I am a final year Ph.D. candidate in the NLP group at the University of British Columbia (UBC) supervised by Prof. Giuseppe Carenini. I received my M.S. in Computer Science from University of Colorado Boulder where I worked with Dr. Michael J. Paul, and completed my B.S. in Management Information System at Soochow University.
My primary research interests lie in the area of natural language processing (NLP) and machine learning (ML), with a focus on designing and implementing computational models to better understand natural language in various forms. In particular, my research experience during my master's and Ph.D. journey spans such domains:
University of British Columbia (UBC)Sept. 2018 - Present
Ph.D. in Computer Science (NLP)
Supervisor: Prof. Giuseppe Carenini
University of Colorado BoulderAug. 2016 - May. 2018
M.S. in Computer Science
Supervisor: Dr. Michael J. Paul
Soochow UniversitySept. 2012 - June. 2016
B.S. in Management Information System
GPA: 3.7/4.0 (Rank: 1/40)
Most recent publications on Google Scholar.
‡ indicates equal contribution.
Towards Human-aligned Evaluation for Linear Programming Word Problems
Linzi Xing, Xinglu Wang, Yuxi Feng, Zhenan Fan, Jing Xiong, Zhijiang Guo, Xiaojin Fu, Rindra Ramamonjison, Mahdi Mostajabdaveh, Xiongwei Han, Zirui Zhou and Yong Zhang
In Proceedings of the Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). 2024
Multi-Modal Video Topic Segmentation with Dual-Contrastive Domain Adaptation
Linzi Xing, Quan Hung Tran, Fabian Caba Heilbron, Franck Dernoncourt, David Seunghyun Yoon, Zhaowen Wang, Trung Bui, and Giuseppe Carenini
In Proceedings of the 30th International Conference on Multimedia Modeling (MMM 2024). 2024
TeX2Solver: a Hierarchical Semantic Parsing of TeX Document into Code for an Assistive Optimization Modeling Application
Rindra Ramamonjison, Timothy Yu, Linzi Xing, Mahdi Mostajabdaveh, Xiaorui Li, Xiaojin Fu, Xiongwei Han, Yuanzhe Chen, Ren Li, Kun Mao, and Yong Zhang
In Proceedings of the 61st Annual Meeting of Association for Computational Linguistics (ACL 2023: Demo). 2023
Diversity-Aware Coherence Loss for Improving Neural Topic Models
Raymond Li, Felipe Gonzalez-Pizarro, Linzi Xing, Gabriel Murray and Giuseppe Carenini
In Proceedings of the 61st Annual Meeting of Association for Computational Linguistics (ACL 2023: Short). 2023
Human Guided Exploitation of Interpretable Attention Patterns in Summarization and Topic Segmentation
Raymond Li, Wen Xiao, Linzi Xing, Lanjun Wang, Gabriel Murray, and Giuseppe Carenin
In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022). 2022
Predicting Above-Sentence Discourse Structure using Distant Supervision from Topic Segmentation
Patrick Huber‡, Linzi Xing‡, and Giuseppe Carenini
In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22). 2022
Demoting the Lead Bias in News Summarization via Alternating Adversarial Learning
Linzi Xing‡, Wen Xiao‡, and Giuseppe Carenini.
In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL 2021: Short). 2021
Improving Unsupervised Dialogue Topic Segmentation with Utterance-Pair Coherence Scoring
Linzi Xing, and Giuseppe Carenini
In Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2021). 2021
Improving Context Modeling in Neural Topic Segmentation
Linzi Xing, Brad Hackinen, Giuseppe Carenini, and Francesco Trebbi
In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL 2020). 2020
Evaluating Topic Quality with Posterior Variability
Linzi Xing, Michael J. Paul, and Giuseppe Carenini
In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019: Short). 2019
Diagnosing and improving topic models by analyzing posterior variability
Linzi Xing, and Michael J. Paul
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18). 2018.
Towards Human-aligned Evaluation for Linear Programming Word Problems
Linzi Xing, Xinglu Wang, Yuxi Feng, Zhenan Fan, Jing Xiong, Zhijiang Guo, Xiaojin Fu, Rindra Ramamonjison, Mahdi Mostajabdaveh, Xiongwei Han, Zirui Zhou and Yong Zhang
In Proceedings of the Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). 2024
Multi-Modal Video Topic Segmentation with Dual-Contrastive Domain Adaptation
Linzi Xing, Quan Hung Tran, Fabian Caba Heilbron, Franck Dernoncourt, David Seunghyun Yoon, Zhaowen Wang, Trung Bui, and Giuseppe Carenini
In Proceedings of the 30th International Conference on Multimedia Modeling (MMM 2024). 2024
Tracing Influence at Scale: A Contrastive Learning Approach to Linking Public Comments and Regulator Responses
Linzi Xing, Brad Hackinen, and Giuseppe Carenini
In Proceedings of the 5th Natural Legal Language Processing Worksho (NLLP 2023). 2023
TeX2Solver: a Hierarchical Semantic Parsing of TeX Document into Code for an Assistive Optimization Modeling Application
Rindra Ramamonjison, Timothy Yu, Linzi Xing, Mahdi Mostajabdaveh, Xiaorui Li, Xiaojin Fu, Xiongwei Han, Yuanzhe Chen, Ren Li, Kun Mao, and Yong Zhang
In Proceedings of the 61st Annual Meeting of Association for Computational Linguistics (ACL 2023: Demo). 2023
Diversity-Aware Coherence Loss for Improving Neural Topic Models
Raymond Li, Felipe Gonzalez-Pizarro, Linzi Xing, Gabriel Murray and Giuseppe Carenini
In Proceedings of the 61st Annual Meeting of Association for Computational Linguistics (ACL 2023: Short). 2023
Human Guided Exploitation of Interpretable Attention Patterns in Summarization and Topic Segmentation
Raymond Li, Wen Xiao, Linzi Xing, Lanjun Wang, Gabriel Murray, and Giuseppe Carenin
In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022). 2022
Improving Topic Segmentation by Injecting Discourse Dependencies
Linzi Xing, Patrick Huber, and Giuseppe Carenini
In Proceedings of the 3rd Workshop on Computational Approaches to Discourse (CODI 2022). 2022
Predicting Above-Sentence Discourse Structure using Distant Supervision from Topic Segmentation
Patrick Huber‡, Linzi Xing‡, and Giuseppe Carenini
In Proceedings of the 36th AAAI Conference on Artificial Intelligence (AAAI-22). 2022
Demoting the Lead Bias in News Summarization via Alternating Adversarial Learning
Linzi Xing‡, Wen Xiao‡, and Giuseppe Carenini.
In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics (ACL 2021: Short). 2021
Improving Unsupervised Dialogue Topic Segmentation with Utterance-Pair Coherence Scoring
Linzi Xing, and Giuseppe Carenini
In Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL 2021). 2021
Improving Context Modeling in Neural Topic Segmentation
Linzi Xing, Brad Hackinen, Giuseppe Carenini, and Francesco Trebbi
In Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL 2020). 2020
Multilingual Twitter Corpus and Baselines for Evaluating Demographic Bias in Hate Speech Recognition
Xiaolei Huang, Linzi Xing, Franck Dernoncourt, and Michael J. Paul
In Proceedings of the 12th Language Resources and Evaluation Conference (LREC 2020). 2020
Evaluating Topic Quality with Posterior Variability
Linzi Xing, Michael J. Paul, and Giuseppe Carenini
In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP 2019: Short). 2019
Diagnosing and improving topic models by analyzing posterior variability
Linzi Xing, and Michael J. Paul
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18). 2018.
Exploring Timelines of Confirmed Suicide Incidents through Social Media
Xiaolei Huang, Linzi Xing, Jed R. Brubaker, and Michael J. Paul
In Proceedings of the 5th IEEE International Conference on Healthcare Informatics (ICHI 2017). 2017
Incorporating Metadata into Content-Based User Embeddings
Linzi Xing, and Michael J. Paul
In Proceedings of the 3rd Workshop on Noisy User-generated Text (WNUT 2017). 2017
Resume [for academia] in PDF (last update: 2023.07.30).
Resume [for industry] in PDF (last update: 2023.07.30).