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Majid Yazdani

Facebook AI, EPFL, Linkedin, Idiap research institute

9 papers hereh-index 131.3k citations32 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author5
  • last author3

Across the 8 of 9 papers where every author was matched, so the position is known.

fields
  • cs.CL9
affiliations
  • Facebook AI, EPFL, Linkedin, Idiap research institute
same name
  • Majid Yazdani — 2 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172022
most citedNeural Databases

13 citations · 28 across the 6 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CL2022★ 3 cited

RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question

Alireza Mohammadshahi, Thomas Scialom, Majid Yazdani +4

Existing metrics for evaluating the quality of automatically generated questions such as BLEU, ROUGE, BERTScore, and BLEURT compare the reference and predicted questions, providing…

cs.CL2022★ 1 cited

Policy Compliance Detection via Expression Tree Inference

Neema Kotonya, Andreas Vlachos, Majid Yazdani +2

Policy Compliance Detection (PCD) is a task we encounter when reasoning over texts, e.g. legal frameworks. Previous work to address PCD relies heavily on modeling the task as a spe…

cs.CL2022★ 1 cited

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…

cs.CL2022★ 8 cited

PERFECT: Prompt-free and Efficient Few-shot Learning with Language Models

Rabeeh Karimi Mahabadi, Luke Zettlemoyer, James Henderson +4

Current methods for few-shot fine-tuning of pretrained masked language models (PLMs) require carefully engineered prompts and verbalizers for each new task to convert examples into…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.