5arXiv cs.CL (Computation and Language)·
GTCL: Latent trajectory discrimination framework for AI-generated text detection
A new arXiv preprint proposes Geometric Trajectory and Contrastive Learning (GTCL), a framework that reframes AI-generated text detection as a problem of distinguishing latent generation trajectories rather than treating documents as static objects. The method segments documents into ordered local units, encodes them in embedding space, and applies contrastive learning to capture geometric regularities of autoregressive generation. GTCL is evaluated on three benchmarks and consistently outperforms detection baselines, suggesting that modeling sequential dynamics provides more robust discriminative signals than aggregate statistics or global embeddings.
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