Junsong Ren


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FPAI at SemEval-2021 Task 6: BERT-MRC for Propaganda Techniques Detection
Xiaolong Hou | Junsong Ren | Gang Rao | Lianxin Lian | Zhihao Ruan | Yang Mo | JIanping Shen
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)

The objective of subtask 2 of SemEval-2021 Task 6 is to identify techniques used together with the span(s) of text covered by each technique. This paper describes the system and model we developed for the task. We first propose a pipeline system to identify spans, then to classify the technique in the input sequence. But it severely suffers from handling the overlapping in nested span. Then we propose to formulize the task as a question answering task by MRC framework which achieves a better result compared to the pipeline method. Moreover, data augmentation and loss design techniques are also explored to alleviate the problem of data sparse and imbalance. Finally, we attain the 3rd place in the final evaluation phase.


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FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis Selection
Chenyang Guo | Xiaolong Hou | Junsong Ren | Lianxin Jiang | Yang Mo | Haiqin Yang | Jianping Shen
Proceedings of the Fourteenth Workshop on Semantic Evaluation

This paper describes the model we apply in the SemEval-2020 Task 10. We formalize the task of emphasis selection as a simplified query-based machine reading comprehension (MRC) task, i.e. answering a fixed question of “Find candidates for emphasis”. We propose our subword puzzle encoding mechanism and subword fusion layer to align and fuse subwords. By introducing the semantic prior knowledge of the informative query and some other techniques, we attain the 7th place during the evaluation phase and the first place during train phase.