See Google Schoolar for the latest list.


2025

  • Beyond correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge
    • Aparna Elangovan, Lei Xu*, Jongwoo Ko*, Mahsa Elyasi* (*equal contribution), Ling Liu, Sravan Bodapati, Dan Roth
    • Proceddings of ICLR, Singapore, 2025
    • [pdf] [code]
  • CriSPO: Multi-Aspect Critique-Suggestion-guided Automatic Prompt Optimization for Text Generation
    • Han He*, Qianchu Liu*, Lei Xu* (*equal contribution), Chaitanya Shivade, Yi Zhang, Sundararajan Srinivasan, Katrin Kirchhoff
    • Proceddings of AAAI, Philadelphia, 2025
    • [pdf] [code] [poster]

2024

  • Salient Information Prompting to Steer Content in Prompt-based Abstractive Summarization
    • Lei Xu, Mohammed Asad Karim, Saket Dingliwal, Aparna Elangovan
    • Proceedings of EMNLP, Miami, 2024
    • [pdf] [code] [poster]
  • ConSiDERS-The-Human Evaluation Framework: Rethinking Human Evaluation for Generative Large Language Models
    • Aparna Elangovan, Ling Liu, Lei Xu, Sravan Bodapati, Dan Roth
    • Proceedings of ACL, Bangkok, 2024
    • [pdf]
  • Single word change is all you need: Designing attacks and defenses for text classifiers
    • Lei Xu, Sarah Alnegheimish, Laure Berti-Equille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
    • ArXiv
    • [pdf] [code]

2022

  • R&R: Metric-guided Adversarial Sentence Generation
    • Lei Xu, Alfredo Cuesta-Infante, Laure Berti-Equille, Kalyan Veeramachaneni
    • Findings of AACL, Taipei, 2022
    • [pdf] [code]
  • Exploring the Universal Vulnerability of Prompt-based Learning Paradigm
    • Lei Xu, Yangyi Chen, Ganqu Cui, Hongcheng Gao, Zhiyuan Liu
    • Findings of NAACL-HLT, Seattle, 2022
    • [pdf] [code] [poster]
  • In Situ Augmentation for Defending Against Adversarial Attacks on Text Classifiers
    • Lei Xu, Laure Berti-Equille, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
    • International Conference on Neural Information Processing (ICONIP), Indore, 2022
    • AdvML Workshop @ KDD, Washington DC, 2022 (best paper)
    • [pdf] [poster]

2021

  • AutoML to Date and Beyond: Challenges and Opportunities
    • Shubhra Kanti Karmaker, Md Mahadi Hassan, Micah J Smith, Lei Xu, Chengxiang Zhai, Kalyan Veeramachaneni
    • ACM Computing Surveys, 2021
    • [pdf]

2019

  • Modeling Tabular Data using Conditional GAN
  • MLFriend: Interactive prediction task recommendation for event-driven time-series data
    • Lei Xu, Shubhra Kanti Karmaker Santu, Kalyan Veeramachaneni
    • ArXiv
    • [pdf] [code]
  • SteganoGAN: High capacity image steganography with GANs
    • Kevin Alex Zhang, Alfredo Cuesta-Infante, Lei Xu, Kalyan Veeramachaneni
    • ArXiv
    • [pdf]
  • Robust invisible video watermarking with attention
    • Kevin Alex Zhang, Lei Xu, Alfredo Cuesta-Infante, Kalyan Veeramachaneni
    • ArXiv
    • [pdf]

2018

  • Synthesizing tabular data using generative adversarial networks
    • Lei Xu, Kalyan Veeramachaneni
    • ArXiv
    • [pdf]

2017

  • Input Convex Neural Networks
    • Brandon Amos, Lei Xu, J. Zico Kolter
    • Proceedings of ICML, Sydney, 2017
    • [pdf] [code]

2016

  • Topic Sensitive Neural Headline Generation
    • Lei Xu*, Ziyun Wang* (*equal contribution), Ayana, Zhiyuan Liu, Maosong Sun
    • ArXiv preprint, 2016
    • [pdf]

2015

  • Joint Learning of Character and Word Embeddings
    • Xinxiong Chen*, Lei Xu* (*equal contribution), Zhiyuan Liu, Maosong Sun, Huanbo Luan
    • Proceedings of IJCAI, Buenos Aires, 2015
    • [pdf] [code]