Keshav Santhanam

According to our database, Keshav Santhanam authored at least 15 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines.

Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, Christopher Potts

Proceedings of the Twelfth International Conference on Learning Representations, 2024

ALTO: An Efficient Network Orchestrator for Compound AI Systems.

Keshav Santhanam, Deepti Raghavan, Muhammad Shahir Rahman, Thejas Venkatesh, Neha Kunjal, Pratiksha Thaker, Philip Alexander Levis, Matei Zaharia

Proceedings of the 4th Workshop on Machine Learning and Systems, 2024

2023

Holistic Evaluation of Language Models.

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

Trans. Mach. Learn. Res., 2023

DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines.

Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, Zhiyuan Zhang, Keshav Santhanam, Sri Vardhamanan, Saiful Haq, Ashutosh Sharma, Thomas T. Joshi, Hanna Moazam, Heather Miller, Matei Zaharia, Christopher Potts

CoRR, 2023

Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs.

Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang

CoRR, 2023

Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models.

Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers.

Jon Saad-Falcon, Omar Khattab, Keshav Santhanam, Radu Florian, Martin Franz, Salim Roukos, Avirup Sil, Md. Arafat Sultan, Christopher Potts

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking.

Keshav Santhanam, Jon Saad-Falcon, Martin Franz, Omar Khattab, Avi Sil, Radu Florian, Md. Arafat Sultan, Salim Roukos, Matei Zaharia, Christopher Potts

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP.

Omar Khattab, Keshav Santhanam, Xiang Lisa Li, David Hall, Percy Liang, Christopher Potts, Matei Zaharia

CoRR, 2022

ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction.

Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, Matei Zaharia

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

PLAID: An Efficient Engine for Late Interaction Retrieval.

Keshav Santhanam, Omar Khattab, Christopher Potts, Matei Zaharia

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

DistIR: An Intermediate Representation and Simulator for Efficient Neural Network Distribution.

Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Tim Harris, Matei Zaharia

CoRR, 2021

DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks.

Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Andrew W. Fitzgibbon, Tim Harris

Proceedings of the EuroMLSys@EuroSys 2021, 2021

2020

Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads.

Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, Amar Phanishayee, Matei Zaharia

Proceedings of the 14th USENIX Symposium on Operating Systems Design and Implementation, 2020

2018

ROLA: A New Distributed Transaction Protocol and Its Formal Analysis.

Si Liu, Peter Csaba Ölveczky, Keshav Santhanam, Qi Wang, Indranil Gupta, José Meseguer

Proceedings of the Fundamental Approaches to Software Engineering, 2018