May 2026 Monthly Summary — ms-swift delivered MiniCPM-V-4.6 integration with a dedicated loader and 4.6-specific template, plus performance-oriented updates to device mapping and input handling for faster training and inference. Key bug fixes include corrected sliced image token splitting and reinforced collator/vLLM paths, along with downsample mode integration in the 4.6 template to improve media input processing. Business impact: expanded model compatibility, more robust media pipelines, and streamlined workflows for customers adopting MiniCPM-V-4.6. Technologies/skills demonstrated: model loading patterns, template engineering, tokenization fixes, input handling, device mapping, and end-to-end integration with collator and vLLM components.

October 2025 — inclusionAI/AReaL: Delivered reinforcement learning stability improvements by implementing the M2PO algorithm and a dedicated loss to constrain the second moment of importance weights, complemented by an update to the M2PO loss mask. Implemented in collaboration with Gemini guidance (commit c431dd6c41712640dfcd359ecdd9d6707f475053). Impact: more stable off-policy training, reduced variance in policy updates, and better reliability for deployment. Technologies demonstrated include reinforcement learning algorithms, loss function design, off-policy training, and Git-based collaboration.