4 papers
HARNESS-LM: A Three-Phase Training Recipe for Harnessing SLMs in Sponsored Search Retrieval
Vipul Gupta, Shikhar Mohan, Lakshya Kumar +4
In the competitive landscape of sponsored search, balancing retrieval quality with production latency is a critical challenge. While large retrieval models based on Small Language…
Improving Retrieval in Sponsored Search by Leveraging Query Context Signals
Akash Kumar Mohankumar, Gururaj K, Gagan Madan +1
Accurately retrieving relevant bid keywords for user queries is critical in Sponsored Search but remains challenging, particularly for short, ambiguous queries. Existing dense and…
Scaling the Vocabulary of Non-autoregressive Models for Efficient Generative Retrieval
Ravisri Valluri, Akash Kumar Mohankumar, Kushal Dave +4
Generative Retrieval introduces a new approach to Information Retrieval by reframing it as a constrained generation task, leveraging recent advancements in Autoregressive (AR) lang…
Graph Regularized Encoder Training for Extreme Classification
Anshul Mittal, Shikhar Mohan, Deepak Saini +10
Deep extreme classification (XC) aims to train an encoder architecture and an accompanying classifier architecture to tag a data point with the most relevant subset of labels from…