80 citations · 216 across the 11 of their papers we have counts for
23 papers
EditEval: An Instruction-Based Benchmark for Text Improvements
Jane Dwivedi-Yu, Timo Schick, Zhengbao Jiang +6
Evaluation of text generation to date has primarily focused on content created sequentially, rather than improvements on a piece of text. Writing, however, is naturally an iterativ…
Entity Tagging: Extracting Entities in Text Without Mention Supervision
Christina Du, Kashyap Popat, Louis Martin +1
Detection and disambiguation of all entities in text is a crucial task for a wide range of applications. The typical formulation of the problem involves two stages: detect mention…
EDIN: An End-to-end Benchmark and Pipeline for Unknown Entity Discovery and Indexing
Nora Kassner, Fabio Petroni, Mikhail Plekhanov +2
Existing work on Entity Linking mostly assumes that the reference knowledge base is complete, and therefore all mentions can be linked. In practice this is hardly ever the case, as…
Open Vocabulary Extreme Classification Using Generative Models
Daniel Simig, Fabio Petroni, Pouya Yanki +4
The extreme multi-label classification (XMC) task aims at tagging content with a subset of labels from an extremely large label set. The label vocabulary is typically defined in ad…
Autoregressive Search Engines: Generating Substrings as Document Identifiers
Michele Bevilacqua, Giuseppe Ottaviano, Patrick Lewis +3
Knowledge-intensive language tasks require NLP systems to both provide the correct answer and retrieve supporting evidence for it in a given corpus. Autoregressive language models…
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models
Robert L. Logan, Ivana Balažević, Eric Wallace +3
Prompting language models (LMs) with training examples and task descriptions has been seen as critical to recent successes in few-shot learning. In this work, we show that finetuni…