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researcher

Xin Li

CUHK

32 papers hereh-index 237.1k citations42 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author6
  • middle author26

Across the 32 of 32 papers where every author was matched, so the position is known.

fields
  • cs.CL27
  • cs.CV5
affiliations
  • CUHK
  • Alibaba
Homepage
same name
  • Xin Li — 66 papers, h 21
  • Xin Li — 42 papers, h 19
  • Xin Li — 36 papers, h 23
  • Xin Li — 26 papers, h 21
  • Xin Li — 26 papers, h 6
  • Xin Li — 25 papers, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182025
most citedA Unified Model for Opinion Target Extraction and Target Sentiment Prediction

86 citations · 388 across the 32 of their papers we have counts for

collaborators
Showing 2021Show all

4 papers · 1 filter

cs.CL2021★ 2 cited

Enhancing Multilingual Language Model with Massive Multilingual Knowledge Triples

Linlin Liu, Xin Li, Ruidan He +3

Knowledge-enhanced language representation learning has shown promising results across various knowledge-intensive NLP tasks. However, prior methods are limited in efficient utiliz…

cs.CL2021

Multilingual AMR Parsing with Noisy Knowledge Distillation

Deng Cai, Xin Li, Jackie Chun-Sing Ho +2

We study multilingual AMR parsing from the perspective of knowledge distillation, where the aim is to learn and improve a multilingual AMR parser by using an existing English parse…

cs.CL2021★ 1 cited

Aspect Sentiment Quad Prediction as Paraphrase Generation

Wenxuan Zhang, Yang Deng, Xin Li +3

Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years, which typically involves four fundamental sentiment elements, including the aspect category, as…

cs.CL2021

MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER

Ran Zhou, Xin Li, Ruidan He +4

Data augmentation is an effective solution to data scarcity in low-resource scenarios. However, when applied to token-level tasks such as NER, data augmentation methods often suffe…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.