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20162025
most citedA Survey on Deep Learning for Named Entity Recognition

1.5k citations · 6.3k across the 95 of their papers we have counts for

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Showing 2021Show all

10 papers · 1 filter

cs.IR2021

Mirror Matching: Document Matching Approach in Seed-driven Document Ranking for Medical Systematic Reviews

Grace E. Lee, Aixin Sun

When medical researchers conduct a systematic review (SR), screening studies is the most time-consuming process: researchers read several thousands of medical literature and manual…

cs.SI2021

DP-GCN: Node Classification Based on Both Connectivity and Topology Structure Convolutions for Risky Seller Detection

Chen Zhe, Aixin Sun

A payment network contains transactions between sellers and buyers. Detecting risky (or bad) sellers on such a payment network is crucial to payment service providers for risk mana…

cs.CV2021★ 6 cited

Towards Debiasing Temporal Sentence Grounding in Video

Hao Zhang, Aixin Sun, Wei Jing +1

The temporal sentence grounding in video (TSGV) task is to locate a temporal moment from an untrimmed video, to match a language query, i.e., a sentence. Without considering bias i…

cs.CL2021★ 2 cited

A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict

Yiyi Liu, Yequan Wang, Aixin Sun +3

Sarcasm employs ambivalence, where one says something positive but actually means negative, and vice versa. The essence of sarcasm, which is also a sufficient and necessary conditi…

cs.IR2021★ 96 cited

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

Xin Zhou, Aixin Sun, Yong Liu +2

Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions. Existing CF-based methods commonly adopt nega…

cs.CL2021★ 42 cited

Parallel Attention Network with Sequence Matching for Video Grounding

Hao Zhang, Aixin Sun, Wei Jing +3

Given a video, video grounding aims to retrieve a temporal moment that semantically corresponds to a language query. In this work, we propose a Parallel Attention Network with Sequ…