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Author: JingfengYang

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         <p> Before the era of LLMs, I studied Natural Language Processing <a href="https://zhuanlan.zhihu.com/p/539706909" style="color:#4133ff;">[Blog: NLP Trends from the perspective of LLM, i.e. summary of ACL 2022 (in Chinese)]</a>, Machine Learning, and large-scale pretraining of unified multimodal, multitask, multilingual Transformer models [<a href="https://github.com/JingfengYang/Multi-modal-Deep-Learning" style="color:#4133ff;">Repo: Paper List of Multi-modal Deep Learning</a>].</p>
 
         <p> My previous work on semantic parsing, compositional generalization, text generation, code generation, multilinguality and multi-modality makes me particularly interested in langauge agents, reasoning and grounding. </p>
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-        <p> Our Amazon Team also has research intern / fulltime oppenings in Generative AI. If you are interested, shoot me an email. </p>
 
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         <p> Before the era of LLMs, I studied Natural Language Processing <a href="https://zhuanlan.zhihu.com/p/539706909" style="color:#4133ff;">[Blog: NLP Trends from the perspective of LLM, i.e. summary of ACL 2022 (in Chinese)]</a>, Machine Learning, and large-scale pretraining of unified multimodal, multitask, multilingual Transformer models [<a href="https://github.com/JingfengYang/Multi-modal-Deep-Learning" style="color:#4133ff;">Repo: Paper List of Multi-modal Deep Learning</a>].</p>
 
         <p> My previous work on semantic parsing, compositional generalization, text generation, code generation, multilinguality and multi-modality makes me particularly interested in langauge agents, reasoning and grounding. </p>
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-        <p> Our Amazon Team also has research intern / fulltime oppenings in Generative AI. If you are interested, shoot me an email. </p>
 
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     <a name="news"></a>
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