mlsanityData to 14 Oct 2026

LAMDA-SSL: Semi-Supervised Learning in Python

arXiv 2208.04610 ↗First posted 9 Aug 2022cs.LGcited by 5

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Abstract (arXiv)

LAMDA-SSL is open-sourced on GitHub and its detailed usage documentation is available at https://ygzwqzd.github.io/LAMDA-SSL/. This documentation introduces LAMDA-SSL in detail from various aspects and can be divided into four parts. The first part introduces the design idea, features and functions of LAMDA-SSL. The second part shows the usage of LAMDA-SSL by abundant examples in detail. The third part introduces all algorithms implemented by LAMDA-SSL to help users quickly understand and choose SSL algorithms. The fourth part shows the APIs of LAMDA-SSL. This detailed documentation greatly reduces the cost of familiarizing users with LAMDA-SSL toolkit and SSL algorithms.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 2 of its 9 references that are in the map. First posted on arXiv 9 Aug 2022.

Builds on

2 of 9 references.

References · 2

  1. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,305
  2. 2022Open-environment Machine Learningcited by 48

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Cited by year

Citing papers per year: 2023: 1; 2024: 3; 2025: 1.

5 papers.

  1. 2023Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurtscited by 58
  2. 2024DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detectioncited by 14
  3. 2024Robust Semi-Supervised Learning in Open Environmentscited by 8
  4. 2024Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classificationcited by 1
  5. 2025ModSSC: A Modular Framework for Semi-Supervised Classification on Heterogeneous Datacited by 0