mlsanityData to 14 Oct 2026

LMC: Large Model Collaboration with Cross-assessment for Training-Free Open-Set Object Recognition

arXiv 2309.12780 ↗First posted 22 Sep 2023cs.CVcited by 10

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Abstract (arXiv)

Open-set object recognition aims to identify if an object is from a class that has been encountered during training or not. To perform open-set object recognition accurately, a key challenge is how to reduce the reliance on spurious-discriminative features. In this paper, motivated by that different large models pre-trained through different paradigms can possess very rich while distinct implicit knowledge, we propose a novel framework named Large Model Collaboration (LMC) to tackle the above challenge via collaborating different off-the-shelf large models in a training-free manner. Moreover, we also incorporate the proposed framework with several novel designs to effectively extract implicit knowledge from large models. Extensive experiments demonstrate the efficacy of our proposed framework. Code is available https://github.com/Harryqu123/LMC

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 58 of its 75 references that are in the map. First posted on arXiv 22 Sep 2023.

Builds on

58 of 75 references.

References · 58

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38 more
  1. 2022Socratic Models: Composing Zero-Shot Multimodal Reasoning with Languagecited by 513
  2. 2023Is ChatGPT a General-Purpose Natural Language Processing Task Solver?cited by 488
  3. 2020Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awarenesscited by 389
  4. 2021Open-Set Recognition: a Good Closed-Set Classifier is All You Need?cited by 353
  5. 2023VideoFusion: Decomposed Diffusion Models for High-Quality Video Generationcited by 331
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  8. 2018Reducing Network Agnostophobiacited by 165
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  10. 2021Adversarial Reciprocal Points Learning for Open Set Recognitioncited by 153
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  12. 2023Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learnerscited by 152
  13. 2018Classification-Reconstruction Learning for Open-Set Recognitioncited by 146
  14. 2019C2AE: Class Conditioned Auto-Encoder for Open-set Recognitioncited by 142
  15. 2021OpenGAN: Open-Set Recognition via Open Data Generationcited by 135
  16. 2018Robust Classification with Convolutional Prototype Learningcited by 123
  17. 2021Learning Placeholders for Open-Set Recognitioncited by 121
  18. 2020Learning Open Set Network with Discriminative Reciprocal Pointscited by 115
  19. 2017DOC: Deep Open Classification of Text Documentscited by 109
  20. 2020Hybrid Models for Open Set Recognitioncited by 109
  21. 2018The Limits and Potentials of Deep Learning for Roboticscited by 104
  22. 2020Conditional Gaussian Distribution Learning for Open Set Recognitioncited by 104
  23. 2022Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wildcited by 70
  24. 2023ViewRefer: Grasp the Multi-view Knowledge for 3D Visual Grounding with GPT and Prototype Guidancecited by 70
  25. 2023C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptationcited by 50
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  27. 2021Modeling Discriminative Representations for Out-of-Domain Detection with Supervised Contrastive Learningcited by 42
  28. 2018Learning a Neural-network-based Representation for Open Set Recognitioncited by 40
  29. 2019Deep Transfer Learning for Multiple Class Novelty Detectioncited by 33
  30. 2021How Transferable Are Self-supervised Features in Medical Image Classification Tasks?cited by 33
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50 most cited of 58 All 58 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 5; 2025: 3; 2026: 1.

10 papers.

  1. 2024LLMs are Good Action Recognizerscited by 37
  2. 2024LTGC: Long-tail Recognition via Leveraging LLMs-driven Generated Contentcited by 33
  3. 2023A Survey on Open-Set Image Recognitioncited by 7
  4. 2025Informative Sample Selection Model for Skeleton-based Action Recognition with Limited Training Samplescited by 4
  5. 2026DiffGraph: An Automated Agent-driven Model Merging Framework for In-the-Wild Text-to-Image Generationcited by 4
  6. 2024GPT-Connect: Interaction between Text-Driven Human Motion Generator and 3D Scenes in a Training-free Mannercited by 3
  7. 2024Off-the-shelf ChatGPT is a Good Few-shot Human Motion Predictorcited by 1
  8. 2024LMSeg: Unleashing the Power of Large-Scale Models for Open-Vocabulary Semantic Segmentationcited by 1
  9. 2025CodeMerge: Codebook-Guided Model Merging for Robust Test-Time Adaptation in Autonomous Drivingcited by 1
  10. 2025Training-Free Label Space Alignment for Universal Domain Adaptationcited by 1