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Ashish Mishra

3 accepted papers

2026

Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer

ICML 2026poster

AI applications have shifted from single, mono-lithic foundation models (FM) to compound agentic systems. Yet today’s stacks remain fragmented: even as protocols (e.g., MCP, A2A) ease tool/agent connectivity, each framework embeds an implicit runtime for state, memory, budgets, and guardrails, makin…

Cited by 0Source ↗Scholar ↗
2018

A Zero-Shot Framework for Sketch based Image Retrieval

ECCV 2018poster

Sketch-based image retrieval (SBIR) is the task of retrieving images from a natural image database that correspond to a given hand-drawn sketch. Ideally, an SBIR model should learn to associate components in the sketch (say, feet, tail, etc.) with the corresponding components in the image. However,…

Cited by 220Source ↗PDF ↗Scholar ↗
2018

Generalized Zero-Shot Learning via Synthesized Examples

CVPR 2018poster

We present a generative framework for generalized zero-shot learning where the training and test classes are not necessarily disjoint. Built upon a variational autoencoder based architecture, consisting of a probabilistic encoder and a probabilistic emph{conditional} decoder, our model can generate…

Cited by 495Source ↗PDF ↗Scholar ↗