Hootan Nakhost

34 papers A* 10A 1B 2Journal 15Unranked 6
YearRankTypeTitle / Venue / Authors
2025 J jnl
From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation.
CoRR
Xingchen Wan, Han Zhou, Ruoxi Sun, Hootan Nakhost, Ke Jiang, Sercan Ö. Arik
2025 J jnl
Maestro: Self-Improving Text-to-Image Generation via Agent Orchestration.
CoRR
Xingchen Wan, Han Zhou, Ruoxi Sun, Hootan Nakhost, Ke Jiang, Rajarishi Sinha, Sercan Ö. Arik
2025 A* conf
PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving.
EMNLP
Mihir Parmar, Xin Liu, Palash Goyal, Yanfei Chen, Long T. Le, Swaroop Mishra, Hossein Mobahi, Jindong Gu, Zifeng Wang, Hootan Nakhost, Chitta Baral, Chen-Yu Lee, Tomas Pfister, Hamid Palangi
2025 J jnl
PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving.
CoRR
Mihir Parmar, Xin Liu, Palash Goyal, Yanfei Chen, Long T. Le, Swaroop Mishra, Hossein Mobahi, Jindong Gu, Zifeng Wang, Hootan Nakhost, Chitta Baral, Chen-Yu Lee, Tomas Pfister, Hamid Palangi
2025 J jnl
VISTA: A Test-Time Self-Improving Video Generation Agent.
CoRR
Do Xuan Long, Xingchen Wan, Hootan Nakhost, Chen-Yu Lee, Tomas Pfister, Sercan Ö. Arik
2024 J jnl
SQL-PaLM: Improved large language model adaptation for Text-to-SQL.
Trans. Mach. Learn. Res.
Ruoxi Sun, Sercan Ö. Arik, Alexandre Muzio, Lesly Miculicich, Satya Kesav Gundabathula, Pengcheng Yin, Hanjun Dai, Hootan Nakhost, Rajarishi Sinha, Zifeng Wang, Tomas Pfister
2024 A* conf
Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization.
NeurIPS
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Sercan Ö. Arik
2024 J jnl
Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization.
CoRR
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Sercan Ö. Arik
2024 — conf
TextGenSHAP: Scalable Post-Hoc Explanations in Text Generation with Long Documents.
ACL (Findings)
James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister
2023 — conf
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.
ACL (Findings)
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alex Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
2023 J jnl
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes.
CoRR
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
2023 J jnl
SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL.
CoRR
Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, Tomas Pfister
2023 — conf
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data.
EMNLP (Findings)
Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister
2023 J jnl
SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Data.
CoRR
Ruoxi Sun, Sercan Ö. Arik, Rajarishi Sinha, Hootan Nakhost, Hanjun Dai, Pengcheng Yin, Tomas Pfister
2023 J jnl
TextGenSHAP: Scalable Post-hoc Explanations in Text Generation with Long Documents.
CoRR
James Enouen, Hootan Nakhost, Sayna Ebrahimi, Sercan Ö. Arik, Yan Liu, Tomas Pfister
2023 A* conf
Universal Self-Adaptive Prompting.
EMNLP
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Eisenschlos, Sercan Ö. Arik, Tomas Pfister
2023 J jnl
Universal Self-adaptive Prompting.
CoRR
Xingchen Wan, Ruoxi Sun, Hootan Nakhost, Hanjun Dai, Julian Martin Eisenschlos, Sercan Ö. Arik, Tomas Pfister
2022 J jnl
Controlling Commercial Cooling Systems Using Reinforcement Learning.
CoRR
Jerry Luo, Cosmin Paduraru, Octavian Voicu, Yuri Chervonyi, Scott Munns, Jerry Li, Crystal Qian, Praneet Dutta, Jared Quincy Davis, Ningjia Wu, Xingwei Yang, Chu-Ming Chang, Ted Li, Rob Rose, Mingyan Fan, Hootan Nakhost, Tinglin Liu, Brian Kirkman, Frank Altamura, Lee Cline, Patrick Tonker, Joel Gouker, Dave Uden, Warren Buddy Bryan, Jason Law, Deeni Fatiha, Neil Satra, Juliet Rothenberg, Molly Carlin, Satish Tallapaka, Sims Witherspoon, David Parish, Peter Dolan, Chenyu Zhao, Daniel J. Mankowitz
2021 — conf
Learning and Evaluating a Differentially Private Pre-trained Language Model.
EMNLP (Findings)
Shlomo Hoory, Amir Feder, Avichai Tendler, Sofia Erell, Alon Peled-Cohen, Itay Laish, Hootan Nakhost, Uri Stemmer, Ayelet Benjamini, Avinatan Hassidim, Yossi Matias
2020 J jnl
Interpretable Sequence Learning for COVID-19 Forecasting.
CoRR
Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister
2020 A* conf
Interpretable Sequence Learning for Covid-19 Forecasting.
NeurIPS
Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister
2014 J jnl
Towards a theory of random walk planning: Regress factors, fair homogeneous graphs and extensions.
AI Commun.
Hootan Nakhost, Martin Müller
2013 A* conf
Towards a Second Generation Random Walk Planner: An Experimental Exploration.
IJCAI
Hootan Nakhost, Martin Müller
2012 B conf
A Theoretical Framework for Studying Random Walk Planning.
SOCS
Hootan Nakhost, Martin Müller
2012 A conf
ArvandHerd: Parallel Planning with a Portfolio.
ECAI
Richard Anthony Valenzano, Hootan Nakhost, Martin Müller, Jonathan Schaeffer, Nathan R. Sturtevant
2012 A* conf
Planning Via Random Walk-Driven Local Search.
ICAPS
Fan Xie, Hootan Nakhost, Martin Müller
2012 A* conf
Resource-Constrained Planning: A Monte Carlo Random Walk Approach.
ICAPS
Hootan Nakhost, Jörg Hoffmann, Martin Müller
2011 A* conf
A Local Monte Carlo Tree Search Approach in Deterministic Planning.
AAAI
Fan Xie, Hootan Nakhost, Martin Müller
2010 A* conf
Action Elimination and Plan Neighborhood Graph Search: Two Algorithms for Plan Improvement.
ICAPS
Hootan Nakhost, Martin Müller
2010 B conf
Improving Local Search for Resource-Constrained Planning.
SOCS
Hootan Nakhost, Jörg Hoffmann, Martin Müller
2009 A* conf
Monte-Carlo Exploration for Deterministic Planning.
IJCAI
Hootan Nakhost, Martin Müller
2007 J jnl
Integrating Module Checking and Deduction in a Formal Proof for the Perlman Spanning Tree Protocol (STP).
J. Univers. Comput. Sci.
Hossein Hojjat, Hootan Nakhost, Marjan Sirjani
2007 — conf
Integration of Symmetry and Macro-operators in Planning.
MICAI
Amirali Houshmandan, Gholamreza Ghassem-Sani, Hootan Nakhost
2005 — conf
Formal Verification of the IEEE 802.1D Spanning Tree Protocol Using Extended
FSEN
Hossein Hojjat, Hootan Nakhost, Marjan Sirjani