Aug 24, 2023 · In this paper, we aim at a more challenging setting, Realistic Zero-Shot Classification, which assumes no annotation but instead a broad vocabulary.
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We propose a Self Structural Semantic Alignment (S 3 A ) framework, to address the challenging Realistic Zero-Shot Classification problem.
To address the new problem, we propose the Self Structural Semantic Alignment (S 3A) framework, which extracts the structural semantic information from ...
Oct 9, 2024 · In this paper, we aim at a more challenging setting, Realistic Zero-Shot Classification, which assumes no annotation but instead a broad ...
Feb 23, 2024 · S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment ... to Bedside' by Nobel prize laureates Richard ...
S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment. Proceedings of the AAAI Conference on Artificial Intelligence, 38(7) ...
Latest. S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment. Published with Wowchemy — the free, open source website ...
Towards realistic zero-shot classification via self structural semantic alignment. S Zhang, M Naseer, G Chen, Z Shen, S Khan, K Zhang, F Khan. arXiv preprint ...
S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment · PromptCAL: Contrastive Affinity Learning via Auxiliary Prompts for ...
S. Zhang, “S3A: Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment”, AAAI, vol. 38, no. 7, pp. 7278-7286, Mar. 2024.