All-in-one: Multi-task Learning for Rumour Verification
Table 3: Comparison of performance of sequential single task approach, multi-task learning approaches with two and three tasks with majority and NileTMRG baselines on veracity classification task.
['[BOLD] RumourEval', '[BOLD] RumourEval  [BOLD] Majority (True)', '[BOLD] RumourEval  [BOLD] NileTMRG*', '[BOLD] RumourEval  [BOLD] branchLSTM', '[BOLD] RumourEval  [BOLD] MTL2 Veracity+Stance', '[BOLD] RumourEval  [BOLD] MTL2 Veracity+Detection', '[BOLD] RumourEval  [BOLD] MTL3']
It shows the results of the multi-task learning models MTL2 with two tasks: Veracity+Stance and Veracity+Detection; MTL3 with three tasks Stance+Veracity+Detection, Majority, NileTMRG* and single task branchLSTM baselines on the main task, veracity classification.