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1
Enhancing Cross-lingual Prompting with Mask Token Augmentation ...
Zhou, Meng; Li, Xin; Jiang, Yue. - : arXiv, 2022
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2
P-hydroxy benzaldehyde facilitates reprogramming of reactive astrocytes into neurons via endogenous transcriptional regulation ...
Li, Xin; Fan, Ruoxi; Xiang, Jianming. - : Taylor & Francis, 2022
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3
P-hydroxy benzaldehyde facilitates reprogramming of reactive astrocytes into neurons via endogenous transcriptional regulation ...
Li, Xin; Fan, Ruoxi; Xiang, Jianming. - : Taylor & Francis, 2022
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4
p-hydroxy benzaldehyde facilitates reprogramming of reactive astrocytes into neurons via endogenous transcriptional regulation ...
Li, Xin; Fan, Ruoxi; Xiang, Jianming. - : Taylor & Francis, 2022
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5
Life in Beijing
Chirkova, Katia; Li, Xin; Ma Zhaorong. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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6
Knowledge Based Multilingual Language Model ...
Liu, Linlin; Li, Xin; He, Ruidan. - : arXiv, 2021
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7
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER ...
Zhou, Ran; Li, Xin; He, Ruidan. - : arXiv, 2021
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8
Multilingual AMR Parsing with Noisy Knowledge Distillation ...
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9
Towards Generative Aspect-Based Sentiment Analysis ...
Abstract: Read paper: https://www.aclanthology.org/2021.acl-short.64 Abstract: Aspect-based sentiment analysis (ABSA) has received increasing attention recently. Most existing work tackles ABSA in a discriminative manner, designing various task-specific classification networks for the prediction. Despite their effectiveness, these methods ignore the rich label semantics in ABSA problems and require extensive task-specific designs. In this paper, we propose to tackle various ABSA tasks in a unified generative framework. Two types of paradigms, namely annotation-style and extraction-style modeling, are designed to enable the training process by formulating each ABSA task as a text generation problem. We conduct experiments on four ABSA tasks across multiple benchmark datasets where our proposed generative approach achieves new state-of-the-art results in almost all cases. This also validates the strong generality of the proposed framework which can be easily adapted to arbitrary ABSA task without additional ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://dx.doi.org/10.48448/kr6a-6s64
https://underline.io/lecture/25603-towards-generative-aspect-based-sentiment-analysis
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10
Life in Beijing
Chirkova, Katia; Li, Xin. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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11
Conversation
Chirkova, Katia; Li, Xin. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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12
Shichahai and the Drum Tower
Chirkova, Katia; Li, Xin; Mr. Zhang. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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13
Bird keepers in Beijing
Chirkova, Katia; Li, Xin; Ma Zhaorong. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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14
Interview with He Yujun
Chirkova, Katia; Li, Xin. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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15
Bird keepers in Beijing
Chirkova, Katia; Li, Xin. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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16
Conversation
Chirkova, Katia; Li, Xin; Ma Zhaorong. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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17
Shichahai and the Drum Tower
Chirkova, Katia; Li, Xin. - : Centre de recherches linguistiques sur l'Asie orientale, 2021
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18
Encoding of facial features by single neurons in the human amygdala and hippocampus
In: Commun Biol (2021)
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19
The Bilingual Home Language Boost Through the Lens of the COVID-19 Pandemic
In: Front Psychol (2021)
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20
Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond ...
Li, Xin; Bing, Lidong; Zhang, Wenxuan. - : arXiv, 2020
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