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Found 10 papers, 4 papers with code
SOS-1K: A Fine-grained Suicide Risk Classification Dataset for Chinese Social Media Analysis
Seven pre-trained models were evaluated in two tasks: high and low suicide risk, and fine-grained suicide risk classification on a level of 0 to 10.
AI-Enhanced Cognitive Behavioral Therapy: Deep Learning and Large Language Models for Extracting Cognitive Pathways from Social Media Texts
Cognitive Behavioral Therapy (CBT) is an effective technique for addressing the irrational thoughts stemming from mental illnesses, but it necessitates precise identification of cognitive pathways to be successfully implemented in patient care.
Towards a Psychological Generalist AI: A Survey of Current Applications of Large Language Models and Future Prospects
The complexity of psychological principles underscore a significant societal challenge, given the vast social implications of psychological problems.
Supervised Learning and Large Language Model Benchmarks on Mental Health Datasets: Cognitive Distortions and Suicidal Risks in Chinese Social Media
In response, we introduce two novel annotated datasets from Chinese social media, focused on cognitive distortions and suicidal risk classification.
Enhancing Psychological Counseling with Large Language Model: A Multifaceted Decision-Support System for Non-Professionals
In the contemporary landscape of social media, an alarming number of users express negative emotions, some of which manifest as strong suicidal intentions.
Unconfounded Propensity Estimation for Unbiased Ranking
The goal of unbiased learning to rank (ULTR) is to leverage implicit user feedback for optimizing learning-to-rank systems.
Cross-view Action Recognition via Contrastive View-invariant Representation
Cross view action recognition (CVAR) seeks to recognize a human action when observed from a previously unseen viewpoint.
Interpretable machine learning-accelerated seed treatment by nanomaterials for environmental stress alleviation
Seed treatment by nanomaterials is a cost-effective and environmentally-friendly solution for environmental stress mitigation in crop plants.
Model-based Unbiased Learning to Rank
Existing methods in unbiased learning to rank typically rely on click modeling or inverse propensity weighting (IPW).
Memory Defense: More Robust Classification via a Memory-Masking Autoencoder
Ideally, a robust classifier would be immune to small variations in input images, and a number of defensive approaches have been created as a result.
