Compact Propositional Encodings of First-Order Theories. - Deepak Ramachandran; Eyal Amir (AAAI, 2005)

Towards Scaleable and Adaptive Document Routing Services. - Deepak Ramachandran; Neil H. Boyette; Isaac K. Cheng; Vikas Krishna; Savitha Srinivasan (IEEE SCC, 2006)

Using Common Sense for Decision Making in an Adventure Game. - Deepak Ramachandran (AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning, 2007)

Bayesian Inverse Reinforcement Learning. - Deepak Ramachandran; Eyal Amir (IJCAI, 2007)

ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning. - Nicolas Loeff; David A. Forsyth; Deepak Ramachandran (ICML, 2008)

Smoothed Sarsa: Reinforcement learning for robot delivery tasks. - Deepak Ramachandran; Rakesh Gupta 001 (ICRA, 2009)

Trust and Online Reputation Systems. - Ming Kwan; Deepak Ramachandran (Computing with Social Trust, 2009)

Dynamic language modeling using Bayesian networks for spoken dialog systems. - Antoine Raux; Neville Mehta; Deepak Ramachandran; Rakesh Gupta 001 (INTERSPEECH, 2010)

Probabilistic Ontology Trees for Belief Tracking in Dialog Systems. - Neville Mehta; Rakesh Gupta 001; Antoine Raux; Deepak Ramachandran; Stefan Krawczyk (SIGDIAL Conference, 2010)

Knowledge and Ignorance in Reinforcement Learning - Deepak Ramachandran (2011)

Improving Hybrid Vehicle Fuel Efficiency Using Inverse Reinforcement Learning. - Adam Vogel; Deepak Ramachandran; Rakesh Gupta 001; Antoine Raux (AAAI, 2012)

Landmark-Based Location Belief Tracking in a Spoken Dialog System. - Yi Ma; Antoine Raux; Deepak Ramachandran; Rakesh Gupta 001 (SIGDIAL Conference, 2012)

Driver familiarity modeling for generating navigation directions. - Deepak Ramachandran; Igor V. Karpov; Rakesh Gupta 001; Antoine Raux (ITSC, 2013)

The Dialog State Tracking Challenge. - Jason D. Williams; Antoine Raux; Deepak Ramachandran; Alan W. Black (SIGDIAL Conference, 2013)

A Speech-Driven Second Screen Application for TV Program Discovery. - Peter Z. Yeh; Benjamin Douglas; William Jarrold; Adwait Ratnaparkhi; Deepak Ramachandran; Peter F. Patel-Schneider; Stephen Laverty; Nirvana Tikku; Sean Brown 001; Jeremy Mendel (AAAI, 2014)

An end-to-end dialog system for TV program discovery. - Deepak Ramachandran; Peter Z. Yeh; William Jarrold; Benjamin Douglas; Adwait Ratnaparkhi; Ronald Provine; Jeremy Mendel; Adam Emfield (SLT, 2014)

The Dialog State Tracking Challenge Series. - Jason D. Williams; Matthew Henderson; Antoine Raux; Blaise Thomson; Alan W. Black; Deepak Ramachandran (AI Mag., 2014)

A TV Program Discovery Dialog System using recommendations. - Deepak Ramachandran; Mark A. Fanty; Ronald Provine; Peter Z. Yeh; William Jarrold; Adwait Ratnaparkhi; Benjamin Douglas (SIGDIAL Conference, 2015)

Belief Tracking with Stacked Relational Trees. - Deepak Ramachandran; Adwait Ratnaparkhi (SIGDIAL Conference, 2015)

An End-to-End Conversational Second Screen Application for TV Program Discovery. - Peter Z. Yeh; Deepak Ramachandran; Benjamin Douglas; Adwait Ratnaparkhi; William Jarrold; Ronald Provine; Peter F. Patel-Schneider; Stephen Laverty; Nirvana Tikku; Sean Brown 001; Jeremy Mendel; Adam Emfield (AI Mag., 2015)

How Large Are Lions? Inducing Distributions over Quantitative Attributes. - Yanai Elazar; Abhijit Mahabal; Deepak Ramachandran; Tania Bedrax-Weiss; Dan Roth 001 (ACL (1), 2019)

Do Language Embeddings capture Scales? - Xikun Zhang 001; Deepak Ramachandran; Ian Tenney; Yanai Elazar; Dan Roth 001 (BlackboxNLP@EMNLP, 2020)

The Association for the Advancement of Artificial Intelligence 2020 Workshop Program. - Grace Bang; Guy Barash; Ryan Beal; Jacques Calì; Mauricio Castillo-Effen; Xin Cynthia Chen; Niyati Chhaya; Rachel Cummings; Rohan Dhoopar; Sebastijan Dumancic; Huáscar Espinoza; Eitan Farchi; et al. (AI Mag., 2020)

Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering. - Najoung Kim; Ellie Pavlick; Burcu Karagol Ayan; Deepak Ramachandran (ACL/IJCNLP (1), 2021)

Subjective Attributes in Conversational Recommendation Systems: Challenges and Opportunities. - Filip Radlinski; Craig Boutilier; Deepak Ramachandran; Ivan Vendrov (AAAI, 2022)

FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue. - Alon Albalak; Yi-Lin Tuan; Pegah Jandaghi; Connor Pryor; Luke Yoffe; Deepak Ramachandran; Lise Getoor; Jay Pujara; William Yang Wang (EMNLP, 2022)

Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. - Christina Göpfert; Yinlam Chow; Chih-Wei Hsu; Ivan Vendrov; Tyler Lu; Deepak Ramachandran; Craig Boutilier (WWW, 2022)

LAMBADA: Backward Chaining for Automated Reasoning in Natural Language. - Mehran Kazemi; Najoung Kim; Deepti Bhatia; Xin Xu; Deepak Ramachandran (ACL (1), 2023)

Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. - Connor Pryor; Quan Yuan 001; Jeremiah Z. Liu; Mehran Kazemi; Deepak Ramachandran; Tania Bedrax-Weiss; Lise Getoor (ACL (1), 2023)

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. - Jeremiah Zhe Liu; Krishnamurthy (Dj) Dvijotham; Jihyeon Lee; Quan Yuan 001; Balaji Lakshminarayanan; Deepak Ramachandran (ICLR, 2023)

Realistic but Non-Identifiable Synthetic User Data Generation. - Isaac Noble; Ivan Vendrov; Xin Xu; Deepak Ramachandran (EvalRS@KDD, 2023)

BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information. - Mehran Kazemi; Quan Yuan 001; Deepti Bhatia; Najoung Kim; Xin Xu; Vaiva Imbrasaite; Deepak Ramachandran (NeurIPS, 2023)

KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. - Sandeep Silwal; Sara Ahmadian; Andrew Nystrom; Andrew McCallum; Deepak Ramachandran; Seyed Mehran Kazemi (SustaiNLP, 2023)

Understanding Finetuning for Factual Knowledge Extraction from Language Models. - Mehran Kazemi; Sid Mittal; Deepak Ramachandran (CoRR, 2023)

Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. - Jeremiah Zhe Liu; Krishnamurthy (Dj) Dvijotham; Jihyeon Lee; Quan Yuan 001; Martin Strobel 001; Balaji Lakshminarayanan; Deepak Ramachandran (CoRR, 2023)

Modeling subjectivity (by Mimicking Annotator Annotation) in toxic comment identification across diverse communities. - Senjuti Dutta; Sid Mittal; Sherol Chen; Deepak Ramachandran; Ravi Rajakumar; Ian Kivlichan; Sunny Mak; Alena Butryna; Praveen K. Paritosh (CoRR, 2023)

Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking. - Jacob Eisenstein; Chirag Nagpal; Alekh Agarwal; Ahmad Beirami; Alex D'Amour; Dj Dvijotham; Adam Fisch; Katherine A. Heller; Stephen Pfohl; Deepak Ramachandran; Peter Shaw 004; Jonathan Berant (CoRR, 2023)

Tackling Provably Hard Representative Selection via Graph Neural Networks. - Mehran Kazemi; Anton Tsitsulin; Hossein Esfandiari; MohammadHossein Bateni; Deepak Ramachandran; Bryan Perozzi; Vahab Mirrokni (Trans. Mach. Learn. Res., 2023)

TaskLAMA: Probing the Complex Task Understanding of Language Models. - Quan Yuan 001; Mehran Kazemi; Xin Xu; Isaac Noble; Vaiva Imbrasaite; Deepak Ramachandran (AAAI, 2024)

Prompt Expansion for Adaptive Text-to-Image Generation. - Siddhartha Datta; Alexander Ku; Deepak Ramachandran; Peter Anderson (ACL (1), 2024)

Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. - Katherine M. Collins; Najoung Kim; Yonatan Bitton; Verena Rieser; Shayegan Omidshafiei; Yushi Hu; Sherol Chen; Senjuti Dutta; Minsuk Chang; Kimin Lee; Youwei Liang; Georgina Evans; et al. (AIES (1), 2024)

Rich Human Feedback for Text-to-Image Generation. - Youwei Liang; Junfeng He; Gang Li; Peizhao Li; Arseniy Klimovskiy; Nicholas Carolan; Jiao Sun; Jordi Pont-Tuset; Sarah Young; Feng Yang; Junjie Ke; Krishnamurthy Dj Dvijotham; et al. (CVPR, 2024)

Demystifying Embedding Spaces using Large Language Models. - Guy Tennenholtz; Yinlam Chow; Chih-Wei Hsu; Jihwan Jeong; Lior Shani; Azamat Tulepbergenov; Deepak Ramachandran; Martin Mladenov; Craig Boutilier (ICLR, 2024)

e-COP : Episodic Constrained Optimization of Policies. - Akhil Agnihotri; Rahul Jain 002; Deepak Ramachandran; Sahil Singla 005 (NeurIPS, 2024)

Understanding Subjectivity through the Lens of Motivational Context in Model-Generated Image Satisfaction. - Senjuti Dutta; Sherol Chen; Sunny Mak; Amnah Ahmad; Katherine Maeve Collins; Alena Butryna; Deepak Ramachandran; Krishnamurthy Dvijotham; Ellie Pavlick; Ravi Rajakumar (CoRR, 2024)

Online Bandit Learning with Offline Preference Data. - Akhil Agnihotri; Rahul Jain 002; Deepak Ramachandran; Zheng Wen 002 (CoRR, 2024)

Imagen 3. - Jason Baldridge; Jakob Bauer; Mukul Bhutani; Nicole Brichtova; Andrew Bunner; Kelvin Chan; Yichang Chen; Sander Dieleman; Yuqing Du; Zach Eaton-Rosen; Hongliang Fei; Nando de Freitas; et al. (CoRR, 2024)

Personalized and Sequential Text-to-Image Generation. - Ofir Nabati; Guy Tennenholtz; Chih-Wei Hsu; Moonkyung Ryu; Deepak Ramachandran; Yinlam Chow; Xiang Li; Craig Boutilier (CoRR, 2024)

Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors. - Christina Göpfert; Alex Haig; Chih-Wei Hsu; Yinlam Chow; Ivan Vendrov; Tyler Lu; Deepak Ramachandran; Hubert Pham; Mohammad Ghavamzadeh; Craig Boutilier (Trans. Recomm. Syst., 2024)

Focus-N-Fix: Region-Aware Fine-Tuning for Text-to-Image Generation. - Xiaoying Xing; Avinab Saha; Junfeng He; Susan Hao; Paul Vicol; Moonkyung Ryu; Gang Li; Sahil Singla 005; Sarah Young; Yinxiao Li; Feng Yang; Deepak Ramachandran (CVPR, 2025)

What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models. - Ahmed Imtiaz Humayun; Ibtihel Amara; Cristina Nader Vasconcelos; Deepak Ramachandran; Candice Schumann; Junfeng He; Katherine A. Heller; Golnoosh Farnadi; Negar Rostamzadeh; Mohammad Havaei (ICLR, 2025)

EraseBench: Understanding The Ripple Effects of Concept Erasure Techniques. - Ibtihel Amara; Ahmed Imtiaz Humayun; Ivana Kajic; Zarana Parekh; Natalie Harris; Sarah Young; Chirag Nagpal; Najoung Kim; Junfeng He; Cristina Nader Vasconcelos; Deepak Ramachandran; Golnoosh Farnadi; et al. (CoRR, 2025)

Best Policy Learning from Trajectory Preference Feedback. - Akhil Agnihotri; Rahul Jain 002; Deepak Ramachandran; Zheng Wen 002 (CoRR, 2025)

Distributionally Robust Direct Preference Optimization. - Zaiyan Xu; Sushil Vemuri; Kishan Panaganti; Dileep Kalathil; Rahul Jain 002; Deepak Ramachandran (CoRR, 2025)

Multi-Objective Preference Optimization: Improving Human Alignment of Generative Models. - Akhil Agnihotri; Rahul Jain 002; Deepak Ramachandran; Zheng Wen 002 (CoRR, 2025)