DELIFT: DATA EFFICIENT LANGUAGE MODEL INSTRUCTION FINE-TUNING
Ishika Agarwal, Krishnateja Killamsetty, et al.
ICLR 2025
We describe a large, high-quality benchmark for the evaluation of Mention Detection tools. The benchmark contains annotations of both named entities as well as other types of entities, annotated on different types of text, ranging from clean text taken from Wikipedia, to noisy spoken data. The benchmark was built through a highly controlled crowd sourcing process to ensure its quality. We describe the benchmark, the process and the guidelines that were used to build it. We then demonstrate the results of a state-of-the-art system running on that benchmark.
Ishika Agarwal, Krishnateja Killamsetty, et al.
ICLR 2025
Arafat Sultan, Jatin Ganhotra, et al.
EMNLP 2024
Scott McCarley, Mihaela Bornea, et al.
AAAI 2023
Felipe Maia Polo, Lucas Weber, et al.
ICLR 2024