FRESHLATENT: Channel-Aware Latent Adaptation for Resource-Constrained Embodied VLM Perception
Mission-critical UAVs increasingly rely on split vision-language model (VLM) perception under tight onboard-resource and wireless-communication constraints. However, corruption of transmitted intermediate features creates a deployment mismatch for clean-trained split interfaces, while stronger channel-aware codecs can impose substantial onboard cost. We present FreshLatent, a lightweight channel-aware latent adapter that trains a power-normalized encoder-decoder through wireless corruption while keeping the surrounding VLM frozen. We formulate deployment around a mission-conditioned perception requirement and embedded interface cost, linking channel quality and communication budget to the...
| Authors | Rajat Bhattacharjya, Minwoo Kim, Arnab Sarkar et al. |
|---|---|
| Primary category | eess.SP |
| Published | 24 September 2026 |
| Last updated at source | 24 September 2026 |
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