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20222026
most citedMere Contrastive Learning for Cross-Domain Sentiment Analysis

10 citations · 28 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CL2024★ 1 cited

Personality Alignment of Large Language Models

Minjun Zhu, Yixuan Weng, Linyi Yang +1

Aligning large language models (LLMs) typically aim to reflect general human values and behaviors, but they often fail to capture the unique characteristics and preferences of indi…

cs.CL2022★ 10 cited

Mere Contrastive Learning for Cross-Domain Sentiment Analysis

Yun Luo, Fang Guo, Zihan Liu +1

Cross-domain sentiment analysis aims to predict the sentiment of texts in the target domain using the model trained on the source domain to cope with the scarcity of labeled data.…

cs.CL2022★ 9 cited

FactMix: Using a Few Labeled In-domain Examples to Generalize to Cross-domain Named Entity Recognition

Linyi Yang, Lifan Yuan, Leyang Cui +2

Few-shot Named Entity Recognition (NER) is imperative for entity tagging in limited resource domains and thus received proper attention in recent years. Existing approaches for few…

cs.CL2022★ 1 cited

A Survey on Open Information Extraction from Rule-based Model to Large Language Model

Pai Liu, Wenyang Gao, Wenjie Dong +7

Open Information Extraction (OpenIE) represents a crucial NLP task aimed at deriving structured information from unstructured text, unrestricted by relation type or domain. This su…

cs.CL2022★ 5 cited

Challenges for Open-domain Targeted Sentiment Analysis

Yun Luo, Hongjie Cai, Linyi Yang +3

Since previous studies on open-domain targeted sentiment analysis are limited in dataset domain variety and sentence level, we propose a novel dataset consisting of 6,013 human-lab…