Papers by Chenxuan Cui
A Hmong Corpus with Elaborate Expression Annotations (2022.lrec-1)
Copied to clipboard
| Challenge: | SCH is the first substantial corpus to be annotated for elaborate expressions . a plurality of speakers are located in China, but many Hmong speakers left Laos as refugees . |
| Approach: | They describe the first publicly available corpus of Hmong, a minority language of China, Vietnam, Laos, Thailand, and various countries in Europe and the Americas. |
| Outcome: | The first publicly available corpus of Hmong is scraped from a long-running Usenet newsgroup . it is the first substantial corpus to be annotated for elaborate expressions . |
WikiHan: A New Comparative Dataset for Chinese Languages (2022.coling-1)
Copied to clipboard
| Challenge: | Currently, there are 1.3 billion speakers of Sinitic varieties, making the family one of the largest in terms of speaker count. |
| Approach: | They have collected a single constituent and structured form of Chinese varieties for comparative linguistics and Chinese NLP. |
| Outcome: | The proposed dataset contains 67,943 entries across 8 varieties and Middle Chinese . it achieves 54.11% accuracy and 17.69% error rate on a protoform reconstruction task . |
Learning the Ordering of Coordinate Compounds and Elaborate Expressions in Hmong, Lahu, and Chinese (2022.naacl-main)
Copied to clipboard
| Challenge: | phonological hierarchies that predict coordinate constructions are often phonetically “natural” . a neural sequence labeling model can learn elaborate expressions in Hmong without using phonology information. |
| Approach: | They propose that coordinate compounds and elaborate expressions can be learned empirically by phonological hierarchies and a neural sequence labeling model can learn the ordering of elaborate expression in Hmong without using phonology. |
| Outcome: | The proposed models beat strong baselines for all three languages and learn hierarchies similar to those proposed by Mortensen. |
Testing the Ability of Language Models to Interpret Figurative Language (2022.naacl-main)
Copied to clipboard
| Challenge: | Existing work on figurative language has not been done on literal language models. |
| Approach: | They propose a Winograd-style task to evaluate figurative phrases with divergent meanings by interpreting paired figurativ phrases with a human input. |
| Outcome: | The proposed task outperforms state-of-the-art models on a nonliteral language understanding task in zero-shot settings. |
PWESuite: Phonetic Word Embeddings and Tasks They Facilitate (2024.lrec-main)
Copied to clipboard
Vilém Zouhar, Kalvin Chang, Chenxuan Cui, Nate B. Carlson, Nathaniel Romney Robinson, Mrinmaya Sachan, David R. Mortensen
| Challenge: | Existing word embedding methods overlook phonetic information that is crucial for many tasks. |
| Approach: | They propose three methods that use articulatory features to build phonetically informed word embeddings. |
| Outcome: | The proposed methods improve word retrieval and correlation with sound similarity and on rhyme and cognate detection tasks. |
Transformed Protoform Reconstruction (2023.acl-short)
Copied to clipboard
| Challenge: | Historical linguists reconstruct proto-languages by identifying systematic sound changes that can be inferred from correspondences between attested daughter languages. |
| Approach: | They propose to update their Latin protoform reconstruction model with the Transformer . romance data of 8,000 cognates spanning 5 languages and Chinese dataset are outperformed . |
| Outcome: | The proposed model outperforms previous models on Romance and Chinese datasets. |