InfoNCE softmax misaligned with normalized embeddings per extreme value theory; WEINCE adds batch-based endpoint shortfall correction for consistent gains on five vision benchmarks.
arXiv preprint arXiv:2501.17683 (2025)
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
MaCo-GAN introduces a manifold-contrastive GAN that replaces adversarial loss with a contrastive minimax game over synthesized fake samples to improve the perception-distortion trade-off in SISR.
citing papers explorer
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When Softmax Fails at the Top: Extreme Value Corrections for InfoNCE
InfoNCE softmax misaligned with normalized embeddings per extreme value theory; WEINCE adds batch-based endpoint shortfall correction for consistent gains on five vision benchmarks.
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MaCo-GAN: Manifold-Contrastive Adversarial Learning for Single Image Super-Resolution
MaCo-GAN introduces a manifold-contrastive GAN that replaces adversarial loss with a contrastive minimax game over synthesized fake samples to improve the perception-distortion trade-off in SISR.