Matthew Riemer

67 papers A* 17A 1B 1C 1Misc 1Journal 36Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI Steerability 360: A Toolkit for Steering Large Language Models. CoRR Erik Miehling, Karthikeyan Natesan Ramamurthy, Praveen Venkateswaran, Irene Ko, Pierre L. Dognin, Moninder Singh, Tejaswini Pedapati, Avinash Balakrishnan, Matthew Riemer, Dennis Wei, Inge Vejsbjerg, Elizabeth M. Daly, Kush R. Varshney
2026	A*	`conf`	The Shepherd Test: How Will Super Intelligent Agents Balance Care and Control in Asymmetric Relationships? AAAI Djallel Bouneffouf, Matthew Riemer, Kush R. Varshney
2025	J	`jnl`	Agentic AI Needs a Systems Theory. CoRR Erik Miehling, Karthikeyan Natesan Ramamurthy, Kush R. Varshney, Matthew Riemer, Djallel Bouneffouf, John T. Richards, Amit Dhurandhar, Elizabeth M. Daly, Michael Hind, Prasanna Sattigeri, Dennis Wei, Ambrish Rawat, Jasmina Gajcin, Werner Geyer
2025	J	`jnl`	Beyond Sliding Windows: Learning to Manage Memory in Non-Markovian Environments. CoRR Geraud Nangue Tasse, Matthew Riemer, Benjamin Rosman, Tim Klinger
2025	—	`conf`	Combining Domain and Alignment Vectors Provides Better Knowledge-Safety Trade-offs in LLMs. ACL (2) Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
2025	Misc	`conf`	Contextual Value Alignment. ICASSP Pierre L. Dognin, Jesus Rios, Ronny Luss, Prasanna Sattigeri, Miao Liu, Inkit Padhi, Matthew Riemer, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2025	A*	`conf`	Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference. ICLR Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish
2025	—	`conf`	EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. ACL (1) Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer
2025	J	`jnl`	EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts. CoRR Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan, Georgios Kollias, Elliot Nelson, Khushbu Pahwa, Tejaswini Pedapati, Igor Melnyk, Matthew Riemer
2025	A*	`conf`	Handling Delay in Real-Time Reinforcement Learning. ICLR Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou
2025	J	`jnl`	Handling Delay in Real-Time Reinforcement Learning. CoRR Ivan Anokhin, Rishav Rishav, Matthew Riemer, Stephen Chung, Irina Rish, Samira Ebrahimi Kahou
2025	—	`conf`	Position: Theory of Mind Benchmarks are Broken for Large Language Models. ICML (Position Papers) Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell
2025	J	`jnl`	Revisiting Replay and Gradient Alignment for Continual Pre-Training of Large Language Models. CoRR Istabrak Abbes, Gopeshh Subbaraj, Matthew Riemer, Nizar Islah, Benjamin Thérien, Tsuguchika Tabaru, Hiroaki Kingetsu, Sarath Chandar, Irina Rish
2025	J	`jnl`	Scopes of Alignment. CoRR Kush R. Varshney, Zahra Ashktorab, Djallel Bouneffouf, Matthew Riemer, Justin D. Weisz
2025	J	`jnl`	The Effectiveness of Approximate Regularized Replay for Efficient Supervised Fine-Tuning of Large Language Models. CoRR Matthew Riemer, Erik Miehling, Miao Liu, Djallel Bouneffouf, Murray Campbell
2025	J	`jnl`	The Ultimate Test of Superintelligent AI Agents: Can an AI Balance Care and Control in Asymmetric Relationships? CoRR Djallel Bouneffouf, Matthew Riemer, Kush R. Varshney
2024	—	`conf`	A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques. ACL (1) Megh Thakkar, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
2024	A*	`conf`	Balancing Context Length and Mixing Times for Reinforcement Learning at Scale. NeurIPS Matthew Riemer, Khimya Khetarpal, Janarthanan Rajendran, Sarath Chandar
2024	J	`jnl`	Can Large Language Models Adapt to Other Agents In-Context? CoRR Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das, Miao Liu, Justin D. Weisz, Murray Campbell
2024	A*	`conf`	ComVas: Contextual Moral Values Alignment System. IJCAI Inkit Padhi, Pierre L. Dognin, Jesus Rios, Ronny Luss, Swapnaja Achintalwar, Matthew Riemer, Miao Liu, Prasanna Sattigeri, Manish Nagireddy, Kush R. Varshney, Djallel Bouneffouf
2024	J	`jnl`	Combining Domain and Alignment Vectors to Achieve Better Knowledge-Safety Trade-offs in LLMs. CoRR Megh Thakkar, Yash More, Quentin Fournier, Matthew Riemer, Pin-Yu Chen, Amal Zouaq, Payel Das, Sarath Chandar
2024	J	`jnl`	Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference. CoRR Matthew Riemer, Gopeshh Subbaraj, Glen Berseth, Irina Rish
2022	A*	`conf`	Context-Specific Representation Abstraction for Deep Option Learning. AAAI Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro, Jonathan P. How
2022	A*	`conf`	Continual Learning In Environments With Polynomial Mixing Times. NeurIPS Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish
2022	J	`jnl`	Game-Theoretical Perspectives on Active Equilibria: A Preferred Solution Concept over Nash Equilibria. CoRR Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Gerald Tesauro, Jonathan P. How
2022	A*	`conf`	Influencing Long-Term Behavior in Multiagent Reinforcement Learning. NeurIPS Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
2022	J	`jnl`	Influencing Long-Term Behavior in Multiagent Reinforcement Learning. CoRR Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster, Michael Everett, Chuangchuang Sun, Gerald Tesauro, Jonathan P. How
2022	J	`jnl`	Towards Continual Reinforcement Learning: A Review and Perspectives. J. Artif. Intell. Res. Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup
2021	A*	`conf`	A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. ICML Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
2021	C	`conf`	Capacity-Limited Decentralized Actor-Critic for Multi-Agent Games. CoG Tyler Malloy, Chris R. Sims, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro
2021	J	`jnl`	Context-Specific Representation Abstraction for Deep Option Learning. CoRR Marwa Abdulhai, Dong-Ki Kim, Matthew Riemer, Miao Liu, Gerald Tesauro, Jonathan P. How
2021	J	`jnl`	Continual Learning In Environments With Polynomial Mixing Times. CoRR Matthew Riemer, Sharath Chandra Raparthy, Ignacio Cases, Gopeshh Subbaraj, Maximilian Puelma Touzel, Irina Rish
2021	A*	`conf`	Efficient Black-Box Planning Using Macro-Actions with Focused Effects. IJCAI Cameron Allen, Michael Katz, Tim Klinger, George Konidaris, Matthew Riemer, Gerald Tesauro
2021	B	`conf`	Modeling Capacity-Limited Decision Making Using a Variational Autoencoder. CogSci Tyler Malloy, Tim Klinger, Miao Liu, Gerald Tesauro, Matthew Riemer, Chris R. Sims
2021	A*	`conf`	RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract). AAAI Tyler Malloy, Tim Klinger, Miao Liu, Gerald Tesauro, Matthew Riemer, Chris R. Sims
2020	J	`jnl`	A Policy Gradient Algorithm for Learning to Learn in Multiagent Reinforcement Learning. CoRR Dong-Ki Kim, Miao Liu, Matthew Riemer, Chuangchuang Sun, Marwa Abdulhai, Golnaz Habibi, Sebastian Lopez-Cot, Gerald Tesauro, Jonathan P. How
2020	J	`jnl`	A Study of Compositional Generalization in Neural Models. CoRR Tim Klinger, Dhaval Adjodah, Vincent Marois, Josh Joseph, Matthew Riemer, Alex 'Sandy' Pentland, Murray Campbell
2020	J	`jnl`	Consolidation via Policy Information Regularization in Deep RL for Multi-Agent Games. CoRR Tyler Malloy, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro, Chris R. Sims
2020	J	`jnl`	Deep RL With Information Constrained Policies: Generalization in Continuous Control. CoRR Tyler Malloy, Chris R. Sims, Tim Klinger, Miao Liu, Matthew Riemer, Gerald Tesauro
2020	J	`jnl`	Finding Macro-Actions with Disentangled Effects for Efficient Planning with the Goal-Count Heuristic. CoRR Cameron Allen, Tim Klinger, George Konidaris, Matthew Riemer, Gerald Tesauro
2020	A*	`conf`	Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract). AAAI Akshay Dharmavaram, Matthew Riemer, Shalabh Bhatnagar
2020	A	`conf`	Learning Hierarchical Teaching Policies for Cooperative Agents. AAMAS Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How
2020	A*	`conf`	On the Role of Weight Sharing During Deep Option Learning. AAAI Matthew Riemer, Ignacio Cases, Clemens Rosenbaum, Miao Liu, Gerald Tesauro
2020	J	`jnl`	Towards Continual Reinforcement Learning: A Review and Perspectives. CoRR Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup
2019	J	`jnl`	Continual Learning with Self-Organizing Maps. CoRR Pouya Bashivan, Martin Schrimpf, Robert Ajemian, Irina Rish, Matthew Riemer, Yuhai Tu
2019	J	`jnl`	Hierarchical Average Reward Policy Gradient Algorithms. CoRR Akshay Dharmavaram, Matthew Riemer, Shalabh Bhatnagar
2019	J	`jnl`	Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning. CoRR Dong-Ki Kim, Miao Liu, Shayegan Omidshafiei, Sebastian Lopez-Cot, Matthew Riemer, Golnaz Habibi, Gerald Tesauro, Sami Mourad, Murray Campbell, Jonathan P. How
2019	—	`conf`	Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference. ICLR (Poster) Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
2019	A*	`conf`	Learning to Teach in Cooperative Multiagent Reinforcement Learning. AAAI Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
2019	J	`jnl`	On the Role of Weight Sharing During Deep Option Learning. CoRR Matthew Riemer, Ignacio Cases, Clemens Rosenbaum, Miao Liu, Gerald Tesauro
2019	—	`conf`	Recursive Routing Networks: Learning to Compose Modules for Language Understanding. NAACL-HLT (1) Ignacio Cases, Clemens Rosenbaum, Matthew Riemer, Atticus Geiger, Tim Klinger, Alex Tamkin, Olivia Li, Sandhini Agarwal, Joshua D. Greene, Dan Jurafsky, Christopher Potts, Lauri Karttunen
2019	J	`jnl`	Routing Networks and the Challenges of Modular and Compositional Computation. CoRR Clemens Rosenbaum, Ignacio Cases, Matthew Riemer, Tim Klinger
2019	A*	`conf`	Scalable Recollections for Continual Lifelong Learning. AAAI Matthew Riemer, Tim Klinger, Djallel Bouneffouf, Michele Franceschini
2018	A*	`conf`	Learning Abstract Options. NeurIPS Matthew Riemer, Miao Liu, Gerald Tesauro
2018	J	`jnl`	Learning Abstract Options. CoRR Matthew Riemer, Miao Liu, Gerald Tesauro
2018	J	`jnl`	Learning to Learn without Forgetting By Maximizing Transfer and Minimizing Interference. CoRR Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, Gerald Tesauro
2018	J	`jnl`	Learning to Teach in Cooperative Multiagent Reinforcement Learning. CoRR Shayegan Omidshafiei, Dong-Ki Kim, Miao Liu, Gerald Tesauro, Matthew Riemer, Christopher Amato, Murray Campbell, Jonathan P. How
2018	J	`jnl`	PepCVAE: Semi-Supervised Targeted Design of Antimicrobial Peptide Sequences. CoRR Payel Das, Kahini Wadhawan, Oscar Chang, Tom Sercu, Cícero Nogueira dos Santos, Matthew Riemer, Inkit Padhi, Vijil Chenthamarakshan, Aleksandra Mojsilovic
2018	—	`conf`	Routing Networks: Adaptive Selection of Non-Linear Functions for Multi-Task Learning. ICLR (Poster) Clemens Rosenbaum, Tim Klinger, Matthew Riemer
2017	J	`jnl`	Generation and Consolidation of Recollections for Efficient Deep Lifelong Learning. CoRR Matthew Riemer, Michele Franceschini, Tim Klinger
2017	J	`jnl`	Representation Stability as a Regularizer for Improved Text Analytics Transfer Learning. CoRR Matthew Riemer, Elham Khabiri, Richard Goodwin
2017	J	`jnl`	Routing Networks: Adaptive Selection of Non-linear Functions for Multi-Task Learning. CoRR Clemens Rosenbaum, Tim Klinger, Matthew Riemer
2016	A*	`conf`	Correcting Forecasts with Multifactor Neural Attention. ICML Matthew Riemer, Aditya Vempaty, Flávio P. Calmon, Fenno F. Terry Heath III, Richard Hull, Elham Khabiri
2015	—	`conf`	A Deep Learning and Knowledge Transfer Based Architecture for Social Media User Characteristic Determination. SocialNLP@NAACL Matthew Riemer, Sophia Krasikov, Harini Srinivasan
2015	—	`conf`	Alexandria: Extensible Framework for Rapid Exploration of Social Media. BigData Congress Fenno F. Terry Heath III, Richard Hull, Elham Khabiri, Matthew Riemer, Noi Sukaviriya, Roman Vaculín
2015	J	`jnl`	Alexandria: Extensible Framework for Rapid Exploration of Social Media. CoRR Fenno F. Terry Heath III, Richard Hull, Elham Khabiri, Matthew Riemer, Noi Sukaviriya, Roman Vaculín
2015	—	`conf`	Domain Scoping for Subject Matter Experts. AAAI Fall Symposia Elham Khabiri, Matthew Riemer, Fenno F. Terry Heath III, Richard Hull