MLn Club (ML Reading Group) #14: Attention Residuals: Rethinking Information Flow in LLMs
Welcome to Week 14: Attention Residuals: Rethinking Information Flow in LLMs
The Paper Link Here
This paper introduces Attention Residuals (AttnRes), a novel architectural mechanism by the Kimi Team designed to rethink how information flows in modern Large Language Models (LLMs). The central challenge addressed in the work is that standard residual connections with PreNorm accumulate all layer outputs using fixed unit weights. This uniform aggregation causes uncontrolled hidden-state growth with depth, progressively diluting each layer's unique contribution. To overcome this limitation, the authors replace this fixed accumulation with a softmax attention mechanism over preceding layer outputs, allowing each layer to selectively aggregate earlier representations using learned, input-dependent weights.
Join us at CASI for discussion at 8 pm, and (optional) quiet reading from 7 pm.
📖 Reading Recommendations, Questions, or Comments? Contact us here!
🔎 View past meeting notes here.
What's this?
A super warm group of folks discussing their favorite topics!
In the first half, we host an optional quiet reading space
In the second half, we have a discussion where people can talk about what they found interesting about the reading and ask questions about things they didn't understand
When/Where:
CMU AI Safety Initiative's Office, 201 Craig Street, right across the PNC bank. Look for the open door up the stairs.
8pm discussion, 7pm optional quiet reading time.
Here's how it usually goes:
7:00 PM — arrival and settling in
8:00 PM — introductions
8:10 PM — discussion time
9:00 PM — wrap up then open discussion
Who's it for?
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.
Why:
We've been procrastinating too much on our readings, even though we have so much fun doing them. We know we're not alone in this and want to keep others accountable for learning more about what they're passionate about!
We've also met a ton of really fun friends by discussing what we care about!
Rules/guidelines on how to act:
Act like a host, include people in conversations, talk to people even if they're strangers, offer to explain what you know, and keep an open mind! come to read stuff and find super fun friends :)
Bring snacks if you're feeling kind!