Been Kim
Scholar

Been Kim

Google Scholar ID: aGXkhcwAAAAJ
Google DeepMind
InterpretabilityMachine Learning
Homepage↗Google Scholar↗
Citations & Impact
All-time
Citations
27,214
 
H-index
45
 
i10-index
64
 
Publications
20
 
Co-authors
29
list available
Contact
No contact links provided.
Publications
9 items
Neologism Learning for Controllability and Self-Verbalization
2025
Cited
0
Video models are zero-shot learners and reasoners
2025
Cited
0
How many classes do we need to see for novel class discovery?
2025
Cited
0
Escaping Platos Cave: JAM for Aligning Independently Trained Vision and Language Models
2025
Cited
0
Because we have LLMs, we Can and Should Pursue Agentic Interpretability
2025
Cited
0
How new data permeates LLM knowledge and how to dilute it
2025
Cited
0
QuestBench: Can LLMs ask the right question to acquire information in reasoning tasks?
2025
Cited
0
We Can't Understand AI Using our Existing Vocabulary
2025
Cited
0
Resume (English only)
Co-authors
29 total
Finale Doshi-Velez
Finale Doshi-Velez
Professor, Harvard
Martin Wattenberg
Martin Wattenberg
Harvard University / Google Research
Fernanda Viégas
Fernanda Viégas
Google, Harvard
Co-author 4
Co-author 4
Justin Gilmer
Justin Gilmer
Google
James Wexler
James Wexler
Google
Co-author 7
Co-author 7
Pieter-Jan Kindermans
Pieter-Jan Kindermans
Staff Research Scientist, Google Deepmind