4 papers · 1 filter
Beyond Static RAG: An Adaptive, Tri-Metric Routing Framework for Efficient Long-Context Inference on Commodity GPUs
Saipraveen Vabbilisetty, Ajay Kumar Boddepalli, Deep Narayan Mishra +3
Deploying retrieval-augmented generation (RAG) on commodity GPUs such as the NVIDIA T4 (16 GB VRAM) exposes a practical failure mode we call the Compression Paradox: neural prompt…
Demand Transfer Estimation at Scale via Restricted Logit Modeling
Lakshya Garg, Deep Narayan Mishra, Swapnil Yadav +4
Item demand forecasting is an integral component of store assortment optimization. Existing literature focuses on learning a suitable customer choice model and using this model to…
LEAP: Layer-wise Exit-Aware Pretraining for Efficient Transformer Inference
Shashank Kapadia, Deep Naryan Mishra, Sujal Reddy Alugubelli +4
Layer-aligned distillation and convergence-based early exit represent two predominant computational efficiency paradigms for transformer inference; yet we establish that they exhib…
Monodense Deep Neural Model for Determining Item Price Elasticity
Lakshya Garg, Sai Yaswanth, Deep Narayan Mishra +3
Item Price Elasticity is used to quantify the responsiveness of consumer demand to changes in item prices, enabling businesses to create pricing strategies and optimize revenue man…