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Silviu Pitis
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Conference and Workshop Papers
- 2024
- [c12]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. ICLR 2024 - 2023
- [c11]Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba:
Large Language Models are Human-Level Prompt Engineers. ICLR 2023 - [c10]Silviu Pitis:
Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards. NeurIPS 2023 - 2022
- [c9]Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg:
MoCoDA: Model-based Counterfactual Data Augmentation. NeurIPS 2022 - 2020
- [c8]Kristopher De Asis, Alan Chan, Silviu Pitis, Richard S. Sutton, Daniel Graves:
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning. AAAI 2020: 3741-3748 - [c7]Silviu Pitis, Michael R. Zhang:
Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. AAMAS 2020: 1064-1071 - [c6]Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba:
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. ICLR 2020 - [c5]Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba:
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. ICML 2020: 7750-7761 - [c4]Silviu Pitis, Elliot Creager, Animesh Garg:
Counterfactual Data Augmentation using Locally Factored Dynamics. NeurIPS 2020 - 2019
- [c3]Silviu Pitis:
Rethinking the Discount Factor in Reinforcement Learning: A Decision Theoretic Approach. AAAI 2019: 7949-7956 - 2018
- [c2]Silviu Pitis:
Source Traces for Temporal Difference Learning. AAAI 2018: 3952-3959 - 2017
- [c1]Silviu Pitis:
Methods for retrieving alternative contract language using a prototype. ICAIL 2017: 179-187
Informal and Other Publications
- 2024
- [i14]Silviu Pitis, Ziang Xiao, Nicolas Le Roux, Alessandro Sordoni:
Improving Context-Aware Preference Modeling for Language Models. CoRR abs/2407.14916 (2024) - [i13]Blair Yang, Fuyang Cui, Keiran Paster, Jimmy Ba, Pashootan Vaezipoor, Silviu Pitis, Michael R. Zhang:
Report Cards: Qualitative Evaluation of Language Models Using Natural Language Summaries. CoRR abs/2409.00844 (2024) - 2023
- [i12]Silviu Pitis, Michael R. Zhang, Andrew Wang, Jimmy Ba:
Boosted Prompt Ensembles for Large Language Models. CoRR abs/2304.05970 (2023) - [i11]Yangjun Ruan, Honghua Dong, Andrew Wang, Silviu Pitis, Yongchao Zhou, Jimmy Ba, Yann Dubois, Chris J. Maddison, Tatsunori Hashimoto:
Identifying the Risks of LM Agents with an LM-Emulated Sandbox. CoRR abs/2309.15817 (2023) - [i10]Silviu Pitis:
Consistent Aggregation of Objectives with Diverse Time Preferences Requires Non-Markovian Rewards. CoRR abs/2310.00435 (2023) - 2022
- [i9]Silviu Pitis, Elliot Creager, Ajay Mandlekar, Animesh Garg:
MoCoDA: Model-based Counterfactual Data Augmentation. CoRR abs/2210.11287 (2022) - [i8]Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, Jimmy Ba:
Large Language Models Are Human-Level Prompt Engineers. CoRR abs/2211.01910 (2022) - 2020
- [i7]Silviu Pitis, Michael R. Zhang:
Objective Social Choice: Using Auxiliary Information to Improve Voting Outcomes. CoRR abs/2001.10092 (2020) - [i6]Silviu Pitis, Harris Chan, Kiarash Jamali, Jimmy Ba:
An Inductive Bias for Distances: Neural Nets that Respect the Triangle Inequality. CoRR abs/2002.05825 (2020) - [i5]Silviu Pitis, Harris Chan, Stephen Zhao, Bradly C. Stadie, Jimmy Ba:
Maximum Entropy Gain Exploration for Long Horizon Multi-goal Reinforcement Learning. CoRR abs/2007.02832 (2020) - [i4]Silviu Pitis, Elliot Creager, Animesh Garg:
Counterfactual Data Augmentation using Locally Factored Dynamics. CoRR abs/2007.02863 (2020) - 2019
- [i3]Silviu Pitis:
Rethinking the Discount Factor in Reinforcement Learning: A Decision Theoretic Approach. CoRR abs/1902.02893 (2019) - [i2]Silviu Pitis:
Source Traces for Temporal Difference Learning. CoRR abs/1902.02907 (2019) - [i1]Kristopher De Asis, Alan Chan, Silviu Pitis, Richard S. Sutton, Daniel Graves:
Fixed-Horizon Temporal Difference Methods for Stable Reinforcement Learning. CoRR abs/1909.03906 (2019)
Coauthor Index
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