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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
Cross-lingual Aspect-based Sentiment Analysis with Aspect Term Code-Switching ...
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3
Towards Multi-Sense Cross-Lingual Alignment of Contextual Embeddings ...
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4
Knowledge Based Multilingual Language Model ...
Liu, Linlin; Li, Xin; He, Ruidan. - : arXiv, 2021
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5
MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER ...
Zhou, Ran; Li, Xin; He, Ruidan. - : arXiv, 2021
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6
Multilingual AMR Parsing with Noisy Knowledge Distillation ...
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7
GlobalWoZ: Globalizing MultiWoZ to Develop Multilingual Task-Oriented Dialogue Systems ...
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8
Multi-perspective Coherent Reasoning for Helpfulness Prediction of Multimodal Reviews ...
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9
On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation ...
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10
Towards Generative Aspect-Based Sentiment Analysis ...
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11
Argument Pair Extraction via Attention-guided Multi-Layer Multi-Cross Encoding ...
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12
Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction ...
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13
MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER ...
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14
Unsupervised Cross-lingual Adaptation for Sequence Tagging and Beyond ...
Li, Xin; Bing, Lidong; Zhang, Wenxuan. - : arXiv, 2020
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15
Dynamic Topic Tracker for KB-to-Text Generation
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16
Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning ...
Li, Zheng; Li, Xin; Wei, Ying. - : arXiv, 2019
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17
A knowledge regularized hierarchical approach for emotion cause analysis
Gui, Lin; Bing, Lidong; Xu, Ruifeng. - : Association for Computational Linguistics, 2019
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18
Neural Rating Regression with Abstractive Tips Generation for Recommendation ...
Li, Piji; Wang, Zihao; Ren, Zhaochun. - : arXiv, 2017
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19
Reader-Aware Multi-Document Summarization via Sparse Coding ...
Abstract: We propose a new MDS paradigm called reader-aware multi-document summarization (RA-MDS). Specifically, a set of reader comments associated with the news reports are also collected. The generated summaries from the reports for the event should be salient according to not only the reports but also the reader comments. To tackle this RA-MDS problem, we propose a sparse-coding-based method that is able to calculate the salience of the text units by jointly considering news reports and reader comments. Another reader-aware characteristic of our framework is to improve linguistic quality via entity rewriting. The rewriting consideration is jointly assessed together with other summarization requirements under a unified optimization model. To support the generation of compressive summaries via optimization, we explore a finer syntactic unit, namely, noun/verb phrase. In this work, we also generate a data set for conducting RA-MDS. Extensive experiments on this data set and some classical data sets demonstrate the ... : 7 pages, 2 figures, accepted as a full paper at IJCAI 2015 ...
Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1504.07324
https://arxiv.org/abs/1504.07324
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20
Abstractive Multi-Document Summarization via Phrase Selection and Merging ...
Bing, Lidong; Li, Piji; Liao, Yi. - : arXiv, 2015
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