| Modeling Tabular Data using Conditional GAN L Xu, M Skoularidou, A Cuesta-Infante, K Veeramachaneni Advances in Neural Information Processing Systems, 2019 | 1762 | 2019 |
| Input convex neural networks B Amos, L Xu, JZ Kolter International conference on machine learning, 146-155, 2017 | 796 | 2017 |
| Synthesizing tabular data using generative adversarial networks L Xu, K Veeramachaneni arXiv preprint arXiv:1811.11264, 2018 | 416 | 2018 |
| Joint learning of character and word embeddings X Chen, L Xu, Z Liu, M Sun, HB Luan IJCAI, 1236-1242, 2015 | 411 | 2015 |
| SteganoGAN: High capacity image steganography with GANs KA Zhang, A Cuesta-Infante, L Xu, K Veeramachaneni arXiv preprint arXiv:1901.03892, 2019 | 300 | 2019 |
| Automl to date and beyond: Challenges and opportunities SK Karmaker, MM Hassan, MJ Smith, L Xu, C Zhai, K Veeramachaneni Acm computing surveys (csur) 54 (8), 1-36, 2021 | 286 | 2021 |
| Robust invisible video watermarking with attention KA Zhang, L Xu, A Cuesta-Infante, K Veeramachaneni arXiv preprint arXiv:1909.01285, 2019 | 112 | 2019 |
| Exploring the universal vulnerability of prompt-based learning paradigm L Xu, Y Chen, G Cui, H Gao, Z Liu Findings of NAACL, 2022 | 87 | 2022 |
| Synthesizing tabular data using conditional GAN L Xu Massachusetts Institute of Technology, 2020 | 60 | 2020 |
| R&R: Metric-guided adversarial sentence generation L Xu, A Cuesta-Infante, L Berti-Equille, K Veeramachaneni Findings of AACL-IJCNLP, 2021 | 22* | 2021 |
| ConSiDERS-The-Human Evaluation Framework: Rethinking Human Evaluation for Generative Large Language Models A Elangovan, L Liu, L Xu, S Bodapati, D Roth Annual Meeting of the Association for Computational Linguistics, 2024 | 14 | 2024 |
| Topic sensitive neural headline generation L Xu, Z Wang, Z Liu, M Sun arXiv preprint arXiv:1608.05777, 2016 | 7 | 2016 |
| MLFriend: Interactive prediction task recommendation for event-driven time-series data L Xu, SKK Santu, K Veeramachaneni arXiv preprint arXiv:1906.12348, 2019 | 4 | 2019 |
| In situ augmentation for defending against adversarial attacks on text classifiers L Xu, L Berti-Equille, A Cuesta-Infante, K Veeramachaneni International Conference on Neural Information Processing, 485-496, 2022 | 3 | 2022 |
| Beyond Correlation: the impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge A Elangovan, L Xu, J Ko, M Elyasi, L Liu, S Bodapati, D Roth International Conference on Learning Representations (ICLR), 2025 | 2 | 2025 |
| Single word change is all you need: Designing attacks and defenses for text classifiers L Xu, S Alnegheimish, L Berti-Equille, A Cuesta-Infante, ... arXiv preprint arXiv:2401.17196, 2024 | 1 | 2024 |
| Guiding transcript generation using detected section types as part of automatic speech recognition L Xu, A Elangovan, R Paturi, S Srinivasan, SB Bodapati, K Kirchoff, ... US Patent App. 18/356,117, 2025 | | 2025 |
| Domain entity extraction for performing text analysis tasks JC Moriarty, S Dingliwal, K Gopalakrishnan, SB Bodapati, K Kirchhoff, ... US Patent App. 18/344,764, 2025 | | 2025 |
| MEDICAL CONVERSATION SUMMARIZATION STYLE INTELLIGENCE A Elangovan, L Xu, D Kulshreshtha, SB Bodapati, K Kirchhoff, S Handa US Patent App. 18/339,749, 2024 | | 2024 |
| Salient information prompting to steer content in prompt-based abstractive summarization L Xu, MA Karim, S Dingliwal, A Elangovan arXiv preprint arXiv:2410.02741, 2024 | | 2024 |
Kalyan VeeramachaneniPrincipal Research Scientist, Massachusetts Institute of Technology在 csail.mit.edu 的電子郵件地址已通過驗證
