Nov 25, 2024
Clear Thought and Clear Speech: Reducing Grammatical Scope Ambiguity
Zmavli Caimle
With language models starting to be used in fields such as law, unambiguity in wording is an important desideratum in model outputs. I therefore try to find features in Llama-3.1-70B-Instruct that correspond to grammatical scope ambiguity using Goodfire's contrastive feature search tool, and try to steer the model away from ambiguous outputs using Goodfire's feature nudging tool.
Jason Schreiber
This is a really interesting application of feature steering. It's great to see more subtle applications of feature steering being explored - with some additional development this work could be a really interesting data point on the limits (or lack thereof) of current feature steering methods
Tom McGrath
This is an interesting project - it's a little surprising to me that features can have nuanced stylistic effects, even if only marginally. The autointerp labels we generated for these features could definitely be better, so kudos to the authors for finding features that have these effects using the contrast tool.
I appreciate the grounded nature of this work: qualitative observations can be the foundation of good science. More examples would be good, and if this was developed further I'd want to see some kind of quantitative evaluation.
Alana Xiang
The author successfully uses steering to decrease "grammatical scope ambiguity."
With more time, I'd love to see the author work on quantifying the effect and comparing this approach to baselines like prompting.
Good work!
Cite this work
@misc {
title={
@misc {
},
author={
Zmavli Caimle
},
date={
11/25/24
},
organization={Apart Research},
note={Research submission to the research sprint hosted by Apart.},
howpublished={https://apartresearch.com}
}
