Browsing: Reinforcement

Kyutai has released Hibiki-Zero, a new model for simultaneous speech-to-speech translation (S2ST) and speech-to-text translation (S2TT). The system translates source speech into a target language in…

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment,…

Nous Research has introduced NousCoder-14B, a competitive olympiad programming model that is post trained on Qwen3-14B using reinforcement learning (RL) with verifiable rewards. On the LiveCodeBench…

What does an end to end stack for terminal agents look like when you combine structured toolkits, synthetic RL environments, and benchmark aligned evaluation? A team…

Liquid AI has introduced LFM2-2.6B-Exp, an experimental checkpoint of its LFM2-2.6B language model that is trained with pure reinforcement learning on top of the existing LFM2…

In this tutorial, we explore how an agent can internalize planning, memory, and tool use within a single neural model rather than relying on external orchestration.…

AgiBot has just achieved what many in robotics research have been chasing for years: the first real-world deployment of reinforcement learning (RL) in industrial robotics. In…

How can AI teams run Tinker style reinforcement learning on large language models using their own infrastructure with a single unified engine? Anyscale and NovaSky (UC…

How can a small model learn to solve tasks it currently fails at, without rote imitation or relying on a correct rollout? A team of researchers…