9 citations · 9 across the 7 of their papers we have counts for
7 papers
Towards a Reliable and Practical Eval Pipeline
Emma Thuong Nguyen, Abhishek Ghose
LLM-based software systems increasingly require effective "evals" as quality gates in the development lifecycle. However, existing work typically addresses individual aspects of ev…
On the Fragility of Active Learners for Text Classification
Abhishek Ghose, Emma Thuong Nguyen
Active learning (AL) techniques optimally utilize a labeling budget by iteratively selecting instances that are most valuable for learning. However, they lack ``prerequisite checks…
Are Good Explainers Secretly Human-in-the-Loop Active Learners?
Emma Thuong Nguyen, Abhishek Ghose
Explainable AI (XAI) techniques have become popular for multiple use-cases in the past few years. Here we consider its use in studying model predictions to gather additional traini…
Data Selection: A General Principle for Building Small Interpretable Models
Abhishek Ghose
We present convincing empirical evidence for an effective and general strategy for building accurate small models. Such models are attractive for interpretability and also find use…
Rational Kernels: A survey
Abhishek Ghose
Many kinds of data are naturally amenable to being treated as sequences. An example is text data, where a text may be seen as a sequence of words. Another example is clickstream da…
Learning Interpretable Models Using Uncertainty Oracles
Abhishek Ghose, Balaraman Ravindran
A desirable property of interpretable models is small size, so that they are easily understandable by humans. This leads to the following challenges: (a) small sizes typically impl…
Interpretability with Accurate Small Models
Abhishek Ghose, Balaraman Ravindran
Models often need to be constrained to a certain size for them to be considered interpretable. For example, a decision tree of depth 5 is much easier to understand than one of dept…