Publication

I publish under "Xinliang Frederick Zhang".
* indicates equal contribution.
^ indicates my mentees.

2024

  1. arXiv
    Improving Temporal Reasoning of Language Models via Recounted Narratives
    Xinliang Frederick Zhang, Nicholas Beauchamp, and Lu Wang
    In arXiv.
    Paper
  2. ACL-Findings
    ULTRA: Unleashing LLM’s Potential for Event Argument Extraction through Hierarchical Modeling and Pairwise Self-Refinement
    Xinliang Frederick Zhang, Carter Blum, Temma Choji, Shalin Shah, and Alakananda Vempala
    In Findings of the Association for Computational Linguistics: ACL 2024.
    Paper
  3. NAACL
    MOKA: Moral Knowledge Augmentation for Moral Event Extraction
    Xinliang Frederick Zhang, Winston Wu, Nicholas Beauchamp, and Lu Wang
    In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2024.
    Paper Code&Data

2023

  1. EMNLP
    All Things Considered: Detecting Partisan Events from News Media with Cross-Article Comparison
    Yujian Liu, Xinliang Frederick Zhang, Kaijian Zou, Ruihong Huang, Nicholas Beauchamp, and Lu Wang
    In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023. (acceptance rate: 23.3%)
    Paper Code&Data
  2. EMNLP-Findings
    Crossing the Aisle: Unveiling Partisan and Counter-Partisan Events in News Reporting
    Kaijian Zou, Xinliang Frederick Zhang, Winston Wu, Nicholas Beauchamp, and Lu Wang
    In Findings of the Association for Computational Linguistics: EMNLP 2023. (main conference acceptance rate: 14.0%, findings acceptance rate: 19.5%)
    Paper Data
  3. EMNLP-Findings
    You Are What You Annotate: Towards Better Models through Annotator Representations
    Naihao Deng, Xinliang Frederick Zhang, Siyang Liu, Winston Wu, Lu Wang, and Rada Mihalcea
    In Findings of the Association for Computational Linguistics: EMNLP 2023. (main conference acceptance rate: 23.3%, findings acceptance rate: 22.9%)
    Paper Code&Data

2022

  1. EMNLP
    Generative Entity-to-Entity Stance Detection with Knowledge Graph Augmentation
    Xinliang Frederick Zhang, Nick Beauchamp, and Lu Wang
    In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022. (acceptance rate: 20.9%)
    Paper Code&Data Slides Poster Video
  2. EMNLP
    Late Fusion with Triplet Margin Objective for Multimodal Ideology Prediction and Analysis
    Changyuan Qiu*^, Winston Wu*, Xinliang Frederick Zhang, and Lu Wang
    In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022. (acceptance rate: 20.9%)
    Paper Code&Data Slides Poster Video
  3. NAACL-Findings
    POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection
    Yujian Liu*, Xinliang Frederick Zhang*, David Wegsman, Nicholas Beauchamp, and Lu Wang
    In Findings of the Association for Computational Linguistics: NAACL 2022. (main conference acceptance rate: 21.0%, findings acceptance rate: 9.9%)
    Paper Code&Data Demo Slides Poster Video

2021

  1. Thesis
    Towards More Robust Natural Language Understanding
    Xinliang Frederick Zhang
    Committee: Dr. Huan Sun (Chair), Dr. Marie-Catherine de Marneffe
    Undergraduate Research Thesis, The Ohio State University
    Paper
  2. BIBM
    CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answering
    Xiang Yue*, Xinliang Frederick Zhang*, Ziyu Yao, Simon M. Lin, and Huan Sun
    In 2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), IEEE BIBM 2021. (acceptance rate: 19.6%)
    Best Paper Award
    Paper Code Data Slides Video
  3. EMNLP
    COUGH: A Challenge Dataset and Models for COVID-19 FAQ Retrieval
    Xinliang Frederick Zhang, Heming Sun, Xiang Yue, Simon M. Lin, and Huan Sun
    In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021. (acceptance rate: 17.9%)
    Paper Data Slides Poster Video
  4. NAACL
    Identifying inherent disagreement in natural language inference
    Xinliang Frederick Zhang, and Marie-Catherine de Marneffe
    In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021. (acceptance rate: 22.6%)
    Paper Code&Data Slides Poster Video