# ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling

Source: [ISCAS at SemEval-2020 Task 5: Pre-trained Transformers for Counterfactual Statement Modeling](<https://www.sota2.com/research/paper/68fa684f1e209131cea1b59c>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-27T06:03:45.482Z

Authors: Yaojie Lu, Annan Li, Hongyu Lin, Xianpei Han, Le Sun

Published: 2020-09-17T09:28:07.000Z

## Abstract

ISCAS participated in two subtasks of SemEval 2020 Task 5: detecting counterfactual statements and detecting antecedent and consequence. This paper describes our system which is based on pre-trained transformers. For the first subtask, we train several transformer-based classifiers for detecting counterfactual statements. For the second subtask, we formulate antecedent and consequence extraction as a query-based question answering problem. The two subsystems both achieved third place in the evaluation. Our system is openly released at https://github.com/casnlu/ISCAS-SemEval2020Task5.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2009.08171>)

[PDF](<https://arxiv.org/pdf/2009.08171.pdf>)