14 citations · 75 across the 28 of their papers we have counts for
3 papers · 1 filter
Annotations Mitigate Post-Training Mode Collapse
Jacob Mitchell Springer, Madhu Advani, Lukas Aichberger +7
Post-training (via supervised fine-tuning) improves instruction-following, but often induces semantic mode collapse by biasing models toward low-entropy fine-tuning data at the exp…
UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity
Yicheng Fu, Raviteja Anantha, Prabal Vashisht +2
Generating user intent from a sequence of user interface (UI) actions is a core challenge in comprehensive UI understanding. Recent advancements in multimodal large language models…
When can transformers reason with abstract symbols?
Enric Boix-Adsera, Omid Saremi, Emmanuel Abbe +3
We investigate the capabilities of transformer models on relational reasoning tasks. In these tasks, models are trained on a set of strings encoding abstract relations, and are the…