LaSeR explores last-token rewards for LLMs
In a post published on October 19, 2025, Tencent presents LaSeR, a reinforcement learning algorithm that aligns last-token scores with real rewards and uses one extra token inference.
Source: LaSeR usa self-rewarding do último token em reinforcement learning para LLMs (x.com). Text prepared with AI from this source.
What happened and what to do
In a post dated October 19, 2025, Tencent presents LaSeR, a reinforcement learning algorithm for aligning last-token scores with real rewards. The approach targets reasoning and self-rewarding in language models and, according to the post, uses one extra token inference.
A company tuning models could assess this approach in a controlled experiment: record scores, rewards, and inference costs, compare results with its current method, and monitor response quality. Implementation depends on diagnosing the data, infrastructure, and training objectives.
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