Logeswaran, Lajanugen

Generative Adversarial Text to Image Synthesis

Reed, S., Akata, Z., Yan, X., Logeswaran, L., Schiele, B., & Lee, H. (2016) · arXiv

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 2,494

An efficient framework for learning sentence representations

Logeswaran, L., & Lee, H. (2018) · arXiv

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 427

When "a helpful assistant" is not really helpful: Personas in system prompts do not improve performances of large language models

Zheng, M., Pei, J., Logeswaran, L., Lee, M., & Jurgens, D. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Topic ModelingNatural Language Processing Techniques

Cited by 82

Small Language Models Need Strong Verifiers to Self-Correct Reasoning

Zhang, Y., Khalifa, M., Logeswaran, L., Kim, J., Lee, M., Lee, H., & Wang, L. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingNatural Language Processing Techniques

Cited by 6

Small Language Models Need Strong Verifiers to Self-Correct Reasoning

Zhang, Y., Khalifa, M., Logeswaran, L., Kim, J., Lee, M., Lee, H., & Wang, L. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 6

Knowledge Unlearning for Mitigating Privacy Risks in Language Models

Jang, J., Yoon, D., Yang, S., Cha, S., Lee, M., Logeswaran, L., & Seo, M. (2022) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 4