Papers by Long Vo-Dang

2 papers
Sentiment Reasoning for Healthcare (2025.acl-industry)

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Challenge: Sentiment Reasoning is an auxiliary task in sentiment analysis where the model predicts both the sentiment label and generates the rationale behind it based on the input transcript.
Approach: They propose a task - Sentiment Reasoning - for both speech and textmodalities and propose 'multimodal multitask framework' . they propose to use a model that generates the rationale behind each predicted label and provides a rationale for model prediction with quality semantically comparable to humans.
Outcome: The proposed task improves model transparency by providing rationale for model prediction with quality semantically comparable to humans while improving model’s classification performance.
Medical Spoken Named Entity Recognition (2025.naacl-industry)

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Challenge: Named Entity Recognition (NER) aims to extract named entities from speech and categorise them into types like person, location, organization, etc.
Approach: They present a spoken NER dataset in the medical domain using pre-trained models that are encoder-only and sequence-to-sequence.
Outcome: The dataset is the largest spoken NER dataset in the world regarding the number of entity types, featuring 18 distinct types.

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