Technical Report

MEE

Human interaction is inherently multimodal. People communicate not only through language, but also through facial expressions, vocal characteristics, temporal patterns, and other observable behavioral signals. Conventional conversational AI systems, however, frequently rely primarily on textual or speech input and therefore have limited access to non-linguistic interaction context.

This technical note presents MEE (Multimodal Emotion Engine), a modular multimodal affective-state estimation system designed for AI companions, intelligent robots, and other human-AI interaction systems.

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Who Am I?

Who Am I? What Local LLMs Reveal About Model Identity, Self-Knowledge, and Runtime Truth Deepsim AI Lab Research & Technical Note — DAI-LAB-TN-2026-002 Dr. Shouke Wei Deepsim AI Lab at Deepsim Intelligence Technology Inc. ORCID: 0000-0002-4665-5366 DOI: https://doi.org/10.5281/zenodo.22064443 Email: [email protected], [email protected] Deepsim Press August 21, 2026 Suggested Citation: Wei, S. (2026). Who Am I? What

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DS-EO: A Governance Framework for Multi-Agent AI Software Engineering

DS-EO: A Governance Framework for Multi-Agent AI Software Engineering Deepsim AI Lab Research & Technical Reports — DAI-LAB-TR-2026-001 Dr. Shouke Wei (魏守科)Founder, Deepsim Intelligence Technology Inc.Deepsim AI LabORCID: 0000-0002-4665-5366DOI: 10.5281/zenodo.21744498 Version 1.0 — August 2026 Abstract Large language models have transformed software development by enabling AI agents to perform increasingly sophisticated engineering activities, including requirements

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