Yuxiang Lin

lin.yuxiang.contact@gmail.com

I am an AI Engineer at Item and Unisco.

I received my MS ECE degree from the Georgia Institute of Technology, where my research interests centered on Multimodal Large Language Models (MLLM) and Affective Computing. Previously, I gained industrial algorithm experience as an intern at Tencent and Baidu.

My current interests include:

AI Application & Memory Systems
Graph-based RAG Systems
Multi-agent Collaboration
Large Language Models (LLMs) & Multimodal LLMs

Open to opportunities! I am happy to discuss any collaboration or role — feel free to reach out.

news

Sep 01, 2025	Started my career as an AI Engineer at Item and Unisco after graduation.
Jul 01, 2025	Try MER-Factory for automatic construction of multimodal emotion recognition and reasoning datasets.
Jun 01, 2025	One paper about Benchmarking VLLM’s Emotion Interpretation ability is accepted by CVPR Workshop, NeXD (1/3 Oral).
May 01, 2025	Started my internship at Tencent.
Dec 01, 2024	One paper about Multimodal Large Language Model in Emotion Reasoning is accepted by NeurIPS (CCF-A).
Jul 01, 2024	One co-first author paper about invisible gas detection is accepted by CVIU (JCR Q1, CCF-B).
Mar 01, 2024	One paper about Conversational Emotion-Cause Pair Analysis with LLM is accepted by SemEval 2024, NAACL.
Jan 15, 2024	Started my internship at Baidu Inc.
Jan 01, 2024	Awarded the First Prize of Research and Innovation Award (3000 CNY) and Star of Craftsmanship (3000 CNY).
Aug 01, 2023	My instance segmentation tutorial has been featured in MMYOLO v0.6.0 highlight! Check out the tutorial to master the essentials of instance segmentation.
Jul 15, 2023	One paper on multimodal emotion recognition is accepted by ACM MM 2023!
Jul 01, 2023	We are the runner-up in the Grand Challenge (MER 2023) of ACM MM!

selected publications

ArXiv

Why We Feel: Breaking Boundaries in Emotional Reasoning with Multimodal Large Language Models

Yuxiang Lin, Jingdong Sun, Zhi-Qi Cheng, and 7 more authors

arXiv preprint arXiv:2504.07521, 2025

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This paper presents EIBench, a comprehensive benchmark for evaluating Vision-Language Large Models’ ability to interpret and reason about emotions across multiple modalities.
NeurIPS

Emotion-LLaMA: Multimodal Emotion Recognition and Reasoning with Instruction Tuning

Zebang Cheng, Zhi-Qi Cheng, Jun-Yan He, and 5 more authors

In Advances in Neural Information Processing Systems (NeurIPS), 2024

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This paper introduces Emotion-LLaMA, a multimodal large language model for emotion recognition and reasoning with instruction tuning. The model achieves state-of-the-art performance on multiple emotion recognition benchmarks.
CVIU

Invisible Gas Detection: An RGB-Thermal Cross Attention Network and A New Benchmark

Jue Wang, Yuxiang Lin, Qi Zhao, and 4 more authors

Computer Vision and Image Understanding, 2024

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This paper proposes an RGB-Thermal Cross Attention Network (RT-CAN) for invisible gas detection and introduces a new benchmark dataset for this task.