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2020 – today
- 2024
[j5]Christina Göpfert
, Alex Haig, Chih-Wei Hsu, Yinlam Chow, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Hubert Pham, Mohammad Ghavamzadeh, Craig Boutilier:
Discovering Personalized Semantics for Soft Attributes in Recommender Systems Using Concept Activation Vectors. Trans. Recomm. Syst. 2(4): 30:1-30:37 (2024)- [c35]Quan Yuan, Mehran Kazemi, Xin Xu, Isaac Noble, Vaiva Imbrasaite, Deepak Ramachandran:
TaskLAMA: Probing the Complex Task Understanding of Language Models. AAAI 2024: 19468-19476 - [c34]Siddhartha Datta, Alexander Ku, Deepak Ramachandran, Peter Anderson:
Prompt Expansion for Adaptive Text-to-Image Generation. ACL (1) 2024: 3449-3476 - [c33]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, Katherine M. Collins, Yiwen Luo, Yang Li, Kai J. Kohlhoff, Deepak Ramachandran, Vidhya Navalpakkam:
Rich Human Feedback for Text-to-Image Generation. CVPR 2024: 19401-19411 - [c32]Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier:
Demystifying Embedding Spaces using Large Language Models. ICLR 2024 - [i22]Senjuti Dutta, Sherol Chen, Sunny Mak, Amnah Ahmad, Katherine Maeve Collins, Alena Butryna, Deepak Ramachandran, Krishnamurthy Dvijotham, Ellie Pavlick, Ravi Rajakumar:
Understanding Subjectivity through the Lens of Motivational Context in Model-Generated Image Satisfaction. CoRR abs/2403.05576 (2024) - [i21]Connor Pryor, Quan Yuan, Jeremiah Z. Liu, Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor:
Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. CoRR abs/2403.17853 (2024) - [i20]Akhil Agnihotri, Rahul Jain, Deepak Ramachandran, Sahil Singla:
e-COP : Episodic Constrained Optimization of Policies. CoRR abs/2406.09563 (2024) - [i19]Akhil Agnihotri, Rahul Jain, Deepak Ramachandran, Zheng Wen:
Online Bandit Learning with Offline Preference Data. CoRR abs/2406.09574 (2024) - [i18]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, Sahil Singla, Gang Li, Adrian Weller, Junfeng He, Deepak Ramachandran, Krishnamurthy Dj Dvijotham:
Beyond Thumbs Up/Down: Untangling Challenges of Fine-Grained Feedback for Text-to-Image Generation. CoRR abs/2406.16807 (2024) - [i17]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, Yilin Gao, Evgeny Gladchenko, Sergio Gómez Colmenarejo, Mandy Guo, Alex Haig, Will Hawkins, Hexiang Hu, Huilian Huang, Tobenna Peter Igwe, Christos Kaplanis, Siavash Khodadadeh, Yelin Kim, Ksenia Konyushkova, Karol Langner, Eric Lau, Shixin Luo, Sona Mokrá, Henna Nandwani, Yasumasa Onoe, Aäron van den Oord, Zarana Parekh, Jordi Pont-Tuset, Hang Qi, Rui Qian, Deepak Ramachandran, Poorva Rane, Abdullah Rashwan, Ali Razavi, Robert Riachi, Hansa Srinivasan, Srivatsan Srinivasan, Robin Strudel, Benigno Uria, Oliver Wang, Su Wang, Austin Waters, Chris Wolff, Auriel Wright, Zhisheng Xiao, Hao Xiong, Keyang Xu, Marc van Zee, Junlin Zhang, Katie Zhang, Wenlei Zhou, Konrad Zolna, Ola Aboubakar, Canfer Akbulut, Oscar Akerlund, Isabela Albuquerque, Nina Anderson, Marco Andreetto, Lora Aroyo, Ben Bariach, David Barker, Sherry Ben, Dana Berman, Courtney Biles, Irina Blok, Pankil Botadra, Jenny Brennan, Karla Brown, John Buckley, Rudy Bunel, Elie Bursztein, Christina Butterfield, Ben Caine, Viral Carpenter, Norman Casagrande, Ming-Wei Chang, Solomon Chang, Shamik Chaudhuri, Tony Chen, John Choi, Dmitry Churbanau, Nathan Clement, Matan Cohen, Forrester Cole, Mikhail Dektiarev, Vincent Du, Praneet Dutta, Tom Eccles, Ndidi Elue, Ashley Feden, Shlomi Fruchter, Frankie Garcia, Roopal Garg:
Imagen 3. CoRR abs/2408.07009 (2024) - 2023
- [j4]Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab Mirrokni:
Tackling Provably Hard Representative Selection via Graph Neural Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c31]Mehran Kazemi, Najoung Kim, Deepti Bhatia, Xin Xu, Deepak Ramachandran:
LAMBADA: Backward Chaining for Automated Reasoning in Natural Language. ACL (1) 2023: 6547-6568 - [c30]Connor Pryor, Quan Yuan, Jeremiah Z. Liu, Mehran Kazemi, Deepak Ramachandran, Tania Bedrax-Weiss, Lise Getoor:
Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic. ACL (1) 2023: 7631-7652 - [c29]Jeremiah Zhe Liu, Krishnamurthy (Dj) Dvijotham, Jihyeon Lee, Quan Yuan, Balaji Lakshminarayanan, Deepak Ramachandran:
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. ICLR 2023 - [c28]Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi:
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. ICLR 2023 - [c27]Isaac Noble, Ivan Vendrov, Xin Xu, Deepak Ramachandran:
Realistic but Non-Identifiable Synthetic User Data Generation. EvalRS@KDD 2023 - [c26]Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran:
BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information. NeurIPS 2023 - [c25]Sandeep Silwal, Sara Ahmadian, Andrew Nystrom, Andrew McCallum, Deepak Ramachandran, Seyed Mehran Kazemi:
KwikBucks: Correlation Clustering with Cheap-Weak and Expensive-Strong Signals. SustaiNLP 2023: 1-31 - [i16]Mehran Kazemi, Sid Mittal, Deepak Ramachandran:
Understanding Finetuning for Factual Knowledge Extraction from Language Models. CoRR abs/2301.11293 (2023) - [i15]Jeremiah Zhe Liu, Krishnamurthy (Dj) Dvijotham, Jihyeon Lee, Quan Yuan, Martin Strobel, Balaji Lakshminarayanan, Deepak Ramachandran:
Pushing the Accuracy-Group Robustness Frontier with Introspective Self-play. CoRR abs/2302.05807 (2023) - [i14]Mehran Kazemi, Quan Yuan, Deepti Bhatia, Najoung Kim, Xin Xu, Vaiva Imbrasaite, Deepak Ramachandran:
BoardgameQA: A Dataset for Natural Language Reasoning with Contradictory Information. CoRR abs/2306.07934 (2023) - [i13]Quan Yuan, Mehran Kazemi, Xin Xu, Isaac Noble, Vaiva Imbrasaite, Deepak Ramachandran:
TaskLAMA: Probing the Complex Task Understanding of Language Models. CoRR abs/2308.15299 (2023) - [i12]Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier:
Demystifying Embedding Spaces using Large Language Models. CoRR abs/2310.04475 (2023) - [i11]Senjuti Dutta, Sid Mittal, Sherol Chen, Deepak Ramachandran, Ravi Rajakumar, Ian Kivlichan, Sunny Mak, Alena Butryna, Praveen K. Paritosh:
Modeling subjectivity (by Mimicking Annotator Annotation) in toxic comment identification across diverse communities. CoRR abs/2311.00203 (2023) - [i10]Jacob Eisenstein, Chirag Nagpal, Alekh Agarwal, Ahmad Beirami, Alex D'Amour, Dj Dvijotham, Adam Fisch, Katherine A. Heller, Stephen Pfohl, Deepak Ramachandran, Peter Shaw, Jonathan Berant:
Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking. CoRR abs/2312.09244 (2023) - [i9]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, Katie Collins, Yiwen Luo, Yang Li, Kai J. Kohlhoff, Deepak Ramachandran, Vidhya Navalpakkam:
Rich Human Feedback for Text-to-Image Generation. CoRR abs/2312.10240 (2023) - [i8]Siddhartha Datta, Alexander Ku, Deepak Ramachandran, Peter Anderson:
Prompt Expansion for Adaptive Text-to-Image Generation. CoRR abs/2312.16720 (2023) - 2022
- [c24]Filip Radlinski, Craig Boutilier, Deepak Ramachandran, Ivan Vendrov:
Subjective Attributes in Conversational Recommendation Systems: Challenges and Opportunities. AAAI 2022: 12287-12293 - [c23]Alon Albalak, Yi-Lin Tuan, Pegah Jandaghi, Connor Pryor, Luke Yoffe, Deepak Ramachandran, Lise Getoor, Jay Pujara, William Yang Wang:
FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue. EMNLP 2022: 10936-10953 - [c22]Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier:
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. WWW 2022: 2411-2421 - [e1]Alon Albalak, Chunting Zhou, Colin Raffel, Deepak Ramachandran, Sebastian Ruder, Xuezhe Ma:
Transfer Learning for Natural Language Processing Workshop, 03 December 2022, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 203, PMLR 2022 [contents] - [i7]Christina Göpfert, Yinlam Chow, Chih-Wei Hsu, Ivan Vendrov, Tyler Lu, Deepak Ramachandran, Craig Boutilier:
Discovering Personalized Semantics for Soft Attributes in Recommender Systems using Concept Activation Vectors. CoRR abs/2202.02830 (2022) - [i6]Alon Albalak, Yi-Lin Tuan, Pegah Jandaghi, Connor Pryor, Luke Yoffe, Deepak Ramachandran, Lise Getoor, Jay Pujara, William Yang Wang:
FETA: A Benchmark for Few-Sample Task Transfer in Open-Domain Dialogue. CoRR abs/2205.06262 (2022) - [i5]Seyed Mehran Kazemi, Anton Tsitsulin, Hossein Esfandiari, MohammadHossein Bateni, Deepak Ramachandran, Bryan Perozzi, Vahab S. Mirrokni:
Tackling Provably Hard Representative Selection via Graph Neural Networks. CoRR abs/2205.10403 (2022) - [i4]Seyed Mehran Kazemi, Najoung Kim, Deepti Bhatia, Xin Xu, Deepak Ramachandran:
LAMBADA: Backward Chaining for Automated Reasoning in Natural Language. CoRR abs/2212.13894 (2022) - 2021
- [c21]Najoung Kim, Ellie Pavlick, Burcu Karagol Ayan, Deepak Ramachandran:
Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering. ACL/IJCNLP (1) 2021: 3932-3945 - [i3]Najoung Kim, Ellie Pavlick, Burcu Karagol Ayan, Deepak Ramachandran:
Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering. CoRR abs/2101.00391 (2021) - 2020
- [j3]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, Ferdinando Fioretto, Raquel Fuentetaja, Christopher William Geib, Odd Erik Gundersen, José Hernández-Orallo, Xiaowei Huang, Kokil Jaidka, Sarah Keren, Seokhwan Kim, Michel Galley, Xiaomo Liu, Tyler Lu, Zhiqiang Ma, Richard Mallah, John A. McDermid, Martin Michalowski, Reuth Mirsky, Seán Ó hÉigeartaigh, Deepak Ramachandran, Javier Segovia-Aguas, Onn Shehory, Arash Shaban-Nejad, Vered Shwartz, Siddharth Srivastava, Kartik Talamadupula, Jian Tang, Pascal Van Hentenryck, Dell Zhang, Jian Zhang:
The Association for the Advancement of Artificial Intelligence 2020 Workshop Program. AI Mag. 41(4): 100-114 (2020) - [c20]Xikun Zhang, Deepak Ramachandran, Ian Tenney, Yanai Elazar, Dan Roth:
Do Language Embeddings capture Scales? BlackboxNLP@EMNLP 2020: 292-299 - [c19]Xikun Zhang, Deepak Ramachandran, Ian Tenney, Yanai Elazar, Dan Roth:
Do Language Embeddings capture Scales? EMNLP (Findings) 2020: 4889-4896 - [i2]Xikun Zhang, Deepak Ramachandran, Ian Tenney, Yanai Elazar, Dan Roth:
Do Language Embeddings Capture Scales? CoRR abs/2010.05345 (2020)
2010 – 2019
- 2019
- [c18]Yanai Elazar, Abhijit Mahabal, Deepak Ramachandran, Tania Bedrax-Weiss, Dan Roth:
How Large Are Lions? Inducing Distributions over Quantitative Attributes. ACL (1) 2019: 3973-3983 - [i1]Yanai Elazar, Abhijit Mahabal, Deepak Ramachandran, Tania Bedrax-Weiss, Dan Roth:
How Large Are Lions? Inducing Distributions over Quantitative Attributes. CoRR abs/1906.01327 (2019) - 2015
- [j2]Peter Z. Yeh, Deepak Ramachandran, Benjamin Douglas, Adwait Ratnaparkhi, William Jarrold, Ronald Provine, Peter F. Patel-Schneider, Stephen Laverty, Nirvana Tikku, Sean Brown, Jeremy Mendel, Adam Emfield:
An End-to-End Conversational Second Screen Application for TV Program Discovery. AI Mag. 36(3): 73-89 (2015) - [c17]Deepak Ramachandran, Adwait Ratnaparkhi:
Belief Tracking with Stacked Relational Trees. SIGDIAL Conference 2015: 68-76 - [c16]Deepak Ramachandran, Mark A. Fanty, Ronald Provine, Peter Z. Yeh, William Jarrold, Adwait Ratnaparkhi, Benjamin Douglas:
A TV Program Discovery Dialog System using recommendations. SIGDIAL Conference 2015: 435-437 - 2014
- [j1]Jason D. Williams, Matthew Henderson, Antoine Raux, Blaise Thomson, Alan W. Black, Deepak Ramachandran:
The Dialog State Tracking Challenge Series. AI Mag. 35(4): 121-124 (2014) - [c15]Peter Z. Yeh, Benjamin Douglas, William Jarrold, Adwait Ratnaparkhi, Deepak Ramachandran, Peter F. Patel-Schneider, Stephen Laverty, Nirvana Tikku, Sean Brown, Jeremy Mendel:
A Speech-Driven Second Screen Application for TV Program Discovery. AAAI 2014: 3010-3016 - [c14]Deepak Ramachandran, Peter Z. Yeh, William Jarrold, Benjamin Douglas, Adwait Ratnaparkhi, Ronald Provine, Jeremy Mendel, Adam Emfield:
An end-to-end dialog system for TV program discovery. SLT 2014: 602-607 - 2013
- [c13]Deepak Ramachandran, Igor V. Karpov, Rakesh Gupta, Antoine Raux:
Driver familiarity modeling for generating navigation directions. ITSC 2013: 2193-2200 - [c12]Jason D. Williams, Antoine Raux, Deepak Ramachandran, Alan W. Black:
The Dialog State Tracking Challenge. SIGDIAL Conference 2013: 404-413 - 2012
- [c11]Adam Vogel, Deepak Ramachandran, Rakesh Gupta, Antoine Raux:
Improving Hybrid Vehicle Fuel Efficiency Using Inverse Reinforcement Learning. AAAI 2012: 384-390 - [c10]Yi Ma, Antoine Raux, Deepak Ramachandran, Rakesh Gupta:
Landmark-Based Location Belief Tracking in a Spoken Dialog System. SIGDIAL Conference 2012: 169-178 - 2011
- [b1]Deepak Ramachandran:
Knowledge and Ignorance in Reinforcement Learning. University of Illinois Urbana-Champaign, USA, 2011 - 2010
- [c9]Antoine Raux, Neville Mehta, Deepak Ramachandran, Rakesh Gupta:
Dynamic language modeling using Bayesian networks for spoken dialog systems. INTERSPEECH 2010: 3030-3033 - [c8]Neville Mehta, Rakesh Gupta, Antoine Raux, Deepak Ramachandran, Stefan Krawczyk:
Probabilistic Ontology Trees for Belief Tracking in Dialog Systems. SIGDIAL Conference 2010: 37-46
2000 – 2009
- 2009
- [c7]Deepak Ramachandran, Rakesh Gupta:
Smoothed Sarsa: Reinforcement learning for robot delivery tasks. ICRA 2009: 2125-2132 - [p1]Ming Kwan, Deepak Ramachandran:
Trust and Online Reputation Systems. Computing with Social Trust 2009: 287-311 - 2008
- [c6]Nicolas Loeff, David A. Forsyth, Deepak Ramachandran:
ManifoldBoost: stagewise function approximation for fully-, semi- and un-supervised learning. ICML 2008: 600-607 - 2007
- [c5]Deepak Ramachandran:
Using Common Sense for Decision Making in an Adventure Game. AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning 2007: 138-143 - [c4]Deepak Ramachandran, Eyal Amir:
Bayesian Inverse Reinforcement Learning. IJCAI 2007: 2586-2591 - 2006
- [c3]Deepak Ramachandran, Neil H. Boyette, Isaac K. Cheng, Vikas Krishna, Savitha Srinivasan:
Towards Scaleable and Adaptive Document Routing Services. IEEE SCC 2006: 311-314 - 2005
- [c2]Deepak Ramachandran, Eyal Amir:
Compact Propositional Encodings of First-Order Theories. AAAI 2005: 340-345 - [c1]Deepak Ramachandran, Eyal Amir:
Compact Propositional Encodings of First-Order Theories. IJCAI 2005: 1579-1580
Coauthor Index
Krishnamurthy Dvijotham
aka: Krishnamurthy Dj Dvijotham
aka: Krishnamurthy (Dj) Dvijotham
aka: Dj Dvijotham
aka: Krishnamurthy Dj Dvijotham
aka: Krishnamurthy (Dj) Dvijotham
aka: Dj Dvijotham
Mehran Kazemi
aka: Seyed Mehran Kazemi
aka: Seyed Mehran Kazemi
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last updated on 2024-11-06 20:32 CET by the dblp team
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