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Been Kim

Identifiers

  • name variant Been Kim 0.60 · backfill

Papers (23)

  1. Video models are zero-shot learners and reasoners cs.LG · 2025 · author #7
  2. Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities cs.CL · 2025 · author #1179
  3. Escaping Plato's Cave: JAM for Aligning Independently Trained Vision and Language Models cs.LG · 2025 · author #3
  4. Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems cs.LG · 2019 · author #4
  5. Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making cs.HC · 2019 · author #5
  6. Interpreting Black Box Predictions using Fisher Kernels cs.LG · 2018 · author #2
  7. Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values cs.CV · 2018 · author #4
  8. Proceedings of the 2018 ICML Workshop on Human Interpretability in Machine Learning (WHI 2018) stat.ML · 2018 · author #1
  9. xGEMs: Generating Examplars to Explain Black-Box Models cs.LG · 2018 · author #3
  10. To Trust Or Not To Trust A Classifier stat.ML · 2018 · author #2
  11. Human-in-the-Loop Interpretability Prior stat.ML · 2018 · author #3
  12. How do Humans Understand Explanations from Machine Learning Systems? An Evaluation of the Human-Interpretability of Explanation cs.AI · 2018 · author #4
  13. Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) stat.ML · 2017 · author #1
  14. The (Un)reliability of saliency methods stat.ML · 2017 · author #8
  15. Proceedings of the 2017 ICML Workshop on Human Interpretability in Machine Learning (WHI 2017) stat.ML · 2017 · author #1
  16. SmoothGrad: removing noise by adding noise cs.LG · 2017 · author #3
  17. Learning how to explain neural networks: PatternNet and PatternAttribution stat.ML · 2017 · author #6
  18. Towards A Rigorous Science of Interpretable Machine Learning stat.ML · 2017 · author #2
  19. Proceedings of NIPS 2016 Workshop on Interpretable Machine Learning for Complex Systems stat.ML · 2016 · author #2
  20. Proceedings of the 2016 ICML Workshop on Human Interpretability in Machine Learning (WHI 2016) stat.ML · 2016 · author #1
  21. The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification stat.ML · 2015 · author #1
  22. Learning About Meetings stat.AP · 2013 · author #1
  23. Inferring Robot Task Plans from Human Team Meetings: A Generative Modeling Approach with Logic-Based Prior cs.AI · 2013 · author #1

Mentions

  • 1503.01161 #1 · backfill · confidence 0.70 Been Kim
  • 1306.1927 #1 · backfill · confidence 0.70 Been Kim
  • 1306.0963 #1 · backfill · confidence 0.70 Been Kim
  • 2507.01201 #3 · arxiv_oai · confidence 0.70 Been Kim

Frequent Coauthors