Author

Deep Naryan Mishra

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Preprint Aug 2026

Demand Transfer Estimation at Scale via Restricted Logit Modeling

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 determine the value of an objective function (i.e. expected demand) with respect to an assortment proposal. However, for large item universe...

Lakshya Garg, Deep Naryan Mishra, Swapnil Yadav et al. · 0 citations

#machine learning Preprint Jul 2026

Beyond Static RAG: An Adaptive, Tri-Metric Routing Framework for Efficient Long-Context Inference on Commodity GPUs

The Tri-Metric Router is introduced, a deterministic, training-free policy that selects among Raw, Neural, and Lexical pipelines and achieves 0% OOM failures, on out-of-distribution holdouts, and improves over always-on lexical compression by 5.2 points without additional VRAM or training cost.

Saipraveen Vabbilisetty, Ajay Kumar Boddepalli, Deep Naryan Mishra et al. · 0 citations

Preprint Aug 2026

Lines and Ladders: A Context-Aware Multi-Agent Framework for Large-Scale Retail Price Taxonomy

A scalable, context-aware Multi-Agent Framework designed to automate the construction of "Lines and Ladders" pricing taxonomies, which achieves 90% precision and 75% recall in Food&Consumables, and 80.2% assignment accuracy in the unstructured General Merchandise catalog.

Ravi Teja Chunduri, Srikaran Reddy Boya, Deep Naryan Mishra et al. · 0 citations