5 citations · 6 across the 6 of their papers we have counts for
6 papers
Mercury: Ultra-Fast Language Models Based on Diffusion
Inception Labs, Samar Khanna, Siddhant Kharbanda +10
We present Mercury, a new generation of commercial-scale large language models (LLMs) based on diffusion. These models are parameterized via the Transformer architecture and traine…
Learning label-label correlations in Extreme Multi-label Classification via Label Features
Siddhant Kharbanda, Devaansh Gupta, Erik Schultheis +3
Extreme Multi-label Text Classification (XMC) involves learning a classifier that can assign an input with a subset of most relevant labels from millions of label choices. Recent w…
UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification
Siddhant Kharbanda, Devaansh Gupta, Gururaj K +4
Extreme Multi-label Classification (XMC) involves predicting a subset of relevant labels from an extremely large label space, given an input query and labels with textual features.…
CLIPTrans: Transferring Visual Knowledge with Pre-trained Models for Multimodal Machine Translation
Devaansh Gupta, Siddhant Kharbanda, Jiawei Zhou +3
There has been a growing interest in developing multimodal machine translation (MMT) systems that enhance neural machine translation (NMT) with visual knowledge. This problem setup…
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification
Siddhant Kharbanda, Atmadeep Banerjee, Erik Schultheis +1
Extreme Multi-label Text Classification (XMC) involves learning a classifier that can assign an input with a subset of most relevant labels from millions of label choices. Recent a…
InceptionXML: A Lightweight Framework with Synchronized Negative Sampling for Short Text Extreme Classification
Siddhant Kharbanda, Atmadeep Banerjee, Devaansh Gupta +2
Automatic annotation of short-text data to a large number of target labels, referred to as Short Text Extreme Classification, has found numerous applications including prediction o…