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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…