6 citations · 21 across the 12 of their papers we have counts for
3 papers · 1 filter
Anchored Preference Optimization and Contrastive Revisions: Addressing Underspecification in Alignment
Karel D'Oosterlinck, Winnie Xu, Chris Develder +5
Large Language Models (LLMs) are often aligned using contrastive alignment objectives and preference pair datasets. The interaction between model, paired data, and objective makes…
Updating CLIP to Prefer Descriptions Over Captions
Amir Zur, Elisa Kreiss, Karel D'Oosterlinck +2
Although CLIPScore is a powerful generic metric that captures the similarity between a text and an image, it fails to distinguish between a caption that is meant to complement the…
In-Context Learning for Extreme Multi-Label Classification
Karel D'Oosterlinck, Omar Khattab, François Remy +3
Multi-label classification problems with thousands of classes are hard to solve with in-context learning alone, as language models (LMs) might lack prior knowledge about the precis…