A sequence to sequence transformer data logic experiment

International audienceIn this paper we present experiments to evaluate how a T5 model behaves with regard to input data fidelity. The rationale behind these experiments is to evaluate if a sequence to sequence transformer can be constrained into generating the specifics of a financial report, and more generally whether it can trustfully reproduce a semantic logic, and to what extent

The Financial Document Causality Detection Shared Task (FinCausal 2020)

We present the FinCausal 2020 Shared Task on Causality Detection in Financial Documents and the associated FinCausal dataset, and discuss the participating systems and results. Two sub-tasks are proposed: a binary classification task (Task 1) and a relation extraction task (Task 2). A total of 16 teams submitted runs across the two Tasks and 13 of them contributed with a system description paper. This workshop is associated to the Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation (FNP-FNS 2020), held at The 28th International Conference on Computational Linguistics (COLING'2020), Barcelona, Spain on September 12, 2020