[2603.18788] Mi:dm K 2.5 Pro

Computer Science > Computation and Language arXiv:2603.18788 (cs) [Submitted on 19 Mar 2026 (v1), last revised 24 Mar 2026 (this version, v2)] Title:Mi:dm K 2.5 Pro Authors:KT Tech innovation Group View a PDF of the paper titled Mi:dm K 2.5 Pro, by KT Tech innovation Group View PDF HTML (experimental) Abstract:The evolving LLM landscape requires capabilities beyond simple text generation, prioritizing multi-step reasoning, long-context understanding, and agentic workflows. This shift challenges existing models in enterprise environments, especially in Korean-language and domain-specific scenarios where scaling is insufficient. We introduce Mi:dm K 2.5 Pro, a 32B parameter flagship LLM designed to address enterprise-grade complexity through reasoning-focused optimization. Our methodology builds a robust data foundation via a quality-centric curation pipeline utilizing abstract syntax tree (AST) analysis for code, gap-filling synthesis for mathematics, and an LLM-based quality evaluator. Pre-training scales the model via layer-predictor-based Depth Upscaling (DuS) and a progressive strategy supporting a 128K token context window. Post-training introduces a specialized multi-stage pipeline, including Reasoning SFT, model merging, and asynchronous reinforcement learning (RL), to develop complex problem-solving skills. "Fusion Training" then rebalances these capabilities with conversational fluency, consistent response styling, and reliable tool-use. The evaluations show that M...