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20172022
most citedGraph-Bert: Only Attention is Needed for Learning Graph Representations

158 citations · 228 across the 12 of their papers we have counts for

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14 papers · 1 filter

cs.CL2022

Continuous Prompt Tuning Based Textual Entailment Model for E-commerce Entity Typing

Yibo Wang, Congying Xia, Guan Wang +1

The explosion of e-commerce has caused the need for processing and analysis of product titles, like entity typing in product titles. However, the rapid activity in e-commerce has l…

cs.CL20223 cited

Multifaceted Improvements for Conversational Open-Domain Question Answering

Tingting Liang, Yixuan Jiang, Congying Xia +3

Open-domain question answering (OpenQA) is an important branch of textual QA which discovers answers for the given questions based on a large number of unstructured documents. Effe…

cs.CL2021

HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization

Ye Liu, Jian-Guo Zhang, Yao Wan +3

To capture the semantic graph structure from raw text, most existing summarization approaches are built on GNNs with a pre-trained model. However, these methods suffer from cumbers…

cs.CL20211 cited

Cross-lingual COVID-19 Fake News Detection

Jiangshu Du, Yingtong Dou, Congying Xia +3

The COVID-19 pandemic poses a great threat to global public health. Meanwhile, there is massive misinformation associated with the pandemic which advocates unfounded or unscientifi…

cs.CL2021

Few-Shot Intent Detection via Contrastive Pre-Training and Fine-Tuning

Jianguo Zhang, Trung Bui, Seunghyun Yoon +6

In this work, we focus on a more challenging few-shot intent detection scenario where many intents are fine-grained and semantically similar. We present a simple yet effective few-…

cs.CL2021

Pseudo Siamese Network for Few-shot Intent Generation

Congying Xia, Caiming Xiong, Philip Yu

Few-shot intent detection is a challenging task due to the scare annotation problem. In this paper, we propose a Pseudo Siamese Network (PSN) to generate labeled data for few-shot…