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Found 7 papers, 5 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.
A Survey on Self-Supervised Learning for Non-Sequential Tabular Data
Recently, SSL has been a new trend in exploring the representation learning capability in the realm of tabular data, which is more challenging due to not having explicit relations for learning descriptive representations.
DoRA: Domain-Based Self-Supervised Learning Framework for Low-Resource Real Estate Appraisal
Existing automated valuation models reducing the subjectivity of domain experts require a large number of transactions for effective evaluation, which is predominantly limited to not only the labeling efforts of transactions but also the generalizability of new developing and rural areas.
Benchmarking Stroke Forecasting with Stroke-Level Badminton Dataset
In recent years, badminton analytics has drawn attention due to the advancement of artificial intelligence and the efficiency of data collection.
Team Triple-Check at Factify 2: Parameter-Efficient Large Foundation Models with Feature Representations for Multi-Modal Fact Verification
Multi-modal fact verification has become an important but challenging issue on social media due to the mismatch between the text and images in the misinformation of news content, which has been addressed by considering cross-modalities to identify the veracity of the news in recent years.
Look Around! A Neighbor Relation Graph Learning Framework for Real Estate Appraisal
However, existing methods only consider the real estate itself, ignoring the relation between the properties.
Track2Vec: fairness music recommendation with a GPU-free customizable-driven framework
Recommendation systems have illustrated the significant progress made in characterizing users' preferences based on their past behaviors.
