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Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 09:31

From Visual Perception to Deep Empathy: An Automated Assessment Framework for House-Tree-Person Drawings Using Multimodal LLMs and Multi-Agent Collaboration

Published:Dec 23, 2025 09:26
1 min read
ArXiv

Analysis

This article describes a research paper exploring the use of Large Language Models (LLMs) and multi-agent systems to automatically assess House-Tree-Person (HTP) drawings. The focus is on moving beyond simple visual perception to infer deeper psychological states, such as empathy. The use of multimodal LLMs suggests the integration of both visual and textual information for a more comprehensive analysis. The multi-agent collaboration aspect likely involves different AI agents specializing in different aspects of the drawing assessment. The source, ArXiv, indicates this is a pre-print and not yet peer-reviewed.
Reference

“The article focuses on automated assessment of House-Tree-Person drawings using multimodal LLMs and multi-agent collaboration.”

PermalinkArXiv
Research#LLM🔬 ResearchAnalyzed: Jan 10, 2026 09:31

Differentiable Cognitive Steering for Human-Object Interaction Detection Using Multi-modal LLMs

Published:Dec 19, 2025 14:41
1 min read
ArXiv

Analysis

This research explores a novel approach to human-object interaction detection by leveraging the capabilities of multi-modal large language models (LLMs). The use of differentiable cognitive steering is a potentially significant innovation in guiding LLMs for this complex task.
Reference

“The research is sourced from ArXiv, indicating peer review might still be pending.”

PermalinkArXiv