A blog for MLP. MLP stands for Model, Language and Philosophy, NOT Multi-Layer Perceptron (MLP) 😛
My name is Yisong. I am a junior Ph.D. student studying Natural Language Processing.
Most of my current works study limited datasets (annotated by limited human) in a limited form (mostly tensors) by limited models (mostly invented in the last 5 years).
How do my current works relate to classic math / ML / AI models (perhaps invented 20 years ago)?
How do my current works relate to classic linguistic theory?
How do my current works implicate philosophical views?
I expect an update frequency around once a month.
I have come with the titles for the first few blogs:
One liner summary: A request by Prof Min to present in a future group meeting, so I decide to write up a blog/PDF for clarity. MaxProb describes the confidence of a model in prediction. Tutorial statement: MaxProb is good enough, but it can be better calibrated and adapted.
Status: Done on Nov. 19th 2021 🎉.
Resources:
One liner summary: This is the one million dollar question my advisor asked me during a research meeting. He compared a neural network with a human with autism. He advised me to find smart proxy to measure understanding.
Status: In Progress.
Update: Jan 16th. I will write around the keyword of “decompose”.
Resources:
One liner summary: I am curious!
Status: Not started.
One liner summary: Knowledge base is not my research focus. But the math behind these methods are facinating. So I decide to write up a technical note for clarity.
Status: Not started.
Blog 1: When a junior NLPer reads Ludwig Wittgenstein.
Blog 2: On information bottleneck with my tasks.
Concept Bottleneck Models. ICML ‘20.
Blog 3: On systematic generalization with my tasks (starting from F&P 1988).
While I am busy writing (procrastinating) my future articles, others’ blogs might fill this void:
Blog and technical notes/slides by Xiachong Feng (friend visiting our group).