Research Blog
Deep dives into machine learning research papers, mathematical derivations, and implementation details.
Essential PyTorch: the 5% that shows up in almost every serious model build
•15 min read
PyTorch looks huge from the outside. In practice, I build Transformers, CLIP, diffusion, flows, and VAEs using a small set of tensor and module patterns over and over. This post is that core.
Hierarchical Reasoning Model (HRM): recursion, deep supervision, and why ACT is challenging
•12 min read
A deep dive into HRM architecture—recursive refinement, deep supervision, DEQ-style gradients, and a mechanical breakdown of ACT's halt/continue logic.
Tiny Recursive Model (TRM)
•10 min read
TRM simplifies HRM by removing fixed-point theory, eliminating ACT's extra forward pass, and backpropagating through full unrolled recursion with no-grad refinement passes.
Designing a Deterministic LLM Agent
•12 min read
A coding agent is a stochastic model wrapped in a deterministic scaffold. This post walks through how to build that scaffold with a ledger-style History, derived summaries, allowlisted tools, driver-owned tests, and reflection triggers.
JanusFlow
•10 min read
JanusFlow unifies image understanding and generation in a single LLM backbone using rectified flow. This post explains the architecture, training stages, representation alignment, and why the shared backbone matters.
LLM Repo Agent v2: What's changed since v1
•8 min read
V2 brings Chat Completions adapters, JSON tool protocol, multi-turn message lists, prompt hardening with invariants, sandboxing, multithreading, Monte Carlo evaluation, and SFT/DPO fine-tuning pipelines.
Bug-fixing agent: json tool calling SFT plan
•12 min read
SFT plan to instruction-tune Qwen2.5-7B for JSON tool-protocol compliance. Covers step-level dataset extraction from teacher traces, data quality filtering, QuixBugs train/test splits, and end-to-end pipeline commands.