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Deep Embedding of Conversation Segments
Conversation embeddings obtained in this fashion are applied to (a) conversation clustering, (b) conversation classification and (c) as a context for automated conversation generation on new datasets (unseen by the pre-training model).
DetoxBench: Benchmarking Large Language Models for Multitask Fraud & Abuse Detection
Our benchmark encompasses a diverse set of tasks, including detecting spam emails, hate speech, misogynistic language, and more.
MARec: Metadata Alignment for cold-start Recommendation
For many recommender systems, the primary data source is a historical record of user clicks.
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