Multilingual Pseudo-Relevance Feedback: Performance Study of Assisting Languages. - Manoj Kumar Chinnakotla; Karthik Raman 001; Pushpak Bhattacharyya (ACL, 2010)

On Improving Pseudo-Relevance Feedback Using Pseudo-Irrelevant Documents. - Karthik Raman 001; Raghavendra Udupa; Pushpak Bhattacharyya; Abhijit Bhole (ECIR, 2010)

Multilingual PRF: english lends a helping hand. - Manoj Kumar Chinnakotla; Karthik Raman 001; Pushpak Bhattacharyya (SIGIR, 2010)

Structured learning of two-level dynamic rankings. - Karthik Raman 001; Thorsten Joachims; Pannaga Shivaswamy (CIKM, 2011)

Learning from mistakes: towards a correctable learning algorithm. - Karthik Raman 001; Krysta M. Svore; Ran Gilad-Bachrach; Christopher J. C. Burges (CIKM, 2012)

Online learning to diversify from implicit feedback. - Karthik Raman 001; Pannaga Shivaswamy; Thorsten Joachims (KDD, 2012)

Stable Coactive Learning via Perturbation. - Karthik Raman 001; Thorsten Joachims; Pannaga Shivaswamy; Tobias Schnabel (ICML (3), 2013)

Beyond myopic inference in big data pipelines. - Karthik Raman 001; Adith Swaminathan; Johannes Gehrke; Thorsten Joachims (KDD, 2013)

Learning Socially Optimal Information Systems from Egoistic Users. - Karthik Raman 001; Thorsten Joachims (ECML/PKDD (2), 2013)

Toward whole-session relevance: exploring intrinsic diversity in web search. - Karthik Raman 001; Paul N. Bennett; Kevyn Collins-Thompson (SIGIR, 2013)

Methods for ordinal peer grading. - Karthik Raman 001; Thorsten Joachims (KDD, 2014)

Understanding Intrinsic Diversity in Web Search: Improving Whole-Session Relevance. - Karthik Raman 001; Paul N. Bennett; Kevyn Collins-Thompson (ACM Trans. Inf. Syst., 2014)

Bayesian Ordinal Peer Grading. - Karthik Raman 001; Thorsten Joachims (L@S, 2015)

Bayesian Ordinal Aggregation of Peer Assessments: A Case Study on KDD 2015. - Thorsten Joachims; Karthik Raman 001 (Solving Large Scale Learning Tasks, 2016)

Learning Multilingual Word Embeddings Using Image-Text Data. - Karan Singhal; Karthik Raman 001; Balder ten Cate (CoRR, 2019)

Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation. - Aditya Siddhant; Melvin Johnson; Henry Tsai; Naveen Arivazhagan; Jason Riesa; Ankur Bapna; Orhan Firat; Karthik Raman 001 (CoRR, 2019)

Evaluating the Cross-Lingual Effectiveness of Massively Multilingual Neural Machine Translation. - Aditya Siddhant; Melvin Johnson; Henry Tsai; Naveen Ari; Jason Riesa; Ankur Bapna; Orhan Firat; Karthik Raman 001 (AAAI, 2020)

DiPair: Fast and Accurate Distillation for Trillion-ScaleText Matching and Pair Modeling. - Jiecao Chen; Liu Yang 005; Karthik Raman 001; Michael Bendersky; Jung-Jung Yeh; Yun Zhou; Marc Najork; Danyang Cai; Ehsan Emadzadeh (EMNLP (Findings), 2020)

Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description (version 1.0). - Shailesh Bavadekar; Andrew M. Dai; John Davis; Damien Desfontaines; Ilya Eckstein; Katie Everett; Alex Fabrikant; Gerardo Flores; Evgeniy Gabrilovich; Krishna Gadepalli; Shane Glass; Rayman Huang; et al. (CoRR, 2020)

DiPair: Fast and Accurate Distillation for Trillion-Scale Text Matching and Pair Modeling. - Jiecao Chen; Liu Yang 005; Karthik Raman 001; Michael Bendersky; Jung-Jung Yeh; Yun Zhou; Marc Najork; Danyang Cai; Ehsan Emadzadeh (CoRR, 2020)

DICT-MLM: Improved Multilingual Pre-Training using Bilingual Dictionaries. - Aditi Chaudhary; Karthik Raman 001; Krishna Srinivasan; Jiecao Chen (CoRR, 2020)

WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning. - Krishna Srinivasan; Karthik Raman 001; Jiecao Chen; Michael Bendersky; Marc Najork (SIGIR, 2021)

Transforming Sequence Tagging Into A Seq2Seq Task. - Karthik Raman 001; Iftekhar Naim; Jiecao Chen; Kazuma Hashimoto; Kiran Yalasangi; Krishna Srinivasan (EMNLP, 2022)

QUILL: Query Intent with Large Language Models using Retrieval Augmentation and Multi-stage Distillation. - Krishna Srinivasan; Karthik Raman 001; Anupam Samanta; Lingrui Liao; Luca Bertelli; Michael Bendersky (EMNLP (Industry Track), 2022)

Multi-Task Retrieval-Augmented Text Generation with Relevance Sampling. - Sebastian Hofstätter; Jiecao Chen; Karthik Raman 001; Hamed Zamani (CoRR, 2022)

GROOT: Corrective Reward Optimization for Generative Sequential Labeling. - Kazuma Hashimoto; Karthik Raman 001 (CoRR, 2022)

How Does Beam Search improve Span-Level Confidence Estimation in Generative Sequence Labeling? - Kazuma Hashimoto; Iftekhar Naim; Karthik Raman 001 (CoRR, 2022)

Exploring the Viability of Synthetic Query Generation for Relevance Prediction. - Aditi Chaudhary; Karthik Raman 001; Krishna Srinivasan; Kazuma Hashimoto; Mike Bendersky; Marc Najork (eCom@SIGIR, 2023)

FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation. - Sebastian Hofstätter; Jiecao Chen; Karthik Raman 001; Hamed Zamani (SIGIR, 2023)

Ambiguity-Aware In-Context Learning with Large Language Models. - Lingyu Gao; Aditi Chaudhary; Krishna Srinivasan; Kazuma Hashimoto; Karthik Raman 001; Michael Bendersky (CoRR, 2023)

It's All Relative! - A Synthetic Query Generation Approach for Improving Zero-Shot Relevance Prediction. - Aditi Chaudhary; Karthik Raman 001; Michael Bendersky (NAACL-HLT (Findings), 2024)

Take One Step at a Time to Know Incremental Utility of Demonstration: An Analysis on Reranking for Few-Shot In-Context Learning. - Kazuma Hashimoto; Karthik Raman 001; Michael Bendersky (NAACL-HLT, 2024)

Refract ICL: Rethinking Example Selection in the Era of Million-Token Models. - Arjun R. Akula; Kazuma Hashimoto; Krishna Srinivasan; Aditi Chaudhary; Karthik Raman 001; Michael Bendersky (CoRR, 2025)