Large language models (LLMs) have demonstrated strong capabilities in recommendation tasks such as item, sequence, conversational recommendation, and explanation generation. However, LLM weights are typically shared across all users. Adapting these models to individual users remains a fundamental challenge that require...
Kanishka Dandeniya, C. Dasanayaka, Daswin de Silva et al.· Proceedings of the 20th ACM...· 0 citations
Owing to their simplicity, minimalistic design, and computational efficiency, MMPerc classifiers are promising candidates for conventional machine learning tasks, linear evaluation of deep neural networks, integration with hyperdimensional computing and vector symbolic architecture representations, and deployment in re...
D. Rachkovskij, Evgeny Osipov, O. Volkov et al.· Neural Computation· 0 citations
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