| Generative adversarial text to image synthesis S Reed, Z Akata, X Yan, L Logeswaran, B Schiele, H Lee International conference on machine learning, 1060-1069, 2016 | 3181 | 2016 |
| An efficient framework for learning sentence representations L Logeswaran, H Lee International Conference on Learning Representations, 2018 | 530 | 2018 |
| Zero-shot entity linking by reading entity descriptions L Logeswaran, MW Chang, K Lee, K Toutanova, J Devlin, H Lee arXiv preprint arXiv:1906.07348, 2019 | 208 | 2019 |
| Sentence ordering and coherence modeling using recurrent neural networks L Logeswaran, H Lee, D Radev Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 114* | 2018 |
| Content preserving text generation with attribute controls L Logeswaran, H Lee, S Bengio Advances in Neural Information Processing Systems 31, 2018 | 110 | 2018 |
| Performance, resource, and cost aware resource provisioning in the cloud L Logeswaran, HMND Bandara, HS Bhathiya 2016 IEEE 9th International Conference on Cloud Computing (CLOUD), 913-916, 2016 | 11 | 2016 |
| Few-shot sequence learning with transformers L Logeswaran, A Lee, M Ott, H Lee, MA Ranzato, A Szlam arXiv preprint arXiv:2012.09543, 2020 | 10 | 2020 |
| Few-shot subgoal planning with language models L Logeswaran, Y Fu, M Lee, H Lee arXiv preprint arXiv:2205.14288, 2022 | 5 | 2022 |
| Layered Depth Image based HEVC Multi-view Codec S Kirshanthan, L Lajanugen, PND Panagoda, LP Wijesinghe, D De Silva, ... International Symposium on Visual Computing, 2014 | 5 | 2014 |
| Exploring the benefits of training expert language models over instruction tuning J Jang, S Kim, S Ye, D Kim, L Logeswaran, M Lee, K Lee, M Seo arXiv preprint arXiv:2302.03202, 2023 | 3 | 2023 |
| Learning compositional tasks from language instructions L Logeswaran, WT Carvalho, H Lee Deep RL Workshop NeurIPS 2021, 2021 | 3 | 2021 |
| Knowledge Unlearning for Mitigating Privacy Risks in Language Models J Jang, D Yoon, S Yang, S Cha, M Lee, L Logeswaran, M Seo arXiv preprint arXiv:2210.01504, 2022 | 2 | 2022 |
| LEPUS: Prompt-based Unsupervised Multi-hop Reranking for Open-domain QA M Khalifa, L Logeswaran, M Lee, H Lee, L Wang arXiv preprint arXiv:2205.12650, 2022 | 1 | 2022 |
| Performance, resource and cost aware virtual machine adaptation L Logeswaran | 1 | 2015 |
| Solving Jigsaw Puzzles using Paths and Cycles. L Logeswaran BMVC, 2014 | 1 | 2014 |
| Discriminator-Guided Multi-step Reasoning with Language Models M Khalifa, L Logeswaran, M Lee, H Lee, L Wang arXiv preprint arXiv:2305.14934, 2023 | | 2023 |
| A Picture is Worth a Thousand Words: Language Models Plan from Pixels AZ Liu, L Logeswaran, S Sohn, H Lee arXiv preprint arXiv:2303.09031, 2023 | | 2023 |
| Exploring Demonstration Ensembling for In-context Learning M Khalifa, L Logeswaran, M Lee, H Lee, L Wang ICLR 2023 Workshop on Mathematical and Empirical Understanding of Foundation …, 2023 | | 2023 |
| Unsupervised Task Graph Generation from Instructional Video Transcripts L Logeswaran, S Sohn, Y Jang, M Lee, H Lee arXiv preprint arXiv:2302.09173, 2023 | | 2023 |
| Multimodal Subtask Graph Generation from Instructional Videos Y Jang, S Sohn, L Logeswaran, T Luo, M Lee, H Lee arXiv preprint arXiv:2302.08672, 2023 | | 2023 |
Honglak LeeLG AI Research / U. MichiganVerified email at umich.edu
