Reading Notes

Notes and summaries from reading ML/AI papers (and some blog posts). All credit to the content in the papers and blog posts goes to the original authors.

End-to-End Test-Time Training for Long Context

TTT-E2E

6 min read · February 26, 2026

2026 · distillation
Interpreting Physics in Video World Models

physics in video models \+ V-JEPA background

2 min read · February 26, 2026

2026 · partial-read · distillation
Language Models use Lookbacks to Track Beliefs

lookback mechanisms

12 min read · February 21, 2026

2026 · distillation
Fast KV Compaction via Attention Matching

Zweiger KV compaction

4 min read · February 20, 2026

2026 · distillation
BRIDGE: Predicting Human Task Completion Time From Model Performance

Predicting Human Time from IRT difficulty

1 min read · February 17, 2026

2026 · partial-read · distillation