Corporate News Classification and Valence Prediction: A Supervised Approach. - Syed Aqueel Haider; Rishabh Mehrotra (WASSA@ACL, 2011)

Dictionary based sparse representation for domain adaptation. - Rishabh Mehrotra; Rushabh Agrawal; Syed Aqueel Haider (CIKM, 2012)

Improving LDA topic models for microblogs via tweet pooling and automatic labeling. - Rishabh Mehrotra; Scott Sanner; Wray L. Buntine; Lexing Xie (SIGIR, 2013)

Task-Based User Modelling for Personalization via Probabilistic Matrix Factorization. - Rishabh Mehrotra; Emine Yilmaz; Manisha Verma (RecSys Posters, 2014)

Terms, Topics & Tasks: Enhanced User Modelling for Better Personalization. - Rishabh Mehrotra; Emine Yilmaz (ICTIR, 2015)

Representative & Informative Query Selection for Learning to Rank using Submodular Functions. - Rishabh Mehrotra; Emine Yilmaz (SIGIR, 2015)

Overview of the TREC 2015 Tasks Track. - Emine Yilmaz; Manisha Verma; Rishabh Mehrotra; Evangelos Kanoulas; Ben Carterette; Nick Craswell (TREC, 2015)

Topics, Tasks & Beyond: Learning Representations for Personalization. - Rishabh Mehrotra (WSDM, 2015)

Modeling the Evolution of User-generated Content on a Large Video Sharing Platform. - Rishabh Mehrotra; Prasanta Bhattacharya (WWW (Companion Volume), 2015)

Towards Hierarchies of Search Tasks & Subtasks. - Rishabh Mehrotra; Emine Yilmaz (WWW (Companion Volume), 2015)

The Information Network: Exploiting Causal Dependencies in Online Information Seeking. - Prasanta Bhattacharya; Rishabh Mehrotra (CHIIR, 2016)

Characterizing Users' Multi-Tasking Behavior in Web Search. - Rishabh Mehrotra; Prasanta Bhattacharya; Emine Yilmaz (CHIIR, 2016)

Deconstructing Complex Search Tasks: a Bayesian Nonparametric Approach for Extracting Sub-tasks. - Rishabh Mehrotra; Prasanta Bhattacharya; Emine Yilmaz (HLT-NAACL, 2016)

Query Log Mining for Inferring User Tasks and Needs. - Rishabh Mehrotra; Emine Yilmaz (ECML/PKDD (3), 2016)

Uncovering Task Based Behavioral Heterogeneities in Online Search Behavior. - Rishabh Mehrotra; Prasanta Bhattacharya; Emine Yilmaz (SIGIR, 2016)

Overview of the TREC Tasks Track 2016. - Manisha Verma; Emine Yilmaz; Rishabh Mehrotra; Evangelos Kanoulas; Ben Carterette; Nick Craswell; Peter Bailey (TREC, 2016)

Deep Sequential Models for Task Satisfaction Prediction. - Rishabh Mehrotra; Ahmed Hassan Awadallah; Milad Shokouhi; Emine Yilmaz; Imed Zitouni; Ahmed El Kholy; Madian Khabsa (CIKM, 2017)

Task Embeddings: Learning Query Embeddings using Task Context. - Rishabh Mehrotra; Emine Yilmaz (CIKM, 2017)

Predictive Power of Online and Offline Behavior Sequences: Evidence from a Micro-finance Context. - Rishabh Mehrotra; Prasanta Bhattacharya; Tianhui Tan; Tuan Phan (ICIS, 2017)

Characterizing and Predicting Supply-side Engagement on Video Sharing Platforms Using a Hawkes Process Model. - Rishabh Mehrotra; Prasanta Bhattacharya (ICTIR, 2017)

Extracting Hierarchies of Search Tasks & Subtasks via a Bayesian Nonparametric Approach. - Rishabh Mehrotra; Emine Yilmaz (SIGIR, 2017)

User Interaction Sequences for Search Satisfaction Prediction. - Rishabh Mehrotra; Imed Zitouni; Ahmed Hassan Awadallah; Ahmed El Kholy; Madian Khabsa (SIGIR, 2017)

TREC 2017 Tasks Track Overview. - Evangelos Kanoulas; Emine Yilmaz; Rishabh Mehrotra; Ben Carterette; Nick Craswell; Peter Bailey (TREC, 2017)

Auditing Search Engines for Differential Satisfaction Across Demographics. - Rishabh Mehrotra; Ashton Anderson; Fernando Diaz 001; Amit Sharma 007; Hanna M. Wallach; Emine Yilmaz (WWW (Companion Volume), 2017)

Identifying User Sessions in Interactions with Intelligent Digital Assistants. - Rishabh Mehrotra; Ahmed El Kholy; Imed Zitouni; Milad Shokouhi; Ahmed Hassan (WWW (Companion Volume), 2017)

Characterizing and Predicting Supply-side Engagement on Crowd-contributed Video Sharing Platforms. - Rishabh Mehrotra; Prasanta Bhattacharya (CoRR, 2017)

Towards a Fair Marketplace: Counterfactual Evaluation of the trade-off between Relevance, Fairness & Satisfaction in Recommendation Systems. - Rishabh Mehrotra; James McInerney; Hugues Bouchard; Mounia Lalmas; Fernando Diaz 001 (CIKM, 2018)

Explore, exploit, and explain: personalizing explainable recommendations with bandits. - James McInerney; Benjamin Lacker; Samantha Hansen; Karl Higley; Hugues Bouchard; Alois Gruson; Rishabh Mehrotra (RecSys, 2018)

LearnIR: WSDM 2018 Workshop on Learning from User Interactions. - Rishabh Mehrotra; Ahmed Hassan Awadallah; Emine Yilmaz (WSDM, 2018)

Inferring User Needs & Tasks from User Interactions. - Rishabh Mehrotra (SIGIR Forum, 2018)

Inferring user needs and tasks from user interactions. - Rishabh Mehrotra (2018)

Towards Task Understanding in Visual Settings. - Sebastin Santy; Wazeer Zulfikar; Rishabh Mehrotra; Emine Yilmaz (AAAI, 2019)

Recommendations in a marketplace. - Rishabh Mehrotra; Benjamin A. Carterette (RecSys, 2019)

The Music Streaming Sessions Dataset. - Brian Brost; Rishabh Mehrotra; Tristan Jehan (WWW, 2019)

Deriving User- and Content-specific Rewards for Contextual Bandits. - Paolo Dragone; Rishabh Mehrotra; Mounia Lalmas (WWW, 2019)

Jointly Leveraging Intent and Interaction Signals to Predict User Satisfaction with Slate Recommendations. - Rishabh Mehrotra; Mounia Lalmas; Doug Kenney; Thomas Lim-Meng; Golli Hashemian (WWW, 2019)

Query Understanding for Surfacing Under-served Music Content. - Federico Tomasi; Rishabh Mehrotra; Aasish Pappu; Judith Bütepage; Brian Brost; Hugo Galvão; Mounia Lalmas (CIKM, 2020)

Counterfactual Evaluation of Slate Recommendations with Sequential Reward Interactions. - James McInerney; Brian Brost; Praveen Chandar; Rishabh Mehrotra; Benjamin A. Carterette (KDD, 2020)

Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys. - Rishabh Mehrotra; Ben Carterette; Yong Li 008; Quanming Yao; Chen Gao 001; James T. Kwok; Qiang Yang 001; Isabelle Guyon (KDD, 2020)

Learning with Limited Labels via Momentum Damped & Differentially Weighted Optimization. - Rishabh Mehrotra; Ashish Gupta (KDD, 2020)

Bandit based Optimization of Multiple Objectives on a Music Streaming Platform. - Rishabh Mehrotra; Niannan Xue; Mounia Lalmas (KDD, 2020)

Joint Attention Neural Model for Demand Prediction in Online Marketplaces. - Ashish Gupta; Rishabh Mehrotra (NLDL, 2020)

Contextual and Sequential User Embeddings for Large-Scale Music Recommendation. - Casper Hansen; Christian Hansen 004; Lucas Maystre; Rishabh Mehrotra; Brian Brost; Federico Tomasi; Mounia Lalmas (RecSys, 2020)

Inferring the Causal Impact of New Track Releases on Music Recommendation Platforms through Counterfactual Predictions. - Rishabh Mehrotra; Prasanta Bhattacharya; Mounia Lalmas (RecSys, 2020)

Investigating Listeners' Responses to Divergent Recommendations. - Rishabh Mehrotra; Chirag Shah 001; Benjamin A. Carterette (RecSys, 2020)

Investigating the Impact of Audio States & Transitions for Track Sequencing in Music Streaming Sessions. - Aaron Ng; Rishabh Mehrotra (RecSys, 2020)

SUM'20: State-based User Modelling. - Sahan Bulathwela; María Pérez-Ortiz 001; Rishabh Mehrotra; Davor Orlic; Colin de la Higuera; John Shawe-Taylor; Emine Yilmaz (WSDM, 2020)

Algorithmic Effects on the Diversity of Consumption on Spotify. - Ashton Anderson; Lucas Maystre; Ian Anderson 003; Rishabh Mehrotra; Mounia Lalmas (WWW, 2020)

Leveraging Behavioral Heterogeneity Across Markets for Cross-Market Training of Recommender Systems. - Kevin Roitero; Ben Carterette; Rishabh Mehrotra; Mounia Lalmas (WWW (Companion Volume), 2020)

Special issue on learning from user interactions. - Rishabh Mehrotra; Ahmed Hassan Awadallah; Emine Yilmaz (Inf. Retr. J., 2020)

Report on the WSDM 2020 workshop on state-based user modelling (SUM'20). - Sahan Bulathwela; María Pérez-Ortiz 001; Rishabh Mehrotra; Davor Orlic; Colin de la Higuera; John Shawe-Taylor; Emine Yilmaz (SIGIR Forum, 2020)

Algorithmic Balancing of Familiarity, Similarity, & Discovery in Music Recommendations. - Rishabh Mehrotra (CIKM, 2021)

Multi-Task Learning of Graph-based Inductive Representations of Music Content. - Antonia Saravanou; Federico Tomasi; Rishabh Mehrotra; Mounia Lalmas (ISMIR, 2021)

Shifting Consumption towards Diverse Content on Music Streaming Platforms. - Christian Hansen 004; Rishabh Mehrotra; Casper Hansen; Brian Brost; Lucas Maystre; Mounia Lalmas (WSDM, 2021)

Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders. - Olivier Jeunen; Ciarán M. Gilligan-Lee; Rishabh Mehrotra; Mounia Lalmas (NeurIPS, 2022)

Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing. - Emanuele Bugliarello; Rishabh Mehrotra; James Kirk; Mounia Lalmas (WWW, 2022)

The Multisided Complexity of Fairness in Recommender Systems. - Nasim Sonboli; Robin Burke; Michael D. Ekstrand; Rishabh Mehrotra (AI Mag., 2022)

Task Preferences across Languages on Community Question Answering Platforms. - Sebastin Santy; Prasanta Bhattacharya; Rishabh Mehrotra (CoRR, 2022)

Exploiting Sequential Music Preferences via Optimisation-Based Sequencing. - Dmitrii Moor; Yi Yuan; Rishabh Mehrotra; Zhenwen Dai; Mounia Lalmas (CIKM, 2023)

On Gradient Boosted Decision Trees and Neural Rankers: A Case-Study on Short-Video Recommendations at ShareChat. - Olivier Jeunen; Hitesh Sagtani; Himanshu Doi; Rasul Karimov; Neeti Pokharna; Md. Danish Kalim; Aleksei Ustimenko; Christopher Green; Rishabh Mehrotra; Wenzhe Shi (FIRE, 2023)

Formulating Video Watch Success Signals for Recommendations on Short Video Platforms. - Srijan Saket; Sai Baba Reddy Velugoti; Rishabh Mehrotra (LERI@RecSys, 2023)

Quantifying and Leveraging User Fatigue for Interventions in Recommender Systems. - Hitesh Sagtani; Madan Gopal Jhawar; Akshat Gupta; Rishabh Mehrotra (SIGIR, 2023)

MEMER - Multimodal Encoder for Multi-signal Early-stage Recommendations. - Mohit Agarwal 004; Srijan Saket; Rishabh Mehrotra (WWW (Companion Volume), 2023)

AI-assisted Coding with Cody: Lessons from Context Retrieval and Evaluation for Code Recommendations. - Jan Hartman; Hitesh Sagtani; Julie Tibshirani; Rishabh Mehrotra (RecSys, 2024)

Ad-load Balancing via Off-policy Learning in a Content Marketplace. - Hitesh Sagtani; Madan Gopal Jhawar; Rishabh Mehrotra; Olivier Jeunen (WSDM, 2024)

AI-assisted Coding with Cody: Lessons from Context Retrieval and Evaluation for Code Recommendations. - Jan Hartman; Rishabh Mehrotra; Hitesh Sagtani; Dominic Cooney; Rafal Gajdulewicz; Beyang Liu; Julie Tibshirani; Quinn Slack (CoRR, 2024)

Crafting Tomorrow: The Influence of Design Choices on Fresh Content in Social Media Recommendation. - Srijan Saket; Mohit Agarwal 004; Rishabh Mehrotra (CoRR, 2024)

Improving FIM Code Completions via Context & Curriculum Based Learning. - Hitesh Sagtani; Rishabh Mehrotra; Beyang Liu (WSDM, 2025)