Engineer. Builder. ICCCNet 2026 - Optimizing Vision Encoders for Edge-Deployed Visual LLMs.
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Optimizing Vision Encoders for Edge-Deployed Visual LLMs ICCCNet 2026 | Peer-reviewed publication
- Benchmarked 8 architectures across 4 hardware platforms; TTFT ranging from 1.6ms to 98.0ms on identical hardware
- Identified vision encoders as the 70-85% latency bottleneck in edge VLLM deployments
- Introduced the Cache Cliff phenomenon and Sensory Bottleneck Hypothesis




