11 citations · 14 across the 9 of their papers we have counts for
3 papers · 1 filter
CATfOOD: Counterfactual Augmented Training for Improving Out-of-Domain Performance and Calibration
Rachneet Sachdeva, Martin Tutek, Iryna Gurevych
In recent years, large language models (LLMs) have shown remarkable capabilities at scale, particularly at generating text conditioned on a prompt. In our work, we investigate the…
Are Emergent Abilities in Large Language Models just In-Context Learning?
Sheng Lu, Irina Bigoulaeva, Rachneet Sachdeva +2
Large language models, comprising billions of parameters and pre-trained on extensive web-scale corpora, have been claimed to acquire certain capabilities without having been speci…
UKP-SQuARE v3: A Platform for Multi-Agent QA Research
Haritz Puerto, Tim Baumgärtner, Rachneet Sachdeva +5
The continuous development of Question Answering (QA) datasets has drawn the research community's attention toward multi-domain models. A popular approach is to use multi-dataset m…