CAMF uses collaborating and adversarial LLM agents to extract linguistic features, probe consistency, and aggregate judgments, claiming state-of-the-art zero-shot machine-text detection.
Homogeneous isosceles-free spaces
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abstract
We study homogeneity aspects of metric spaces in which all triples of distinct points admit pairwise different distances; such spaces are called isosceles-free. In particular, we characterize all homogeneous isosceles-free spaces up to isometry as vector spaces over the two-element field, endowed with an injective norm. Using isosceles-free decompositions, we provide bounds on the maximal number of distances in arbitrary homogeneous finite metric spaces.
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cs.CL 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
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CAMF: Collaborative Adversarial Multi-agent Framework for Machine Generated Text Detection
CAMF uses collaborating and adversarial LLM agents to extract linguistic features, probe consistency, and aggregate judgments, claiming state-of-the-art zero-shot machine-text detection.