374 citations · 827 across the 88 of their papers we have counts for
100 papers
Learning to Play: Reinforcement Learning and Games
Aske Plaat
Amazing breakthroughs in reinforcement learning have taken place. Computers teach themselves to play Chess and Go and beat world champions. There is talk about expanding applicatio…
Reinforcement Learning with Verifiable Rewards for Small Search Agents
Gaurisankar Jayadas, Aske Plaat, Álvaro Serra-Gómez +1
Reinforcement Learning with Verifiable Rewards (RLVR) performs well on problems with clear rewards, such as mathematics and coding, but whether it also works where the reward is le…
Evaluation Metrics for Safe Reinforcement Learning
Lindsay Spoor, Aske Plaat, Thomas Moerland
Safe reinforcement learning (RL) is commonly formalized as a Constrained Markov Decision Process (CMDP), in which an agent maximizes expected reward while keeping its expected cumu…
Silent Metronome: Rhythmic Grounding for Live Music Accompaniment
Kevin Bretz, Derya Soydaner, Aske Plaat
Live accompaniment models generate music for an incoming audio stream, committing to each output frame before hearing what comes next. In this strictly causal setting the model mus…
Detecting and Repairing Hallucinations in Retrieval-Augmented Generation
Sai Krishna Reddy Mulakkayala, Niki van Stein, Aske Plaat
Language models increasingly answer questions by consulting retrieved documents rather than memory alone, a design now common in search assistants and enterprise knowledge tools. G…
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning
Zhao Yang, Yuxuan Jiang, Ting-Chih Chen +18
Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a narrow slice of what RL offers.…