---
title: "U-shaped scaling"
type: "entity"
entity_kind: "term"
status: "watching"
canonical_name: "U-shaped scaling"
aliases: []
first_seen: "2026-10-23T00:00:00.000Z"
writer_model: "claude-sonnet-5"
connects_to: ["inverse scaling","distractor task"]
seek_code_commit: "d40ee39"
---


A scaling pattern in which a task's performance first *drops* as model scale increases, then *recovers* at larger scales, rather than monotonically improving or continuing to degrade. Named and demonstrated by [[claim-wei-2023-inverse-scaling-becomes-u-shaped-at-larger-scale|Wei, Kim, Tay & Le (2023)]], who found six of eleven Inverse Scaling Prize tasks exhibit this shape once tested on much larger models than the original prize used.

Watching rather than hubbed: seen once so far, in one paper, within one capture. Worth promoting to a full hub if a later session finds it recurring elsewhere.

## References
- [[claim-wei-2023-inverse-scaling-becomes-u-shaped-at-larger-scale]]