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Found 4 papers, 2 papers with code
NYCU_TWD@LT-EDI-ACL2022: Ensemble Models with VADER and Contrastive Learning for Detecting Signs of Depression from Social Media
This paper presents a state-of-the-art solution to the LT-EDI-ACL 2022 Task 4: Detecting Signs of Depression from Social Media Text.
RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training
Existing intent detection approaches have highly relied on adaptively pre-training language models with large-scale datasets, yet the predominant cost of data collection may hinder their superiority.
NYCU-TWO at Memotion 3: Good Foundation, Good Teacher, then you have Good Meme Analysis
In this work, we use CLIP to extract aligned image-text features and propose a novel meme sentiment analysis framework, consisting of a Cooperative Teaching Model (CTM) for Task A and a Cascaded Emotion Classifier (CEC) for Tasks B&C.
EmotionGIF-Yankee: A Sentiment Classifier with Robust Model Based Ensemble Methods
This paper provides a method to classify sentiment with robust model based ensemble methods.
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