most citedFEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information

52 citations · 54 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL202152 cited

FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information

Rami Aly, Zhijiang Guo, Michael Schlichtkrull +5

Fact verification has attracted a lot of attention in the machine learning and natural language processing communities, as it is one of the key methods for detecting misinformation…

cs.CL2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Sewon Min, Jordan Boyd-Graber, Chris Alberti +50

We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and…

cs.CL2020

Joint Verification and Reranking for Open Fact Checking Over Tables

Michael Schlichtkrull, Vladimir Karpukhin, Barlas Oğuz +3

Structured information is an important knowledge source for automatic verification of factual claims. Nevertheless, the majority of existing research into this task has focused on…

cs.CL20202 cited

Evaluating for Diversity in Question Generation over Text

Michael Sejr Schlichtkrull, Weiwei Cheng

Generating diverse and relevant questions over text is a task with widespread applications. We argue that commonly-used evaluation metrics such as BLEU and METEOR are not suitable…

cs.CL2020

How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking

Nicola De Cao, Michael Schlichtkrull, Wilker Aziz +1

Attribution methods assess the contribution of inputs to the model prediction. One way to do so is erasure: a subset of inputs is considered irrelevant if it can be removed without…