2 citations · 2 across the 6 of their papers we have counts for
6 papers
Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval
Sachin Yadav, Deepak Saini, Anirudh Buvanesh +6
We develop accurate and efficient solutions for large-scale retrieval tasks where novel (zero-shot) items can arrive continuously at a rapid pace. Conventional Siamese-style approa…
Aligning the Query Space: Greedy Information Projection for Language Model Data Selection
Victor Ye Dong, Kuan-Yun Lee, Jiamei Shuai +3
Data selection for language models is often framed as balancing example quality and diversity. We argue that both are consequences of a more fundamental principle: selected example…
CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks
Bhawna Paliwal, Deepak Saini, Mudit Dhawan +6
Ranking a set of items based on their relevance to a given query is a core problem in search and recommendation. Transformer-based ranking models are the state-of-the-art approache…
On the Necessity of World Knowledge for Mitigating Missing Labels in Extreme Classification
Jatin Prakash, Anirudh Buvanesh, Bishal Santra +6
Extreme Classification (XC) aims to map a query to the most relevant documents from a very large document set. XC algorithms used in real-world applications learn this mapping from…
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…