TwinGate deploys a stateful dual-encoder system with asymmetric contrastive learning to detect decompositional jailbreaks in untraceable LLM traffic at high recall and low false-positive rate with negligible latency.
InAdvances in Neural Information Process- ing Systems (NeurIPS)
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The paper supplies a unified definition based on data flow and dynamic interaction plus a systematic taxonomy to organize fragmented work on streaming large language models.
citing papers explorer
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TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning
TwinGate deploys a stateful dual-encoder system with asymmetric contrastive learning to detect decompositional jailbreaks in untraceable LLM traffic at high recall and low false-positive rate with negligible latency.
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From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models
The paper supplies a unified definition based on data flow and dynamic interaction plus a systematic taxonomy to organize fragmented work on streaming large language models.