Reinforcement Learning Based Dialogue Management Strategy. - Tulika Saha; Dhawal Gupta; Sriparna Saha 001; Pushpak Bhattacharyya (ICONIP (3), 2018)

Gradient Temporal-Difference Learning with Regularized Corrections. - Sina Ghiassian; Andrew Patterson; Shivam Garg 006; Dhawal Gupta; Adam White 001; Martha White (ICML, 2020)

Towards integrated dialogue policy learning for multiple domains and intents using Hierarchical Deep Reinforcement Learning. - Tulika Saha; Dhawal Gupta; Sriparna Saha 001; Pushpak Bhattacharyya (Expert Syst. Appl., 2020)

Structural Credit Assignment in Neural Networks using Reinforcement Learning. - Dhawal Gupta; Gabor Mihucz; Matthew Schlegel; James E. Kostas; Philip S. Thomas; Martha White (NeurIPS, 2021)

Emotion Aided Dialogue Act Classification for Task-Independent Conversations in a Multi-modal Framework. - Tulika Saha; Dhawal Gupta; Sriparna Saha 001; Pushpak Bhattacharyya (Cogn. Comput., 2021)

A hierarchical approach for efficient multi-intent dialogue policy learning. - Tulika Saha; Dhawal Gupta; Sriparna Saha 001; Pushpak Bhattacharyya (Multim. Tools Appl., 2021)

A Unified Dialogue Management Strategy for Multi-intent Dialogue Conversations in Multiple Languages. - Tulika Saha; Dhawal Gupta; Sriparna Saha 001; Pushpak Bhattacharyya (ACM Trans. Asian Low Resour. Lang. Inf. Process., 2021)

A Mixture-of-Expert Approach to RL-based Dialogue Management. - Yinlam Chow; Aza Tulepbergenov; Ofir Nachum; Dhawal Gupta; Moonkyung Ryu; Mohammad Ghavamzadeh; Craig Boutilier (ICLR, 2023)

Behavior Alignment via Reward Function Optimization. - Dhawal Gupta; Yash Chandak; Scott M. Jordan; Philip S. Thomas; Bruno C. da Silva 001 (NeurIPS, 2023)

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. - Dhawal Gupta; Yinlam Chow; Azamat Tulepbergenov; Mohammad Ghavamzadeh; Craig Boutilier (NeurIPS, 2023)

Offline Reinforcement Learning for Mixture-of-Expert Dialogue Management. - Dhawal Gupta; Yinlam Chow; Mohammad Ghavamzadeh; Craig Boutilier (CoRR, 2023)

Coagent Networks: Generalized and Scaled. - James E. Kostas; Scott M. Jordan; Yash Chandak; Georgios Theocharous; Dhawal Gupta; Martha White; Bruno Castro da Silva; Philip S. Thomas (CoRR, 2023)

Exploring the impact of low-rank adaptation on the performance, efficiency, and regularization of RLHF. - Simeng Sun; Dhawal Gupta; Mohit Iyyer (CoRR, 2023)

From Past to Future: Rethinking Eligibility Traces. - Dhawal Gupta; Scott M. Jordan; Shreyas Chaudhari; Bo Liu 006; Philip S. Thomas; Bruno Castro da Silva (AAAI, 2024)

Authentication in IoT Networks via Machine Learning and Deep Learning: A Review. - Mehwash Weqar; Shabana Mehfuz; Dhawal Gupta (ICCCNT, 2024)

Mitigating the Curse of Horizon in Monte-Carlo Returns. - Alex Ayoub; David Szepesvari; Francesco Zanini; Bryan Chan; Dhawal Gupta; Bruno Castro da Silva; Dale Schuurmans (RLJ, 2024)

ICU-Sepsis: A Benchmark MDP Built from Real Medical Data. - Kartik Choudhary; Dhawal Gupta; Philip S. Thomas (RLJ, 2024)

Adaptive Switching Based Data-Communication Model for Internet of Healthcare Things Networks. - Mehwash Weqar; Shabana Mehfuz; Dhawal Gupta; Shabana Urooj (IEEE Access, 2024)

A Safe Exploration Strategy for Model-free Task Adaptation in Safety-constrained Grid Environments. - Erfan Entezami; Mahsa Sahebdel; Dhawal Gupta (CoRR, 2024)

Mitigating Preference Hacking in Policy Optimization with Pessimism. - Dhawal Gupta; Adam Fisch; Christoph Dann; Alekh Agarwal (CoRR, 2025)