| RLPrompt: Optimizing Discrete Text Prompts With Reinforcement Learning M Deng, J Wang, CP Hsieh, Y Wang, H Guo, T Shu, M Song, EP Xing, ... arXiv preprint arXiv:2205.12548, 2022 | 293 | 2022 |
| VisualGPT: Data-efficient adaptation of pretrained language models for image captioning J Chen, H Guo, K Yi, B Li, M Elhoseiny arXiv preprint arXiv:2102.10407, 2021 | 228 | 2021 |
| Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation H Guo, R Pasunuru, M Bansal ACL 2018, 2018 | 166 | 2018 |
| Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits H Guo, R Pasunuru, M Bansal AAAI 2020, 2020 | 135 | 2020 |
| FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging H Guo, NF Rajani, P Hase, M Bansal, C Xiong arXiv preprint arXiv:2012.15781, 2020 | 108 | 2020 |
| Uncertainty toolbox: an open-source library for assessing, visualizing, and improving uncertainty quantification Y Chung, I Char, H Guo, J Schneider, W Neiswanger arXiv preprint arXiv:2109.10254, 2021 | 95 | 2021 |
| Dynamic Multi-Level Multi-Task Learning for Sentence Simplification H Guo, R Pasunuru, M Bansal COLING 2018, 2018 | 89 | 2018 |
| MPCFormer: fast, performant and private Transformer inference with MPC D Li, R Shao, H Wang, H Guo, EP Xing, H Zhang arXiv preprint arXiv:2211.01452, 2022 | 63 | 2022 |
| Efficient (Soft) Q-Learning for Text Generation with Limited Good Data H Guo, B Tan, Z Liu, E Xing, Z Hu Findings of the Association for Computational Linguistics: EMNLP 2022, 6969-6991, 2022 | 58* | 2022 |
| AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning H Guo, R Pasunuru, M Bansal NAACL 2019, 2019 | 55 | 2019 |
| Towards Improving Abstractive Summarization via Entailment Generation R Pasunuru, H Guo, M Bansal Proceedings of the Workshop on New Frontiers in Summarization, 27-32, 2017 | 48 | 2017 |
| LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning H Guo, P Greengard, EP Xing, Y Kim arXiv preprint arXiv:2311.12023, 2023 | 37 | 2023 |
| Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach H Guo, P Greengard, H Wang, A Gelman, Y Kim, EP Xing arXiv preprint arXiv:2302.04228, 2023 | 11 | 2023 |
| An Overview of Uncertainty Calibration for Text Classification and the Role of Distillation H Guo, R Pasunuru, M Bansal Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP …, 2021 | 9 | 2021 |
| DORB: Dynamically Optimizing Multiple Rewards with Bandits R Pasunuru, H Guo, M Bansal Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020 | 7 | 2020 |
| Fast Matrix Multiplications for Lookup Table-Quantized LLMs H Guo, W Brandon, R Cholakov, J Ragan-Kelley, EP Xing, Y Kim arXiv preprint arXiv:2407.10960, 2024 | 3 | 2024 |
| Training-Free Activation Sparsity in Large Language Models J Liu, P Ponnusamy, T Cai, H Guo, Y Kim, B Athiwaratkun arXiv preprint arXiv:2408.14690, 2024 | 2 | 2024 |
| The Surprising Effectiveness of Test-Time Training for Abstract Reasoning E Akyürek, M Damani, L Qiu, H Guo, Y Kim, J Andreas arXiv preprint arXiv:2411.07279, 2024 | | 2024 |
Mohit BansalParker Distinguished Professor, Computer Science, UNC Chapel HillEmail verificata su cs.unc.edu