Papers by Rong Xiang
Ciron: a New Benchmark Dataset for Chinese Irony Detection (2020.lrec-1)
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| Challenge: | Automatic Chinese irony detection often lacks labeled benchmark datasets . despite its pervasive nature, irony is a trope whose actual meaning differs from what is literally enunciated. |
| Approach: | They propose to use a Chinese benchmark dataset for automatic Chinese irony detection to provide a benchmark for machine learning models. |
| Outcome: | The proposed dataset includes more than 8.7K posts, collected from Weibo, a micro blogging platform. |
Automatic Learning of Modality Exclusivity Norms with Crosslingual Word Embeddings (2020.starsem-1)
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| Challenge: | Normative studies on modality for English words are relatively common . however, they are limited to a relatively small number of languages and require costly ratings. |
| Approach: | They aim to learn a mapping between word embeddings and modality norms by training on a high-resource language and testing on . monolingual and crosslingual word embeds are used to predict modality association scores . |
| Outcome: | The proposed model predicts modality associations even when trained on an English resource and tested on a completely unseen language. |
Improving Multi-label Emotion Classification by Integrating both General and Domain-specific Knowledge (D19-55)
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| Challenge: | Text in domains like social media has its own salient characteristics. |
| Approach: | They propose a method to obtain domain knowledge and integrate it with general knowledge to improve emotion classification. |
| Outcome: | The proposed method improves performance of emotion classification on Twitter data. |
Affection Driven Neural Networks for Sentiment Analysis (2020.lrec-1)
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| Challenge: | Existing deep neural network models lack mechanisms to highlight important sentiment terms. |
| Approach: | They propose a method to incorporate affective knowledge into deep neural network models by mapping affective influence vectors to an affective impact value and integrating them into long-term memory models to highlight affective terms. |
| Outcome: | The proposed approach improves on three large datasets by 1.0% to 1.5% on the benchmark datasets. |
When Cantonese NLP Meets Pre-training: Progress and Challenges (2022.aacl-tutorials)
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| Challenge: | Cantonese is an influential Chinese variant with a large population of speakers worldwide. |
| Approach: | This tutorial will review Cantonese's progress in linguistics and NLP . it will introduce transformer-based pre-training methods for a wide range of downstream tasks . |
| Outcome: | This tutorial will present the main challenges for Cantonese NLP in relation to Cantonesian language idiosyncrasies of colloquialism and multilingualism. |
Sina Mandarin Alphabetical Words:A Web-driven Code-mixing Lexical Resource (2020.aacl-main)
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| Challenge: | Mandarin Alphabetical Words (MAWs) are a key component of Modern Chinese . they are characterized by unique code-mixing idiosyncrasies influenced by language exchanges . |
| Approach: | They propose to construct a large collection of Mandarin Alphabetic Words from Sina Weibo . they propose to use a web-based technique to identify and validate MAWs . |
| Outcome: | The proposed method identifies 16,207 Mandarin Alphabetic Words (MAWs) using a web-based technique . the results show that the proposed method is useful for linguistic research and inquiries . |