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FastVLM: Self-Speculative Decoding for Fast Vision-Language Model Inference
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Vision-language Models (VLMs) have made significant strides in visual understanding and query response generation, but often face challenges of high computational cost and inferenc…
Beyond Greedy Exits: Improved Early Exit Decisions for Risk Control and Reliability
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Early-Exit Deep Neural Networks enable adaptive inference by allowing prediction at intermediary layers, significantly reducing computational costs and latency. Most of the early e…
Know What You Don't Know: Selective Prediction for Early Exit DNNs
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Inference latency and trustworthiness of Deep Neural Networks (DNNs) are the bottlenecks in deploying them in critical applications like sensitive tasks. Early Exit (EE) DNNs overc…
FREE: Fast and Robust Vision Language Models with Early Exits
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
In recent years, Vision-Language Models (VLMs) have shown remarkable performance improvements in Vision-Language tasks. However, their large size poses challenges for real-world ap…
BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Early Exit (EE) techniques have emerged as a means to reduce inference latency in Deep Neural Networks (DNNs). The latency improvement and accuracy in these techniques crucially de…
A Survey of Early Exit Deep Neural Networks in NLP
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Deep Neural Networks (DNNs) have grown increasingly large in size to achieve state of the art performance across a wide range of tasks. However, their high computational requiremen…