NLA Maintains Accuracy but Confabulates More
Turn_Trout · x · 2026-07-13
The author proposes an explanation: Claude's guesses might leak some "real stuff," such as the identity of the last token; these rare clues are particularly critical for reconstruction tasks.
The thread also mentions a key finding: an NLA initialized with confabulation achieves almost the same reconstruction accuracy as the control group, but massively increases the confabulation rate, reaching 99.3%. In other words, training can reduce confabulation to some extent, but it's not enough to offset the bias introduced by this initialization; meanwhile, the control group actually learns to confabulate more.
More from Research
- Stanford Team Introduces Gigatoken, the World's Fastest Tokenizer — StanfordAILab · 2026-07-22
- Tabul AI launches Metal TreeSHAP to speed up Shapley values on Apple silicon — Scobleizer · 2026-07-22
- Reddit points to OpenAI’s ChatGPT Ads page — EcstaticAsparagus509 · 2026-07-22
- Open-source runtime lets each repo define its own AI code reviewer — ibabufrik · 2026-07-22
- DeepSWE: A New Benchmark for Evaluating AI Coding Agents on Real GitHub Issues — pmz · 2026-07-22
- A Rust space-economy sim runs hundreds of autonomous ships, built with Claude — kalcode · 2026-07-22