mlsanityData to 7 Oct 2026

Challenges in Representation Learning: A report on three machine learning contests

arXiv 1307.0414 ↗First posted 1 Jul 2013stat.ML cs.LGcited by 301

Not on the map. Why?

Abstract (arXiv)

The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge. We describe the datasets created for these challenges and summarize the results of the competitions. We provide suggestions for organizers of future challenges and some comments on what kind of knowledge can be gained from machine learning competitions.

Key facts. Cited by 301 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Jul 2013.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 45; 2022: 44; 2023: 47; 2024: 51; 2025: 57; 2026: 57.

301 papers.

Sort:

By area:

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2023InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Taskscited by 2,534
  3. 2023Vision-Language Models for Vision Tasks: A Surveycited by 834
  4. 2023EVA-CLIP: Improved Training Techniques for CLIP at Scalecited by 786
  5. 2021SLIP: Self-supervision meets Language-Image Pre-trainingcited by 434
  6. 2023EVA-02: A Visual Representation for Neon Genesiscited by 377
  7. 2024Task Singular Vectors: Reducing Task Interference in Model Mergingcited by 143
  8. 2024Localizing Task Information for Improved Model Merging and Compressioncited by 130
  9. 2024EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameterscited by 99
  10. 2025No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspacescited by 90
  11. 2021Dive into Ambiguity: Latent Distribution Mining and Pairwise Uncertainty Estimation for Facial Expression Recognitioncited by 89
  12. 2021CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIPcited by 88
38 more
  1. 2022A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglementcited by 87
  2. 2021TransFER: Learning Relation-aware Facial Expression Representations with Transformerscited by 85
  3. 2022AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilitiescited by 84
  4. 2022Parameter-efficient Model Adaptation for Vision Transformerscited by 81
  5. 2023EmoSet: A Large-scale Visual Emotion Dataset with Rich Attributescited by 81
  6. 2022Learn From All: Erasing Attention Consistency for Noisy Label Facial Expression Recognitioncited by 67
  7. 2022POSTER: A Pyramid Cross-Fusion Transformer Network for Facial Expression Recognitioncited by 49
  8. 2022Learning Generalizable Dexterous Manipulation from Human Grasp Affordancecited by 46
  9. 2021Deep Learning for Micro-expression Recognition: A Surveycited by 43
  10. 2025AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Modelscited by 43
  11. 2024LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Mergingcited by 39
  12. 2023GPT-4V with Emotion: A Zero-shot Benchmark for Generalized Emotion Recognitioncited by 38
  13. 2024Diffusion Feedback Helps CLIP See Bettercited by 37
  14. 2022Vision Transformer with Attentive Pooling for Robust Facial Expression Recognitioncited by 35
  15. 2021Py-Feat: Python Facial Expression Analysis Toolboxcited by 33
  16. 2021INTERN: A New Learning Paradigm Towards General Visioncited by 33
  17. 2023MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learningcited by 33
  18. 2024What Do VLMs NOTICE? A Mechanistic Interpretability Pipeline for Gaussian-Noise-free Text-Image Corruption and Evaluationcited by 29
  19. 2023The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learningcited by 27
  20. 2021Stimuli-Aware Visual Emotion Analysiscited by 26
  21. 2024Facial Affective Behavior Analysis with Instruction Tuningcited by 26
  22. 2021V2C: Visual Voice Cloningcited by 23
  23. 2024HEMM: Holistic Evaluation of Multimodal Foundation Modelscited by 21
  24. 2021Facial Emotion Recognition: State of the Art Performance on FER2013cited by 20
  25. 2021Learning Facial Representations from the Cycle-consistency of Facecited by 20
  26. 2024FindingEmo: An Image Dataset for Emotion Recognition in the Wildcited by 20
  27. 2023LA-Net: Landmark-Aware Learning for Reliable Facial Expression Recognition under Label Noisecited by 17
  28. 2023Hydra: Multi-head Low-rank Adaptation for Parameter Efficient Fine-tuningcited by 17
  29. 2023Leave No Stone Unturned: Mine Extra Knowledge for Imbalanced Facial Expression Recognitioncited by 17
  30. 2024Self-Supervised Facial Representation Learning with Facial Region Awarenesscited by 17
  31. 2022Pose-disentangled Contrastive Learning for Self-supervised Facial Representationcited by 16
  32. 2023Weakly-Supervised Text-driven Contrastive Learning for Facial Behavior Understandingcited by 16
  33. 2023Unleashing Mask: Explore the Intrinsic Out-of-Distribution Detection Capabilitycited by 16
  34. 2024Cross-Task Multi-Branch Vision Transformer for Facial Expression and Mask Wearing Classificationcited by 16
  35. 2021Graph-based Facial Affect Analysis: A Reviewcited by 14
  36. 2024Let Go of Your Labels with Unsupervised Transfercited by 14
  37. 2024Multi-label Cluster Discrimination for Visual Representation Learningcited by 14
  38. 2025MINGLE: Mixture of Null-Space Gated Low-Rank Experts for Test-Time Continual Model Mergingcited by 14

50 most cited of 301 All 301 (JSON)