Xinpeng Wang

I am a first-year PhD student at the Munich AI & NLP (MaiNLP) research lab at LMU Munich . My supervisor is Barbara Plank .

Previously, I completed my M.Sc. degree in Robitics, Cognition, Intelligence at Technical University of Munich, where I was a student researcher at Visual Computing & AI lab at TUM working on indoor scene synthesis. I was also a teaching assistant of the course Introduction to Deep Learning (IN2346).

My research interests broadly lie in the field of Deep Learning, Machine Learning, Computer Vision and NLP.

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Research

ACTOR: Active Learning with Annotator-specific Classification Heads to Embrace Human Label Variation

We proposed an active learning framework that utilizes a muli-head model to model individual annotators. We designed different acquisition functions and showed our active learning setup achieved performance comparable to full-scale training while saving up to 70% of the annotation budget.

How to Distill your BERT: An Empirical Study on the Impact of Weight Initialisation and Distillation Objectives

We showed that using lower teacher layers for pre-loading student model gives significant performance improvement compared to higher layers. We also studied the robustness of different distillation objectives under various initialisation choices.

Sceneformer: Indoor Scene Generation with Transformers

We proposed a transformer model for scene generation conditioned on room layout and text description.

Projects

These include coursework and practical course projects.

Domain Specific Multi-Lingually Aligned Word Embeddings

Curiosity Driven Learning

Evaluated and compared the count-based and prediction-based curiosity driven learning on different Atari game environments.

Teaching

Introduction to Deep Learning (IN2346)

Design and source code from Jon Barron's website