Name: MLn Club (ML Reading Group) #7: In-context Learning and Induction Heads
Start: 2026-06-29T19:00:00.000-04:00
End: 2026-06-29T21:00:00.000-04:00
Location: 201 S Craig St

We meet weekly on Sundays in person to talk about ML papers! Optional quiet reading from 7 pm, discussion starts 8 pm. Come and join the discussion! Open to all. Website: https://czhs.github.io/mln/

MLn Reading Club

Week 7: In-context Learning and Induction Heads

People who've been wanting to read up on the latest papers in ML and other fields but just haven't been able to find the time/motivation.

When does a model suddenly learn to learn — and can you spot the moment on the loss curve?

If a circuit is defined to do nothing but copy random text, why does the same circuit also translate French?

 Olsson, Elhage, Nanda, et al. (Anthropic)

This blog post suggests that induction heads might constitute the mechanism for the actual majority of all in-context learning in large transformer models.

The majority of in-context learning ability (as measured by difference in loss between tokens early and late in the sequence) is acquired, and simultaneously induction heads form within the model that are capable of implementing fairly abstract and fuzzy versions of pattern completion.

 for discussion at 8 pm, and (optional) quiet reading from 7 pm.

Reading Recommendations, Questions, or Comments? Contact us 

MLn Club (ML Reading Group) #7: In-context Learning and Induction Heads