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Ran Zmigrod

7 accepted papers

2024

Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation

EMNLP 2024finding

Language models are capable of memorizing detailed patterns and information, leading to a double-edged effect: they achieve impressive modeling performance on downstream tasks with the stored knowledge but also raise significant privacy concerns. Traditional differential privacy based training appro…

Cited by 1SourcePDFScholar
2024

“What is the value of templates?” Rethinking Document Information Extraction Datasets for LLMs

EMNLP 2024finding

The rise of large language models (LLMs) for visually rich document understanding (VRDU) has kindled a need for prompt-response, document-based datasets. As annotating new datasets from scratch is labor-intensive, the existing literature has generated prompt-response datasets from available resource…

Cited by 0SourcePDFScholar
2023

Efficient Semiring-Weighted Earley Parsing

ACL 2023long

We present Earley’s (1970) context-free parsing algorithm as a deduction system, incorporating various known and new speed-ups. In particular, our presentation supports a known worst-case runtime improvement from Earley’s (1970) O(N3|G||R|), which is unworkable for the large grammars that arise in n…

2022

Exact Paired-Permutation Testing for Structured Test Statistics

NAACL 2022long

Significance testing—especially the paired-permutation test—has played a vital role in developing NLP systems to provide confidence that the difference in performance between two systems (i.e., the test statistic) is not due to luck. However, practitioners rely on Monte Carlo approximation to perfor…