activity
20152026
most citedAtlas: Few-shot Learning with Retrieval Augmented Language Models

201 citations · 562 across the 21 of their papers we have counts for

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Showing 2020Show all

8 papers · 1 filter

cs.CL2020★ 29 cited

A Memory Efficient Baseline for Open Domain Question Answering

Gautier Izacard, Fabio Petroni, Lucas Hosseini +3

Recently, retrieval systems based on dense representations have led to important improvements in open-domain question answering, and related tasks. While very effective, this appro…

cs.CL2020

Generating Fact Checking Briefs

Angela Fan, Aleksandra Piktus, Fabio Petroni +5

Fact checking at scale is difficult -- while the number of active fact checking websites is growing, it remains too small for the needs of the contemporary media ecosystem. However…

cs.CL2020

Autoregressive Entity Retrieval

Nicola De Cao, Gautier Izacard, Sebastian Riedel +1

Entities are at the center of how we represent and aggregate knowledge. For instance, Encyclopedias such as Wikipedia are structured by entities (e.g., one per Wikipedia article).…

cs.CL2020

KILT: a Benchmark for Knowledge Intensive Language Tasks

Fabio Petroni, Aleksandra Piktus, Angela Fan +10

Challenging problems such as open-domain question answering, fact checking, slot filling and entity linking require access to large, external knowledge sources. While some models d…

cs.CV2020★ 26 cited

Video Understanding as Machine Translation

Bruno Korbar, Fabio Petroni, Rohit Girdhar +1

With the advent of large-scale multimodal video datasets, especially sequences with audio or transcribed speech, there has been a growing interest in self-supervised learning of vi…

cs.LG2020

Concept Matching for Low-Resource Classification

Federico Errica, Ludovic Denoyer, Bora Edizel +4

We propose a model to tackle classification tasks in the presence of very little training data. To this aim, we approximate the notion of exact match with a theoretically sound mec…