Reported interview periodNov 2025–May 2026
Mine Novel Examples from an Unlabeled Corpus
Design a pipeline that selects rare, useful, and diverse examples from a very large unlabeled text corpus for human labeling.
Practice focusRequirements - Define the downstream task, novelty target, labeling budget, and what counts as success. - Remove unsafe, low-quality, duplicate, and near-duplicate content while tracking provenance. - Represent examples for semantic retrieval and compare distance-to-labeled-data, density, uncertainty, and rule-based signals. - Balance novelty against diversity and relevance so annotators are not flooded with one unusual cluster. - Build a review workflow with sampling, auditability, and feedback from annotators.…