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Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 07:26

Representation Calibration and Uncertainty Guidance for Class-Incremental Learning based on Vision Language Model

Published:Dec 10, 2025 09:09
1 min read
ArXiv

Analysis

This article focuses on class-incremental learning, a challenging area in AI. It explores how to improve this learning paradigm using vision-language models. The core of the research likely involves techniques to calibrate representations and guide the learning process based on uncertainty. The use of vision-language models suggests an attempt to leverage the rich semantic understanding capabilities of these models.
Reference

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PermalinkArXiv
Research#llm🔬 ResearchAnalyzed: Jan 4, 2026 09:02

HMR3D: Hierarchical Multimodal Representation for 3D Scene Understanding with Large Vision-Language Model

Published:Nov 28, 2025 08:06
1 min read
ArXiv

Analysis

The article introduces HMR3D, a method for 3D scene understanding using a large vision-language model. The focus is on hierarchical multimodal representation, suggesting an approach that integrates visual and textual information at different levels of abstraction. The source being ArXiv indicates this is a research paper, likely detailing the technical aspects, experiments, and results of the proposed method.
Reference

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PermalinkArXiv