Guy Tennenholtz

55 papers A* 17A 3Journal 34Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders. EACL (Volume 1: Long Papers) Ofer Meshi, Krisztian Balog, Sally Goldman, Avi Caciularu, Guy Tennenholtz, Jihwan Jeong, Amir Globerson, Craig Boutilier
2026	J	`jnl`	ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders. CoRR Ofer Meshi, Krisztian Balog, Sally Goldman, Avi Caciularu, Guy Tennenholtz, Jihwan Jeong, Amir Globerson, Craig Boutilier
2026	J	`jnl`	Diffusion Controller: Framework, Algorithms and Parameterization. CoRR Tong Yang, Moonkyung Ryu, Chih-Wei Hsu, Guy Tennenholtz, Yuejie Chi, Craig Boutilier, Bo Dai
2025	J	`jnl`	Asking Clarifying Questions for Preference Elicitation With Large Language Models. CoRR Ali Montazeralghaem, Guy Tennenholtz, Craig Boutilier, Ofer Meshi
2025	J	`jnl`	Descriptive History Representations: Learning Representations by Answering Questions. CoRR Guy Tennenholtz, Jihwan Jeong, Chih-Wei Hsu, Yinlam Chow, Craig Boutilier
2025	A*	`conf`	Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. ICLR Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Aviral Kumar, Rishabh Agarwal, Sridhar Thiagarajan, Craig Boutilier, Aleksandra Faust
2025	A*	`conf`	Preference Adaptive and Sequential Text-to-Image Generation. ICML Ofir Nabati, Guy Tennenholtz, Chih-Wei Hsu, Moonkyung Ryu, Deepak Ramachandran, Yinlam Chow, Xiang Li, Craig Boutilier
2025	J	`jnl`	Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces. CoRR Haitong Ma, Ofir Nabati, Aviv Rosenberg, Bo Dai, Oran Lang, Idan Szpektor, Craig Boutilier, Na Li, Shie Mannor, Lior Shani, Guy Tennenholtz
2025	J	`jnl`	Spectral Bellman Method: Unifying Representation and Exploration in RL. CoRR Ofir Nabati, Bo Dai, Shie Mannor, Guy Tennenholtz
2024	A*	`conf`	Bayesian Regret Minimization in Offline Bandits. ICML Marek Petrik, Guy Tennenholtz, Mohammad Ghavamzadeh
2024	J	`jnl`	Benchmarks for Reinforcement Learning with Biased Offline Data and Imperfect Simulators. CoRR Ori Linial, Guy Tennenholtz, Uri Shalit
2024	A*	`conf`	Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. ICLR Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz
2024	A*	`conf`	Demystifying Embedding Spaces using Large Language Models. ICLR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
2024	A*	`conf`	DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. NeurIPS Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier
2024	J	`jnl`	DynaMITE-RL: A Dynamic Model for Improved Temporal Meta-Reinforcement Learning. CoRR Anthony Liang, Guy Tennenholtz, Chih-Wei Hsu, Yinlam Chow, Erdem Biyik, Craig Boutilier
2024	A*	`conf`	Embedding-Aligned Language Models. NeurIPS Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Yi Liang, Craig Boutilier
2024	J	`jnl`	Embedding-Aligned Language Models. CoRR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Lior Shani, Ethan Liang, Craig Boutilier
2024	J	`jnl`	Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models. CoRR Yinlam Chow, Guy Tennenholtz, Izzeddin Gur, Vincent Zhuang, Bo Dai, Sridhar Thiagarajan, Craig Boutilier, Rishabh Agarwal, Aviral Kumar, Aleksandra Faust
2024	J	`jnl`	Personalized and Sequential Text-to-Image Generation. CoRR Ofir Nabati, Guy Tennenholtz, Chih-Wei Hsu, Moonkyung Ryu, Deepak Ramachandran, Yinlam Chow, Xiang Li, Craig Boutilier
2024	A*	`conf`	Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization. AAAI Craig Boutilier, Martin Mladenov, Guy Tennenholtz
2023	J	`jnl`	A Convex Relaxation Approach to Bayesian Regret Minimization in Offline Bandits. CoRR Mohammad Ghavamzadeh, Marek Petrik, Guy Tennenholtz
2023	J	`jnl`	Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding. CoRR Alizée Pace, Hugo Yèche, Bernhard Schölkopf, Gunnar Rätsch, Guy Tennenholtz
2023	J	`jnl`	Demystifying Embedding Spaces using Large Language Models. CoRR Guy Tennenholtz, Yinlam Chow, Chih-Wei Hsu, Jihwan Jeong, Lior Shani, Azamat Tulepbergenov, Deepak Ramachandran, Martin Mladenov, Craig Boutilier
2023	J	`jnl`	Ever Evolving Evaluator (EV3): Towards Flexible and Reliable Meta-Optimization for Knowledge Distillation. CoRR Li Ding, Masrour Zoghi, Guy Tennenholtz, Maryam Karimzadehgan
2023	J	`jnl`	Factual and Personalized Recommendations using Language Models and Reinforcement Learning. CoRR Jihwan Jeong, Yinlam Chow, Guy Tennenholtz, Chih-Wei Hsu, Azamat Tulepbergenov, Mohammad Ghavamzadeh, Craig Boutilier
2023	J	`jnl`	Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models. CoRR Craig Boutilier, Martin Mladenov, Guy Tennenholtz
2023	A	`conf`	Never Worse, Mostly Better: Stable Policy Improvement in Deep Reinforcement Learning. AAMAS Pranav Khanna, Guy Tennenholtz, Nadav Merlis, Shie Mannor, Chen Tessler
2023	J	`jnl`	Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics. CoRR Guy Tennenholtz, Martin Mladenov, Nadav Merlis, Craig Boutilier
2023	A*	`conf`	Reinforcement Learning with History Dependent Dynamic Contexts. ICML Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier
2023	J	`jnl`	Reinforcement Learning with History-Dependent Dynamic Contexts. CoRR Guy Tennenholtz, Nadav Merlis, Lior Shani, Martin Mladenov, Craig Boutilier
2023	A*	`conf`	Representation-Driven Reinforcement Learning. ICML Ofir Nabati, Guy Tennenholtz, Shie Mannor
2023	J	`jnl`	Representation-Driven Reinforcement Learning. CoRR Ofir Nabati, Guy Tennenholtz, Shie Mannor
2022	A*	`conf`	Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning. AAAI Roy Zohar, Shie Mannor, Guy Tennenholtz
2022	A*	`conf`	On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. ICLR Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit
2022	A*	`conf`	Reinforcement Learning with a Terminator. NeurIPS Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal
2022	J	`jnl`	Reinforcement Learning with a Terminator. CoRR Guy Tennenholtz, Nadav Merlis, Lior Shani, Shie Mannor, Uri Shalit, Gal Chechik, Assaf Hallak, Gal Dalal
2022	A*	`conf`	Uncertainty Estimation Using Riemannian Model Dynamics for Offline Reinforcement Learning. NeurIPS Guy Tennenholtz, Shie Mannor
2021	J	`jnl`	Action Redundancy in Reinforcement Learning. CoRR Nir Baram, Guy Tennenholtz, Shie Mannor
2021	A	`conf`	Action redundancy in reinforcement learning. UAI Nir Baram, Guy Tennenholtz, Shie Mannor
2021	A	`conf`	Bandits with partially observable confounded data. UAI Guy Tennenholtz, Uri Shalit, Shie Mannor, Yonathan Efroni
2021	J	`jnl`	GELATO: Geometrically Enriched Latent Model for Offline Reinforcement Learning. CoRR Guy Tennenholtz, Nir Baram, Shie Mannor
2021	J	`jnl`	Locality Matters: A Scalable Value Decomposition Approach for Cooperative Multi-Agent Reinforcement Learning. CoRR Roy Zohar, Shie Mannor, Guy Tennenholtz
2021	J	`jnl`	Maximum Entropy Reinforcement Learning with Mixture Policies. CoRR Nir Baram, Guy Tennenholtz, Shie Mannor
2021	J	`jnl`	On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning. CoRR Guy Tennenholtz, Assaf Hallak, Gal Dalal, Shie Mannor, Gal Chechik, Uri Shalit
2020	J	`jnl`	Bandits with Partially Observable Offline Data. CoRR Guy Tennenholtz, Uri Shalit, Shie Mannor, Yonathan Efroni
2020	A*	`conf`	Off-Policy Evaluation in Partially Observable Environments. AAAI Guy Tennenholtz, Uri Shalit, Shie Mannor
2020	J	`jnl`	The Pendulum Arrangement: Maximizing the Escape Time of Heterogeneous Random Walks. CoRR Asaf B. Cassel, Shie Mannor, Guy Tennenholtz
2019	A*	`conf`	Distributional Policy Optimization: An Alternative Approach for Continuous Control. NeurIPS Chen Tessler, Guy Tennenholtz, Shie Mannor
2019	J	`jnl`	Distributional Policy Optimization: An Alternative Approach for Continuous Control. CoRR Chen Tessler, Guy Tennenholtz, Shie Mannor
2019	J	`jnl`	Natural Language State Representation for Reinforcement Learning. CoRR Erez Schwartz, Guy Tennenholtz, Chen Tessler, Shie Mannor
2019	J	`jnl`	Off-Policy Evaluation in Partially Observable Environments. CoRR Guy Tennenholtz, Shie Mannor, Uri Shalit
2019	A*	`conf`	The Natural Language of Actions. ICML Guy Tennenholtz, Shie Mannor
2019	J	`jnl`	The Natural Language of Actions. CoRR Guy Tennenholtz, Shie Mannor
2018	J	`jnl`	Train on Validation: Squeezing the Data Lemon. CoRR Guy Tennenholtz, Tom Zahavy, Shie Mannor
2017	J	`jnl`	The Stochastic Firefighter Problem. CoRR Guy Tennenholtz, Constantine Caramanis, Shie Mannor