Matthew Riemer
24 papers · 2016–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge π£ Hot Topic Early Bird π§ Keyword Pioneer π Academic Marathon (9)
π§
Keyword Pioneer
πΊοΈ
Taxonomy Completionist
(47)
π
Interdisciplinary Bridge
π§¬
Topic Evolution
π
Grand Slam
π
Keyword Champion
(2)
ποΈ
Keyword Collector
(95)
π
Conference Pioneer
π
Trend Setter
π
Century Club
(22)
π₯
Unstoppable
(5)
β
The Questioner
β‘
Prolific Year
(5)
Conferences
AAAI (7)
ACL (4)
ICLR (4)
NIPS (4)
ICML (2)
IJCAI (2)
NAACL (1)
Top co-authors
Keywords
hierarchical reinforcement learning
(4)
temporal abstraction
(4)
option learning
(3)
large language model
(3)
reinforcement learning
(3)
multi-agent reinforcement learning
(2)
catastrophic forgetting
(2)
policy gradient
(2)
multiagent reinforcement learning
(2)
partially observable environment
(2)
mixing time
(2)
average reward
(2)
attention mechanism
(1)
direct preference optimization
(1)
function approximation
(1)
policy evaluation
(1)
natural language processing
(1)
preference optimization
(1)
policy optimization
(1)
continual learning
(1)
Papers
The Shepherd Test: How Will Super Intelligent Agents Balance Care and Control in Asymmetric Relationships?
AAAI 2026
AI Steerability 360: A Toolkit for Steering Large Language Models
ACL 2026
Combining Domain and Alignment Vectors Provides Better Knowledge-Safety Trade-offs in LLMs
ACL 2025
EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts
ACL 2025
Enabling Realtime Reinforcement Learning at Scale with Staggered Asynchronous Inference
ICLR 2025
Handling Delay in Real-Time Reinforcement Learning
ICLR 2025
Position: Theory of Mind Benchmarks are Broken for Large Language Models
ICML 2025
A Deep Dive into the Trade-Offs of Parameter-Efficient Preference Alignment Techniques
ACL 2024
ComVas: Contextual Moral Values Alignment System
IJCAI 2024
Balancing Context Length and Mixing Times for Reinforcement Learning at Scale
NIPS 2024
Influencing Long-Term Behavior in Multiagent Reinforcement Learning
NIPS 2022
Context-Specific Representation Abstraction for Deep Option Learning
AAAI 2022
Continual Learning In Environments With Polynomial Mixing Times
NIPS 2022
Efficient Black-Box Planning Using Macro-Actions with Focused Effects
IJCAI 2021
RL Generalization in a Theory of Mind Game Through a Sleep Metaphor (Student Abstract)
AAAI 2021
Hierarchical Average Reward Policy Gradient Algorithms (Student Abstract)
AAAI 2020
On the Role of Weight Sharing During Deep Option Learning
AAAI 2020
Scalable Recollections for Continual Lifelong Learning
AAAI 2019
Learning to Teach in Cooperative Multiagent Reinforcement Learning
AAAI 2019
Learning to Learn without Forgetting by Maximizing Transfer and Minimizing Interference
ICLR 2019
Recursive Routing Networks: Learning to Compose Modules for Language Understanding
NAACL 2019
Learning Abstract Options
NIPS 2018
Routing Networks: Adaptive Selection of Non-Linear Functions for Multi-Task Learning
ICLR 2018
Correcting Forecasts with Multifactor Neural Attention
ICML 2016