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Text revision has become an integral component of large language models. This paper formulates revision such that it admits a Nash equilibrium: Token positions are players, vocabulary items are actions, and each player's utility is the language model's log conditional probability. We motivate the revision by showing th...
USteer, a simple, training-free steering mechanism that adjusts a model's layer-wise activations during inference using the gradient of a confidence measure with respect to the activations, demonstrates that confidence signals can be leveraged not only for detection, but also for effective inference-time control of mod...
It is proved that in-context learning extends further to data generation: frozen transformers can simulate iterative generative samplers from in-context samples, and it is proved that transformers can approximate an energy-based sampler.
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