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The study of the Generalized Turing Test is initiated, a formal generalization of Turing's imitation game from humans to arbitrary interactive agents, yielding an inherently adaptive form of evaluation that does not rely on fixed benchmarks.
A benchmark in which a model progressively solves a Boolean circuit over $GF(2)$ from data is introduced, isolating OOD reasoning from these confounding factors, and general, as any computable function can be represented as a sufficiently large $GF(2)$ polynomial.
This work introduces and studies hyper-kernel ridge regression (HKRR), an approach blending neural networks and kernel methods, and exploits the kernel nature of the estimator to develop ad hoc optimization approaches.
It is shown that a symmetry fixes what variables are: a network layer is a sum over interchangeable units, so relabeling the units leaves it unchanged; given smoothness and the condition that a unit's gradient vanish at the origin, symmetry then enforces a universal leading form for the expansion about the near-zero we...
Cross-Modal Alignment Regularization (CMAR) is proposed, a method designed to improve LLMs by aligning their internal representations with those of vision models during training by bringing the internal representations of the language and vision models closer together.
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