85 citations · 193 across the 8 of their papers we have counts for
3 papers · 2 filters
Understanding In-Context Learning via Supportive Pretraining Data
Xiaochuang Han, Daniel Simig, Todor Mihaylov +3
In-context learning (ICL) improves language models' performance on a variety of NLP tasks by simply demonstrating a handful of examples at inference time. It is not well understood…
Evaluating end-to-end entity linking on domain-specific knowledge bases: Learning about ancient technologies from museum collections
Sebastian Cadavid-Sanchez, Khalil Kacem, Rafael Aparecido Martins Frade +4
To study social, economic, and historical questions, researchers in the social sciences and humanities have started to use increasingly large unstructured textual datasets. While r…
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization
Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru +15
Recent work has shown that fine-tuning large pre-trained language models on a collection of tasks described via instructions, a.k.a. instruction-tuning, improves their zero and few…