Kyutai's Voice of Reason uses reinforcement learning to lift GLM-4-Voice from 27.3% to 77.1% on spoken GSM8K math.

Newly announced reinforcement learning with calibrated decisions (RLCD) is mindfully unpacked. An AI Insider analysis and scoop.

Prompt sampling reinforcement learning with LEEPS improves large language model training efficiency and reasoning across benchmarks.

Training an animal on a complex task is often a painstaking, incremental process. This is because conventional behavioral learning protocols focus on minimizing reward to maximize trials. Gong et al.

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Negative reinforcement is a frequently misused term that diminishes its value as a powerful tool for behavior change. You may be puzzled by the claim that negative reinforcement is actually a good ...

Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...

Download PDF Join the Discussion View in the ACM Digital Library Deep reinforcement learning (DRL) has elevated RL to complex environments by employing neural network representations of policies. 1 It ...