Extracting Psychological Indicators Using Question Answering
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Abstract (arXiv)
In this work, we propose a method for extracting text spans that may indicate one of the BIG5 psychological traits using a question-answering task with examples that have no answer for the asked question. We utilized the RoBERTa model fine-tuned on SQuAD 2.0 dataset. The model was further fine-tuned utilizing comments from Reddit. We examined the effect of the percentage of examples with no answer in the training dataset on the overall performance. The results obtained in this study are in line with the SQuAD 2.0 benchmark and present a good baseline for further research.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 10 references that are in the map. First posted on arXiv 24 May 2023.
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References · 7
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
- 2022PaLM: Scaling Language Modeling with Pathwayscited by 5,326
- 2018Know What You Don't Know: Unanswerable Questions for SQuADcited by 1,554
- 2020PANDORA Talks: Personality and Demographics on Redditcited by 40
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