Papers by Feifan Yang

3 papers
Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations (2026.acl-long)

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Challenge: Previous work shows that large language models generate hallucinations, yet the origins and mechanisms of these signals remain unclear.
Approach: They propose to validate and disentangle two different pathways for truthfulness cues . they also propose to use the same mechanism to derive self-contained evidence from the generated answer .
Outcome: The proposed applications improve hallucination detection performance by integrating two different inputs.
Psycholinguistic Tripartite Graph Network for Personality Detection (2021.acl-long)

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Challenge: Existing work on personality detection from online posts adopts multifarious deep neural networks to represent the posts and builds predictive models in a data-driven manner without the exploitation of psycholinguistic knowledge.
Approach: They propose a psycholinguistic knowledge-based tripartite graph network, TrigNet, which consists of a tripartitic graph network and a BERT-based graph initializer.
Outcome: The proposed graph network outperforms the existing state-of-the-art model by 3.47 and 2.10 points in average F1 on two datasets.
Learning to Answer Psychological Questionnaire for Personality Detection (2021.findings-emnlp)

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Challenge: Existing text-based personality detection research relies on data-driven approaches to implicitly capture personality cues in online posts lacking the guidance of psychological knowledge.
Approach: They propose a model to capture key information in texts and a questionnaire to help the user to make a personality assessment.
Outcome: The proposed model captures key information in texts and a questionnaire and can be used to improve personality prediction.

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