Mukherjee, Subhabrata

Credibility Assessment of Textual Claims on the Web

Popat, K., Mukherjee, S., Strötgen, J., & Weikum, G. (2016) · Proceedings of the 25th ACM International on Conference on Information and Knowledge Management

Misinformation and Its ImpactsSpam and Phishing Detection

Cited by 177

AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning

Wang, Y., Agarwal, S., Mukherjee, S., Liu, X., Gao, J., Awadallah, A. H., & Gao, J. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 77

Retrieval-Augmented Generation with Graphs (GraphRAG)

Han, H., Wang, Y., Shomer, H., Guo, K., Ding, J., Lei, Y., Halappanavar, M., Rossi, R. A., Mukherjee, S., Tang, X., et al. (2025) · arXiv

Topic ModelingAdvanced Graph Neural Networks

Cited by 34

ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models

Xu, B., Peng, Z., Lei, B., Mukherjee, S., Liu, Y., & Xu, D. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 17

Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing

Ding, D., Mallick, A., Wang, C., Sim, R., Mukherjee, S., Ruhle, V., Lakshmanan, L. V. S., & Awadallah, A. H. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models

Javaheripi, M., de Rosa, G. H., Mukherjee, S., Shah, S., Religa, T. L., Mendes, C. C. T., Bubeck, S., Koushanfar, F., & Dey, D. (2022) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 11