1 citations · 1 across the 8 of their papers we have counts for
8 papers
Transferable Dual-Stream Representations for Mesoscale-Preserving Sea Surface Temperature Downscaling
Parth Doshi, Priyanka Aravindan, Vaishnav Vaidheeswaran +2
Deep learning models for scientific spatio-temporal downscaling often minimize reconstruction error while failing to preserve physically meaningful multi-scale structure. For sea s…
20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone
DatologyAI, :, Siddharth Joshi +32
Data curation has shifted the quality-compute frontier for language-model and contrastive image-text pretraining, but its role for vision-language models (VLMs) is far less establi…
The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data
Christina Baek, Ricardo Pio Monti, David Schwab +31
Real-world model deployments demand strong performance on narrow domains where data is often scarce. Typically, practitioners finetune models to specialize them, but this risks ove…
ÜberWeb: Insights from Multilingual Curation for a 20-Trillion-Token Dataset
DatologyAI, :, Aldo Gael Carranza +32
Multilinguality is a core capability for modern foundation models, yet training high-quality multilingual models remains challenging due to uneven data availability across language…
DatBench: Discriminative, Faithful, and Efficient VLM Evaluations
DatologyAI, :, Siddharth Joshi +30
Empirical evaluation serves as the primary compass guiding research progress in foundation models. Despite a large body of work focused on training frontier vision-language models…
Luxical: High-Speed Lexical-Dense Text Embeddings
DatologyAI, :, Luke Merrick +31
Frontier language model quality increasingly hinges on our ability to organize web-scale text corpora for training. Today's dominant tools trade off speed and flexibility: lexical…
BeyondWeb: Lessons from Scaling Synthetic Data for Trillion-scale Pretraining
DatologyAI, :, Pratyush Maini +28
Recent advances in large language model (LLM) pretraining have shown that simply scaling data quantity eventually leads to diminishing returns, hitting a data wall. In response, th…
OSM vs HD Maps: Map Representations for Trajectory Prediction
Jing-Yan Liao, Parth Doshi, Zihan Zhang +2
While High Definition (HD) Maps have long been favored for their precise depictions of static road elements, their accessibility constraints and susceptibility to rapid environment…