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🎓 Currently pursuing a PhD inVisual Perception and Reasoning.

🔍 My research interests revolve aroundVision-Language Models 🧠,Embodied Agents 🤖, andScene Graph Generation 🕸. I am passionate about creating generalist AI models capable of understanding and interacting with complex visual data.

• Visual Generalist Models: Developing models that process diverse visual data (e.g., images, videos, 3D, audio, IMU) to tackle various tasks in perception, reasoning, generation, robotics, and gaming. Notable projects includeEgoLife,Octopus,FunQA, andOtter.

• AI Safety for Foundation Models: Investigating how to mitigate hallucinations in large language models (LLMs) and multimodal models (LMMs). A key contribution is the introduction ofUPD to withhold answers when faced with unsolvable questions.

• PSG Series (2022-2023): Led the development of thePSG,PVSG, andPSG4D models, focusing on relation modeling for scene understanding. I also collaborated on works likeRelate-Anything andPairNet.

• OOD Detection (2021-2022): Led a comprehensivesurvey and developedOpenOOD, a popular codebase for Out-of-Distribution detection in AI safety.

• Prompt Tuning (2022): Contributed to foundational works likeCoOp andCoCoOp for prompt tuning in vision-language models.

• Email:yangjingkang001@gmail.com
• LinkedIn:Jingkang Yang
• Twitter:@JingkangY

Feel free to reach out for collaboration or just to chat about AI and technology!

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