 · cs.CLShow all

8 papers · 2 filters

cs.CL2021★ 1 cited

Achieving Human Parity on Visual Question Answering

Ming Yan, Haiyang Xu, Chenliang Li +14

The Visual Question Answering (VQA) task utilizes both visual image and language analysis to answer a textual question with respect to an image. It has been a popular research topi…

cs.CL2021★ 1 cited

DialogueCSE: Dialogue-based Contrastive Learning of Sentence Embeddings

Che Liu, Rui Wang, Jinghua Liu +3

Learning sentence embeddings from dialogues has drawn increasing attention due to its low annotation cost and high domain adaptability. Conventional approaches employ the siamese-n…

cs.CL2021★ 39 cited

LightNER: A Lightweight Tuning Paradigm for Low-resource NER via Pluggable Prompting

Xiang Chen, Lei Li, Shumin Deng +6

Most NER methods rely on extensive labeled data for model training, which struggles in the low-resource scenarios with limited training data. Existing dominant approaches usually s…

cs.CL2021

CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark

Ningyu Zhang, Mosha Chen, Zhen Bi +20

Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice. With the development of biomedical langua…

cs.CL2021

Document-level Relation Extraction as Semantic Segmentation

Ningyu Zhang, Xiang Chen, Xin Xie +6

Document-level relation extraction aims to extract relations among multiple entity pairs from a document. Previously proposed graph-based or transformer-based models utilize the en…

cs.CL2021★ 4 cited

Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialog State Tracking

Yinpei Dai, Hangyu Li, Yongbin Li +4

Existing dialog state tracking (DST) models are trained with dialog data in a random order, neglecting rich structural information in a dataset. In this paper, we propose to use cu…