DSIPA is a zero-shot black-box detector that uses sentiment distribution consistency and preservation metrics to identify LLM text, reporting up to 49.89% F1 gains over baselines across domains and models.
A survey on generative AI and LLM for video generation, understanding, and streaming
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DeepFleet develops and compares four foundation model architectures for multi-agent robot fleet coordination using warehouse data, finding robot-centric and graph-floor models most promising for prediction and scaling.
This survey introduces the C5 Interaction Model as a unifying taxonomy to synthesize proactive detection methods for GenAI-enabled adversarial narratives across socio-technical and computational research streams.
The paper surveys the evolution of video trailer generation from extractive heuristics to generative AI methods and proposes a new taxonomy for future systems based on autoregressive and foundation models.
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DeepFleet: Multi-Agent Foundation Models for Mobile Robots
DeepFleet develops and compares four foundation model architectures for multi-agent robot fleet coordination using warehouse data, finding robot-centric and graph-floor models most promising for prediction and scaling.