RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information. - Shikhar Vashishth; Rishabh Joshi; Sai Suman Prayaga; Chiranjib Bhattacharyya; Partha P. Talukdar (EMNLP, 2018)

Removal of Parameter Adjustment of Frangi Filters in Case of Coronary Angiograms. - Dhruv Gosain; Rishabh Joshi (CoRR, 2018)

A Team Based Player Versus Player Recommender Systems Framework For Player Improvement. - Rishabh Joshi; Varun Gupta 004; Xinyue Li; Yue Cui; Ziwen Wang; Yaser Norouzzadeh Ravari; Diego Klabjan; Rafet Sifa; Azita Parsaeian; Anders Drachen; Simon Demediuk (ACSW, 2019)

Keeping Up Appearances: Computational Modeling of Face Acts in Persuasion Oriented Discussions. - Ritam Dutt; Rishabh Joshi; Carolyn P. Rosé (EMNLP (1), 2020)

Analysing the Extent of Misinformation in Cancer Related Tweets. - Rakesh Bal; Sayan Sinha; Swastika Dutta; Rishabh Joshi; Sayan Ghosh 002; Ritam Dutt (ICWSM, 2020)

AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue. - Gaurav Kumar; Rishabh Joshi; Jaspreet Singh; Promod Yenigalla (LREC, 2020)

LTIatCMU at SemEval-2020 Task 11: Incorporating Multi-Level Features for Multi-Granular Propaganda Span Identification. - Sopan Khosla; Rishabh Joshi; Ritam Dutt; Alan W. Black; Yulia Tsvetkov (SemEval@COLING, 2020)

MedType: Improving Medical Entity Linking with Semantic Type Prediction. - Shikhar Vashishth; Rishabh Joshi; Ritam Dutt; Denis Newman-Griffis; Carolyn P. Rosé (CoRR, 2020)

ResPer: Computationally Modelling Resisting Strategies in Persuasive Conversations. - Ritam Dutt; Sayan Sinha; Rishabh Joshi; Surya Shekhar Chakraborty; Meredith Riggs; Xinru Yan; Haogang Bao; Carolyn P. Rosé (EACL, 2021)

DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues. - Rishabh Joshi; Vidhisha Balachandran; Shikhar Vashishth; Alan W. Black; Yulia Tsvetkov (ICLR, 2021)

Improving broad-coverage medical entity linking with semantic type prediction and large-scale datasets. - Shikhar Vashishth; Denis Newman-Griffis; Rishabh Joshi; Ritam Dutt; Carolyn P. Rosé (J. Biomed. Informatics, 2021)

Unsupervised Keyphrase Extraction via Interpretable Neural Networks. - Rishabh Joshi; Vidhisha Balachandran; Emily Saldanha; Maria Glenski; Svitlana Volkova; Yulia Tsvetkov (EACL (Findings), 2023)

Calibrating Sequence likelihood Improves Conditional Language Generation. - Yao Zhao; Misha Khalman; Rishabh Joshi; Shashi Narayan; Mohammad Saleh; Peter J. Liu (ICLR, 2023)

SLiC-HF: Sequence Likelihood Calibration with Human Feedback. - Yao Zhao; Rishabh Joshi; Tianqi Liu 002; Misha Khalman; Mohammad Saleh; Peter J. Liu (CoRR, 2023)

Calibrating Likelihoods towards Consistency in Summarization Models. - Polina Zablotskaia; Misha Khalman; Rishabh Joshi; Livio Baldini Soares; Shoshana Jakobovits; Joshua Maynez; Shashi Narayan (CoRR, 2023)

Statistical Rejection Sampling Improves Preference Optimization. - Tianqi Liu 002; Yao Zhao; Rishabh Joshi; Misha Khalman; Mohammad Saleh; Peter J. Liu; Jialu Liu (ICLR, 2024)

Human Alignment of Large Language Models through Online Preference Optimisation. - Daniele Calandriello; Zhaohan Daniel Guo; Rémi Munos; Mark Rowland 001; Yunhao Tang; Bernardo Ávila Pires; Pierre Harvey Richemond; Charline Le Lan; Michal Valko; Tianqi Liu 002; Rishabh Joshi; Zeyu Zheng; et al. (ICML, 2024)

Offline Regularised Reinforcement Learning for Large Language Models Alignment. - Pierre Harvey Richemond; Yunhao Tang; Daniel Guo 001; Daniele Calandriello; Mohammad Gheshlaghi Azar; Rafael Rafailov; Bernardo Ávila Pires; Eugene Tarassov; Lucas Spangher; Will Ellsworth; Aliaksei Severyn; Jonathan Mallinson; et al. (CoRR, 2024)

RRM: Robust Reward Model Training Mitigates Reward Hacking. - Tianqi Liu 002; Wei Xiong 015; Jie Ren 006; Lichang Chen; Junru Wu; Rishabh Joshi; Yang Gao; Jiaming Shen; Zhen Qin 001; Tianhe Yu; Daniel Sohn; Anastasiia Makarova; et al. (CoRR, 2024)

Preference Optimization as Probabilistic Inference. - Abbas Abdolmaleki; Bilal Piot; Bobak Shahriari; Jost Tobias Springenberg; Tim Hertweck; Rishabh Joshi; Junhyuk Oh; Michael Bloesch; Thomas Lampe; Nicolas Heess; Jonas Buchli; Martin A. Riedmiller (CoRR, 2024)

Evolving Alignment via Asymmetric Self-Play. - Ziyu Ye; Rishabh Agarwal; Tianqi Liu 002; Rishabh Joshi; Sarmishta Velury; Quoc V. Le; Qijun Tan; Yuan Liu (CoRR, 2024)

RRM: Robust Reward Model Training Mitigates Reward Hacking. - Tianqi Liu 002; Wei Xiong 015; Jie Ren 006; Lichang Chen; Junru Wu; Rishabh Joshi; Yang Gao; Jiaming Shen; Zhen Qin 001; Tianhe Yu; Daniel Sohn; Anastasia Makarova; et al. (ICLR, 2025)

Building Math Agents with Multi-Turn Iterative Preference Learning. - Wei Xiong 015; Chengshuai Shi; Jiaming Shen; Aviv Rosenberg 002; Zhen Qin 001; Daniele Calandriello; Misha Khalman; Rishabh Joshi; Bilal Piot; Mohammad Saleh; Chi Jin; Tong Zhang 001; et al. (ICLR, 2025)

Learning from negative feedback, or positive feedback or both. - Abbas Abdolmaleki; Bilal Piot; Bobak Shahriari; Jost Tobias Springenberg; Tim Hertweck; Michael Bloesch; Rishabh Joshi; Thomas Lampe; Junhyuk Oh; Nicolas Heess; Jonas Buchli; Martin A. Riedmiller (ICLR, 2025)

LiPO: Listwise Preference Optimization through Learning-to-Rank. - Tianqi Liu 002; Zhen Qin 001; Junru Wu; Jiaming Shen; Misha Khalman; Rishabh Joshi; Yao Zhao; Mohammad Saleh; Simon Baumgartner; Jialu Liu; Peter J. Liu; Xuanhui Wang (NAACL (Long Papers), 2025)