80 citations · 110 across the 6 of their papers we have counts for
6 papers
Investigating the Robustness of Subtask Distillation under Spurious Correlation
Pattarawat Chormai, Klaus-Robert Müller, Grégoire Montavon
Subtask distillation is an emerging paradigm in which compact, specialized models are extracted from large, general-purpose 'foundation models' for deployment in environments with…
Distilling Lightweight Domain Experts from Large ML Models by Identifying Relevant Subspaces
Pattarawat Chormai, Ali Hashemi, Klaus-Robert Müller +1
Knowledge distillation involves transferring the predictive capabilities of large, high-performing AI models (teachers) to smaller models (students) that can operate in environment…
PyThaiNLP: Thai Natural Language Processing in Python
Wannaphong Phatthiyaphaibun, Korakot Chaovavanich, Charin Polpanumas +6
We present PyThaiNLP, a free and open-source natural language processing (NLP) library for Thai language implemented in Python. It provides a wide range of software, models, and da…
Towards Fixing Clever-Hans Predictors with Counterfactual Knowledge Distillation
Sidney Bender, Christopher J. Anders, Pattarawatt Chormai +3
This paper introduces a novel technique called counterfactual knowledge distillation (CFKD) to detect and remove reliance on confounders in deep learning models with the help of hu…
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces
Pattarawat Chormai, Jan Herrmann, Klaus-Robert Müller +1
Explainable AI aims to overcome the black-box nature of complex ML models like neural networks by generating explanations for their predictions. Explanations often take the form of…
AttaCut: A Fast and Accurate Neural Thai Word Segmenter
Pattarawat Chormai, Ponrawee Prasertsom, Attapol Rutherford
Word segmentation is a fundamental pre-processing step for Thai Natural Language Processing. The current off-the-shelf solutions are not benchmarked consistently, so it is difficul…