activity
20172022
most citedPERFECT: Prompt-free and Efficient Few-shot Learning with Language Models

8 citations · 12 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL20221 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.CL20221 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.CL20228 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…

cs.CL2021

Cross-Policy Compliance Detection via Question Answering

Marzieh Saeidi, Majid Yazdani, Andreas Vlachos

Policy compliance detection is the task of ensuring that a scenario conforms to a policy (e.g. a claim is valid according to government rules or a post in an online platform confor…

cs.CL2021

Database Reasoning Over Text

James Thorne, Majid Yazdani, Marzieh Saeidi +3

Neural models have shown impressive performance gains in answering queries from natural language text. However, existing works are unable to support database queries, such as "List…

cs.CL2020

Neural Databases

James Thorne, Majid Yazdani, Marzieh Saeidi +3

In recent years, neural networks have shown impressive performance gains on long-standing AI problems, and in particular, answering queries from natural language text. These advanc…