Here are some books I found interesting in 2021.
- 西方现代思想讲义（刘擎）
- Capital and Ideology (Piketty)
- Keep Sharp: Build a Better Brain at Any Age (Gupta)
- The Nature of Expertise (Chi etal)
Quantifying the Task-Specific Information in Text-Based Classifications
In this paper, we estimate the task-specific information in text-based classification datasets.
An unsupervised framework for tracing textual sources of moral change
In this paper, we propose an unsupervised framework that infers the source text with prominent influence on the moral time course.
What do writing features tell us about AI papers?
This paper studies the writing features and their indications towards conference / workshop appearances in AI venues.
How is BERT surprised? Layerwise detection of linguistic anomalies
This paper uses Gaussian mixture model to detect how contextualized LMs show surprisal given different types of anomalies.
Interpretable NLP 2021 winter
In winter 2021, we ran a seminar discussing interesting papers related to interpretability in NLP. Here are the list of topics, with links to slides. This is the first iteration; I expect there will be a refined version in the future.
Cool Books in 2020
Here are some books I found interesting in 2020.
- Principles (Ray Dalio)
- Good work if you can get it (Jason Brennan)
- Kochland (Christopher Leonard)
- Daniels’ Running Formula (Jack Daniels)
Examining the rhetorical capacities of neural language models
This paper just got accepted to EMNLP 2020 BlackboxNLP Workshop.
Here is a 10-min video to explain the main contents.
An information theoretic view on selecting linguistic probes
This paper just got accepted to EMNLP 2020 as a short paper (acceptance rate 16.7% — a record low)
Here is a 10-min video to explain the main contents.