Kimi k1.5 Reinforcement Learning vs. Next-Token Pretraining on Reasoning Benchmarks

Abstract

Abstract: This report synthesises findings from 3 peer-reviewed papers addressing the following research question: How does Kimi k1.5's reinforcement learning approach compare to next-token prediction pretraining in terms of performance on MMLU or BIG-Bench Hard reasoning benchmarks. 10 claims were extracted from source literature; 9 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 7.8/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research Question

How does Kimi k1.5's reinforcement learning approach compare to next-token prediction pretraining in terms of performance on MMLU or BIG-Bench Hard reasoning benchmarks?

Verification Level

Descriptive public verification status only; aggregate claim counts are public, but individual claim records are not exposed here.

Quality Tier

Descriptive public triage only; this tier does not alter current publication or DOI behavior.

Quality Dimensions

Automated triage signals derived from public fields; not human peer review or independent validation.

Correction Record

Public corrections are additive records. Current status does not claim the synthesis is error-free.

Provenance