Scale Invariant Solutions for Overdetermined Linear Systems with Applications to Reinforcement Learning. - Rahul Madhavan; Gugan Thoppe; Hemanta Makwana (CoRR, 2021)

Intervention Efficient Algorithm for Two-Stage Causal MDPs. - Rahul Madhavan; Aurghya Maiti; Gaurav Sinha 001; Siddharth Barman (CoRR, 2021)

CFL: Causally Fair Language Models Through Token-level Attribute Controlled Generation. - Rahul Madhavan; Rishabh Garg; Kahini Wadhawan; Sameep Mehta (ACL (Findings), 2023)

Learning good interventions in causal graphs via covering. - Ayush Sawarni; Rahul Madhavan; Gaurav Sinha 001; Siddharth Barman (UAI, 2023)

Causal ATE Mitigates Unintended Bias in Controlled Text Generation. - Rahul Madhavan; Kahini Wadhawan (CoRR, 2023)

Time-Reversal Provides Unsupervised Feedback to LLMs. - Yerram Varun; Rahul Madhavan; Sravanti Addepalli; Arun Sai Suggala; Karthikeyan Shanmugam; Prateek Jain 002 (NeurIPS, 2024)

Causal Contextual Bandits with Adaptive Context. - Rahul Madhavan; Aurghya Maiti; Gaurav Sinha 001; Siddharth Barman (RLJ, 2024)

SWEPO: Simultaneous Weighted Preference Optimization for Group Contrastive Alignment. - Taneesh Gupta; Rahul Madhavan; Xuchao Zhang; Chetan Bansal; Saravan Rajmohan (CoRR, 2024)

REFA: Reference Free Alignment for multi-preference optimization. - Taneesh Gupta; Rahul Madhavan; Xuchao Zhang; Chetan Bansal; Saravan Rajmohan (CoRR, 2024)

CARMO: Dynamic Criteria Generation for Context Aware Reward Modelling. - Taneesh Gupta; Shivam Shandilya; Xuchao Zhang; Rahul Madhavan; Supriyo Ghosh; Chetan Bansal; Huaxiu Yao; Saravan Rajmohan (ACL (Findings), 2025)

AMPO: Active Multi-Preference Optimization. - Taneesh Gupta; Rahul Madhavan; Xuchao Zhang; Chetan Bansal; Saravan Rajmohan (CoRR, 2025)

Robust Reward Modeling via Causal Rubrics. - Pragya Srivastava; Harman Singh; Rahul Madhavan; Gandharv Patil; Sravanti Addepalli; Arun Sai Suggala; Rengarajan Aravamudhan; Soumya Sharma; Anirban Laha; Aravindan Raghuveer; Karthikeyan Shanmugam; Doina Precup (CoRR, 2025)