Research map / Label-efficient and robust learning

Test-time adaptation: research map

359 accepted papers on Test-time adaptation in Label-efficient and robust learning, from ICML, NeurIPS, ICLR, CVPR and AAAI (2016–2026), grouped into 2 clusters and 6 approaches. The busiest year so far is 2026.

Within Label-efficient and robust learning, its share grew from 3.8% in 2023–24 to 5.8% in 2025–26 (110 → 176 papers at ICML, NeurIPS, CVPR and AAAI, the venues with data for all four years).

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Approaches and key papers

Related topics in Label-efficient and robust learning

• Noisy labels (462)
• Zero-/few-shot and meta-learning (784)
• OOD and anomaly detection (614)
• Recognition and long-tail (4,953)
• Semi-supervised learning (623)
• Self-supervised and contrastive (988)
• Domain adaptation and generalization (1,330)
• Knowledge distillation (544)