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Lajanugen Logeswaran
Lajanugen Logeswaran
LG AI Research
Verified email at lgresearch.ai - Homepage
Title
Cited by
Cited by
Year
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
46722016
An efficient framework for learning sentence representations
L Logeswaran, H Lee
International Conference on Learning Representations, 2018
7602018
Knowledge unlearning for mitigating privacy risks in language models
J Jang, D Yoon, S Yang, S Cha, M Lee, L Logeswaran, M Seo
Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023
3852023
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
3542019
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
151*2018
Content preserving text generation with attribute controls
L Logeswaran, H Lee, S Bengio
Advances in Neural Information Processing Systems 31, 2018
1482018
When” a helpful assistant” is not really helpful: Personas in system prompts do not improve performances of large language models
M Zheng, J Pei, L Logeswaran, M Lee, D Jurgens
Findings of the Association for Computational Linguistics: EMNLP 2024, 15126 …, 2024
1052024
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
International Conference on Machine Learning, 14702-14729, 2023
972023
Understanding the capabilities and limitations of large language models for cultural commonsense
S Shen, L Logeswaran, M Lee, H Lee, S Poria, R Mihalcea
arXiv preprint arXiv:2405.04655, 2024
742024
Small language models need strong verifiers to self-correct reasoning
Y Zhang, M Khalifa, L Logeswaran, J Kim, M Lee, H Lee, L Wang
arXiv preprint arXiv:2404.17140, 2024
712024
Autoguide: Automated generation and selection of context-aware guidelines for large language model agents
Y Fu, DK Kim, J Kim, S Sohn, L Logeswaran, K Bae, H Lee
Advances in Neural Information Processing Systems 37, 119919-119948, 2024
59*2024
Dallas Card, and David Jurgens. 2024. You don’t need a personality test to know these models are unreliable: Assessing the reliability of large language models on psychometric …
B Shu, L Zhang, M Choi, L Dunagan, L Logeswaran, M Lee
Proceedings of the 2024 Conference of the North American Chapter of the …, 2023
522023
Process reward models that think
M Khalifa, R Agarwal, L Logeswaran, J Kim, H Peng, M Lee, H Lee, ...
arXiv preprint arXiv:2504.16828, 2025
482025
Merging generated and retrieved knowledge for open-domain QA
Y Zhang, M Khalifa, L Logeswaran, M Lee, H Lee, L Wang
arXiv preprint arXiv:2310.14393, 2023
452023
Grace: Discriminator-guided chain-of-thought reasoning
M Khalifa, L Logeswaran, M Lee, H Lee, L Wang
arXiv preprint arXiv:2305.14934, 2023
432023
Sprig: Improving large language model performance by system prompt optimization
L Zhang, T Ergen, L Logeswaran, M Lee, D Jurgens
arXiv preprint arXiv:2410.14826, 2024
372024
Few-shot reranking for multi-hop QA via language model prompting
M Khalifa, L Logeswaran, M Lee, H Lee, L Wang
Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023
302023
Few-shot subgoal planning with language models
L Logeswaran, Y Fu, M Lee, H Lee
arXiv preprint arXiv:2205.14288, 2022
262022
You don’t need a personality test to know these models are unreliable: Assessing the reliability of large language models on psychometric instruments
B Shu, L Zhang, M Choi, L Dunagan, L Logeswaran, M Lee, D Card, ...
Proceedings of the 2024 Conference of the North American Chapter of the …, 2024
222024
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
182023
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