Panda, Rameswar

AdaShare: Learning What To Share For Efficient Deep Multi-Task Learning

Sun, X., Panda, R., Feris, R., & Saenko, K. (2019) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 169

IA-RED$^2$: Interpretability-Aware Redundancy Reduction for Vision Transformers

Pan, B., Panda, R., Jiang, Y., Wang, Z., Feris, R., & Oliva, A. (2021) · arXiv

Advanced Neural Network ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 70

Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks

Abdelaziz, I., Basu, K., Agarwal, M., Kumaravel, S., Stallone, M., Panda, R., Rizk, Y., Bhargav, G. P. S., Crouse, M., Gunasekara, C., et al. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing: Industry Track

Topic ModelingNatural Language Processing Techniques

Cited by 22

Gated Linear Attention Transformers with Hardware-Efficient Training

Yang, S., Wang, B., Shen, Y., Panda, R., & Kim, Y. (2023) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 10

Data Engineering for Scaling Language Models to 128K Context

Fu, Y., Panda, R., Niu, X., Yue, X., Hajishirzi, H., Kim, Y., & Peng, H. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 3