Mustang Wang

Tag: llm

  • Benchmarking 17 AI Models on Razavi’s Analog Design Questions

    I re-ran Behzad Razavi’s ‘Analog Mind’ LLM experiments across 17 model configurations, with a controlled anonymized grader and ngspice as the referee. The methodology moved scores as much as the models did.

  • One Prompt, One Complete IEEE Transactions Project with Claude Code

    A single copy-pasteable prompt that makes Claude Code scaffold a complete IEEE Transactions LaTeX project: main manuscript, S-numbered supplementary materials, a shared author file, and a full revision workflow – with no dependencies beyond a TeX distribution and make.

  • Train a Transformer on Silicon: #0 The Genesis

    Start here — the series hub A short intro to a series where I build a chip that trains a transformer — and document the whole thing, mistakes included. What this is I’m building a digital chip that trains a transformer on-chip — not just runs it, but actually learns: forward pass, backpropagation, and weight…

  • Claude Code Cheat Code

    Default Options Copy and run the following code to allow Claude to run itself without asking for permissions every time it wants to run code. Variables Monitors

  • Note on NotebookLM

  • Gallery of LLM Prompts

    This post is going to explore a new way for blogging, by gathering tweets from X or Twitter that discuss a certain topic. I consider it as a note for me, you could utilize all those info on your workflow. You could click any of the tweet to go back to the original source.

  • Rook2Vet4Word2Vec

    The goal of this blog is to help readers understand what word2vec means so that rookie like you could become a veteran on the concept of embeddings training process. I’ve tried to find resources to understand how word2vec actually works. What surprises me the most is that although it looks really simple in terms of…

  • Revolutionizing Academic Workflows: AI-Powered Equation Extraction from PDFs to LaTeX

    In the fast-paced world of academia and technical writing, efficiency is key. As researchers, students, and professionals, we often grapple with the tedious task of extracting equations from PDF papers and converting them into LaTeX code. This process, while crucial for writing papers, blogging, or taking comprehensive notes, has long been a bottleneck in our…