Creates the BGTD benchmark and mmTraffic architecture to enable explainable multimodal interpretation of encrypted network traffic using LLMs.
Trafficllm: Enhancing large language models for network traffic analysis with generic traffic representation
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
TraceCodec is a compiler-backed neural codec that lifts packets to state-aware action latents for high-fidelity multi-flow trace generation, matching real traces within 0.03% on CICIDS2017.
ReasonLight uses multimodal foundation models to refine RL-proposed traffic signal phases based on camera images and sensor data, enabling zero-shot adaptation to unseen events such as emergency vehicle priority.
citing papers explorer
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TraceCodec: A Compiler-Backed Neural Codec for Stateful Multi-Flow Network Traffic Traces
TraceCodec is a compiler-backed neural codec that lifts packets to state-aware action latents for high-fidelity multi-flow trace generation, matching real traces within 0.03% on CICIDS2017.