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Found 8 papers, 2 papers with code
Detecting Suicidality with a Contextual Graph Neural Network
Discovering individuals’ suicidality on social media has become increasingly important.
A Dual-Prompting for Interpretable Mental Health Language Models
Despite the increasing demand for AI-based mental health monitoring tools, their practical utility for clinicians is limited by the lack of interpretability. The CLPsych 2024 Shared Task (Chim et al., 2024) aims to enhance the interpretability of Large Language Models (LLMs), particularly in mental health analysis, by providing evidence of suicidality through linguistic content.
BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation
We validate our method outperforms multiple CTTA scenarios including disjoint and gradual domain shits, while only requiring ~98% fewer trainable parameters.
Improving Lane Detection Generalization: A Novel Framework using HD Maps for Boosting Diversity
Lane detection is a vital task for vehicles to navigate and localize their position on the road.
Learning Co-Speech Gesture for Multimodal Aphasia Type Detection
By learning the correlation between the speech and gesture modalities for each aphasia type, our model can generate textual representations sensitive to gesture information, leading to accurate aphasia type detection.
Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning
Bipolar disorder (BD) is closely associated with an increased risk of suicide.
Resolving Class Imbalance for LiDAR-based Object Detector by Dynamic Weight Average and Contextual Ground Truth Sampling
An autonomous driving system requires a 3D object detector, which must perceive all present road agents reliably to navigate an environment safely.
Cross-Lingual Suicidal-Oriented Word Embedding toward Suicide Prevention
However, little attention has been paid to validate whether and how the existing dictionaries for other languages (i. e., English and Chinese) can be used for predicting suicidal ideation for a low-resource language (i. e., Korean) where a knowledge-based suicide dictionary has not yet been developed.
