From Sparse Representations to Behavioral Insights for Multimodal Depression Assessment

arXiv:2610.11787 · cs.CL · Submitted 2026-10-08 · Read on arXiv

cs.CL

Submitted: 2026-10-08

Updated: 2026-10-08

Terminology

• Aggregation — 5× in this paper · explained in 1 episode
• Alignment — 5× in this paper · explained in 1 episode
• Interpretability — 4× in this paper · explained in 15 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Representation Learning — 3× in this paper · explained in 2 episodes
• Ablation study — 2× in this paper · explained in 1 episode
• Consistency — 2× in this paper · explained in 3 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Multimodal Learning — 2× in this paper · explained in 2 episodes
• Semantic Alignment — 2× in this paper · explained in 3 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Algorithmic Bias — 1× in this paper · explained in 1 episode
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Multimodal Fusion — 1× in this paper · explained in 3 episodes
• Multimodal Integration — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Qwen2-Audio Technical Report
• What do we need to build explainable AI systems for the medical domain?
• Bidirectional LSTM-CRF Models for Sequence Tagging
• Perceiver IO: A General Architecture for Structured Inputs & Outputs
• Llama 2: Open Foundation and Fine-Tuned Chat Models

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