| Contextualized weak supervision for text classification D Mekala, J Shang Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 115 | 2020 |
| SCDV: Sparse Composite Document Vectors using soft clustering over distributional representations D Mekala, V Gupta, B Paranjape, H Karnick EMNLP 2017, 2016 | 99 | 2016 |
| X-class: Text classification with extremely weak supervision Z Wang, D Mekala, J Shang arXiv preprint arXiv:2010.12794, 2020 | 72 | 2020 |
| Meta: Metadata-empowered weak supervision for text classification D Mekala, X Zhang, J Shang Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 38 | 2020 |
| Coarse2Fine: Fine-grained text classification on coarsely-grained annotated data D Mekala, V Gangal, J Shang arXiv preprint arXiv:2109.10856, 2021 | 22 | 2021 |
| Bfclass: A backdoor-free text classification framework Z Li, D Mekala, C Dong, J Shang arXiv preprint arXiv:2109.10855, 2021 | 18 | 2021 |
| Leveraging qa datasets to improve generative data augmentation D Mekala, T Vu, T Schick, J Shang arXiv preprint arXiv:2205.12604, 2022 | 12 | 2022 |
| LOPS: Learning order inspired pseudo-label selection for weakly supervised text classification D Mekala, C Dong, J Shang arXiv preprint arXiv:2205.12528, 2022 | 11 | 2022 |
| Zerotop: Zero-shot task-oriented semantic parsing using large language models D Mekala, J Wolfe, S Roy arXiv preprint arXiv:2212.10815, 2022 | 10 | 2022 |
| User bias removal in review score prediction R Wadbude, V Gupta, D Mekala, H Karnick Proceedings of the ACM India Joint International Conference on Data Science …, 2018 | 10* | 2018 |
| A benchmark on extremely weakly supervised text classification: Reconcile seed matching and prompting approaches Z Wang, T Wang, D Mekala, J Shang arXiv preprint arXiv:2305.12749, 2023 | 6 | 2023 |
| DAIL: Data Augmentation for In-Context Learning via Self-Paraphrase D Li, Y Li, D Mekala, S Li, X Wang, W Hogan, J Shang arXiv preprint arXiv:2311.03319, 2023 | 5 | 2023 |
| Smaller language models are capable of selecting instruction-tuning training data for larger language models D Mekala, A Nguyen, J Shang arXiv preprint arXiv:2402.10430, 2024 | 2 | 2024 |
| MORL-Prompt: An Empirical Analysis of Multi-Objective Reinforcement Learning for Discrete Prompt Optimization Y Jafari, D Mekala, R Yu, T Berg-Kirkpatrick arXiv preprint arXiv:2402.11711, 2024 | 1 | 2024 |
| SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank D Mekala, A Samavedhi, C Dong, J Shang arXiv preprint arXiv:2305.14696, 2023 | 1 | 2023 |
| News meets microblog: Hashtag annotation via retriever-generator X Zheng, D Mekala, A Gupta, J Shang arXiv preprint arXiv:2104.08723, 2021 | 1 | 2021 |
| Bayes-optimal Hierarchical Classification over Asymmetric Tree-Distance Loss D Mekala, V Gupta, P Kar, H Karnick arXiv preprint arXiv:1802.06771, 2018 | 1 | 2018 |
| When is the consistent prediction likely to be a correct prediction? A Nguyen, D Mekala, C Dong, J Shang arXiv preprint arXiv:2407.05778, 2024 | | 2024 |
| DOCMASTER: A Unified Platform for Annotation, Training, & Inference in Document Question-Answering A Nguyen, Z Wang, J Shang, D Mekala arXiv preprint arXiv:2404.00439, 2024 | | 2024 |
| TOOLVERIFIER: Generalization to New Tools via Self-Verification D Mekala, J Weston, J Lanchantin, R Raileanu, M Lomeli, J Shang, ... arXiv preprint arXiv:2402.14158, 2024 | | 2024 |
Jingbo ShangAssistant Professor, UC San Diego在 ucsd.edu 的电子邮件经过验证
