1 citations · 1 across the 7 of their papers we have counts for
8 papers
Softmax Reparameterization for Output-Head Quantization
Asim Kadav, Christian Flores, Chirag Arora +5
Large vocabularies make output heads a substantial inference cost in small language models. We introduce softmax reparameterization, a post-training method that searches over funct…
Localization Boosting for Growth Markets: Mitigating Cross-Locale Behavioral Bias in Learning-to-Rank
Suryaa Veerabathiran Seran, Ashwin Naresh Kumar, Tracy Holloway King +1
Adobe Express is expanding internationally, but the US has a disproportionately large content supply and interaction volume. Learning-to-rank (LTR) models trained primarily on beha…
Text Style Transfer with Machine Translation for Graphic Designs
Deergh Singh Budhauria, Sanyam Jain, Rishav Agarwal +1
Globalization of graphic designs such as those used in marketing materials and magazines is increasingly important for communication to broad audiences. To accomplish this, the tex…
Spike Hijacking in Late-Interaction Retrieval
Karthik Suresh, Tushar Vatsa, Tracy King +2
Late-interaction retrieval models rely on hard maximum similarity (MaxSim) to aggregate token-level similarities. Although effective, this winner-take-all pooling rule may structur…
Scaling Multimodal Search and Recommendation with Small Language Models via Upside-Down Reinforcement Learning
Yu-Chen Lin, Sanat Sharma, Hari Manikandan +3
In this work, we investigate how small language models (SLMs) can be scaled to support multimodal search and recommendation use cases while remaining efficient enough for real-time…
Smart Multi-Modal Search: Contextual Sparse and Dense Embedding Integration in Adobe Express
Cherag Aroraa, Tracy Holloway King, Jayant Kumar +6
As user content and queries become increasingly multi-modal, the need for effective multi-modal search systems has grown. Traditional search systems often rely on textual and metad…
Semantic In-Domain Product Identification for Search Queries
Sanat Sharma, Jayant Kumar, Twisha Naik +3
Accurate explicit and implicit product identification in search queries is critical for enhancing user experiences, especially at a company like Adobe which has over 50 products an…
Augmenting Knowledge Graph Hierarchies Using Neural Transformers
Sanat Sharma, Mayank Poddar, Jayant Kumar +2
Knowledge graphs are useful tools to organize, recommend and sort data. Hierarchies in knowledge graphs provide significant benefit in improving understanding and compartmentalizat…