2024

Aeree Cho; Grace C. Kim; Alexander Karpekov; Alec Helbling; Zijie J. Wang; Seongmin Lee; Benjamin Hoover; Duen Horng (Polo) Chau · Georgia Institute of Technology (Polo Club of Data Science)

An interactive tool that runs a live GPT-2 instance in your browser and visualises every stage of the forward pass — embeddings, attention, MLP, output probabilities — updating as you type your own text.

The most accessible route into transformer internals that exists: no installation, no GPU, no prior knowledge. That is a different kind of contribution from any research result in this ledger, and arguably a wider-reaching one.

High · Read the arXiv abstract page in full, 2026-08-06. The live tool itself was not inspected — it is client-rendered and the fetch returned an empty page shell.

Yida Chen; Aoyu Wu; Trevor DePodesta; Catherine Yeh; Kenneth Li; Nicholas Castillo Marin; Oam Patel; Jan Riecke; Shivam Raval; Olivia Seow; Martin Wattenberg; Fernanda Viégas · Harvard University

A dashboard that sits beside a chatbot and shows, in real time, what the model has internally inferred about the user's age, gender, education and socioeconomic status — and lets the user edit those inferences and watch the responses change.

Almost everything else in this ledger is built for researchers; this is built for the person being modelled, and a user study found it helped participants expose the system's biased behaviour.

High · Read the arXiv abstract page in full, 2026-08-06. Project page (bit.ly/talktuner-project-page) not fetched.

Anthropic Interpretability team (individual contributors not named on the post) · Anthropic

For 24 hours Anthropic put a version of Claude 3 Sonnet online with its 'Golden Gate Bridge' feature clamped to roughly ten times maximum activation, so anyone could talk to a model that could not stop mentioning the bridge.

Turned an interpretability result into something the public could feel rather than read, and showed that a single identified feature exerts precise causal control over behaviour — not prompting, not fine-tuning.

High · Read the announcement post in full, 2026-08-06

Adly Templeton; Tom Conerly; Jonathan Marcus; Jack Lindsey; Trenton Bricken; Brian Chen; Adam Jermyn; et al. · Anthropic

First demonstration that sparse autoencoders scale from toy models to a frontier production model, published as a browsable index of millions of features — including the Golden Gate Bridge feature that later became a public demo.

The moment interpretability stopped being a toy-model science, and the origin of the field's most famous public artefact.

High · Read the article; cross-referenced in BlueDot and ACX pieces, 2026-08-06