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2020 – today
- 2024
[c39]Rohit Gandikota, Joanna Materzynska, Tingrui Zhou, Antonio Torralba, David Bau:
Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models. ECCV (40) 2024: 172-188- [c38]Sheridan Feucht, David Atkinson, Byron C. Wallace, David Bau:
Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs. EMNLP 2024: 9727-9739 - [c37]Stephen Casper
, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas A. Haupt, Kevin Wei, Jérémy Scheurer, Marius Hobbhahn, Lee Sharkey, Satyapriya Krishna, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell:
Black-Box Access is Insufficient for Rigorous AI Audits. FAccT 2024: 2254-2272 - [c36]Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau:
Linearity of Relation Decoding in Transformer Language Models. ICLR 2024 - [c35]Nikhil Prakash, Tamar Rott Shaham, Tal Haklay, Yonatan Belinkov, David Bau:
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking. ICLR 2024 - [c34]Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau:
Function Vectors in Large Language Models. ICLR 2024 - [c33]Maxwell Jones, Sheng-Yu Wang, Nupur Kumari, David Bau, Jun-Yan Zhu:
Customizing Text-to-Image Models with a Single Image Pair. SIGGRAPH Asia 2024: 6:1-6:13 - [c32]Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzynska, David Bau:
Unified Concept Editing in Diffusion Models. WACV 2024: 5099-5108 - [i48]Stephen Casper, Carson Ezell, Charlotte Siegmann, Noam Kolt, Taylor Lynn Curtis, Benjamin Bucknall, Andreas Alexander Haupt, Kevin Wei, Jérémy Scheurer, Marius Hobbhahn, Lee Sharkey, Satyapriya Krishna, Marvin Von Hagen, Silas Alberti, Alan Chan, Qinyi Sun, Michael Gerovitch, David Bau, Max Tegmark, David Krueger, Dylan Hadfield-Menell:
Black-Box Access is Insufficient for Rigorous AI Audits. CoRR abs/2401.14446 (2024) - [i47]Kenneth Li, Tianle Liu, Naomi Bashkansky, David Bau, Fernanda B. Viégas, Hanspeter Pfister, Martin Wattenberg:
Measuring and Controlling Persona Drift in Language Model Dialogs. CoRR abs/2402.10962 (2024) - [i46]Nikhil Prakash, Tamar Rott Shaham, Tal Haklay, Yonatan Belinkov, David Bau:
Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking. CoRR abs/2402.14811 (2024) - [i45]Koyena Pal, David Bau, Renée J. Miller:
Model Lakes. CoRR abs/2403.02327 (2024) - [i44]Samuel Marks, Can Rager, Eric J. Michaud, Yonatan Belinkov, David Bau, Aaron Mueller:
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models. CoRR abs/2403.19647 (2024) - [i43]Arnab Sen Sharma, David Atkinson, David Bau:
Locating and Editing Factual Associations in Mamba. CoRR abs/2404.03646 (2024) - [i42]Maxwell Jones, Sheng-Yu Wang, Nupur Kumari, David Bau, Jun-Yan Zhu:
Customizing Text-to-Image Models with a Single Image Pair. CoRR abs/2405.01536 (2024) - [i41]Sheridan Feucht, David Atkinson, Byron C. Wallace, David Bau:
Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs. CoRR abs/2406.20086 (2024) - [i40]Jaden Fiotto-Kaufman, Alexander R. Loftus, Eric Todd, Jannik Brinkmann, Caden Juang, Koyena Pal, Can Rager, Aaron Mueller, Samuel Marks, Arnab Sen Sharma, Francesca Lucchetti, Michael Ripa, Adam Belfki, Nikhil Prakash, Sumeet Multani, Carla E. Brodley, Arjun Guha, Jonathan Bell, Byron C. Wallace, David Bau:
NNsight and NDIF: Democratizing Access to Foundation Model Internals. CoRR abs/2407.14561 (2024) - [i39]Adam Karvonen, Benjamin Wright, Can Rager, Rico Angell, Jannik Brinkmann, Logan Smith, Claudio Mayrink Verdun, David Bau, Samuel Marks:
Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models. CoRR abs/2408.00113 (2024) - [i38]Aaron Mueller, Jannik Brinkmann, Millicent L. Li, Samuel Marks, Koyena Pal, Nikhil Prakash, Can Rager, Aruna Sankaranarayanan, Arnab Sen Sharma, Jiuding Sun, Eric Todd, David Bau, Yonatan Belinkov:
The Quest for the Right Mediator: A History, Survey, and Theoretical Grounding of Causal Interpretability. CoRR abs/2408.01416 (2024) - [i37]Rohit Gandikota, Sheridan Feucht, Samuel Marks, David Bau:
Erasing Conceptual Knowledge from Language Models. CoRR abs/2410.02760 (2024) - 2023
- [j7]Grace W. Lindsay, David Bau:
Testing methods of neural systems understanding. Cogn. Syst. Res. 82: 101156 (2023) - [c31]Koyena Pal, Jiuding Sun, Andrew Yuan, Byron C. Wallace, David Bau:
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State. CoNLL 2023: 548-560 - [c30]Rohit Gandikota, Joanna Materzynska, Jaden Fiotto-Kaufman, David Bau:
Erasing Concepts from Diffusion Models. ICCV 2023: 2426-2436 - [c29]Sarah Schwettmann, Neil Chowdhury, Samuel Klein, David Bau, Antonio Torralba:
Multimodal Neurons in Pretrained Text-Only Transformers. ICCV (Workshops) 2023: 2854-2859 - [c28]Kenneth Li, Aspen K. Hopkins, David Bau, Fernanda B. Viégas, Hanspeter Pfister, Martin Wattenberg:
Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task. ICLR 2023 - [c27]Kevin Meng, Arnab Sen Sharma, Alex J. Andonian, Yonatan Belinkov, David Bau:
Mass-Editing Memory in a Transformer. ICLR 2023 - [c26]Sarah Schwettmann, Tamar Rott Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba:
FIND: A Function Description Benchmark for Evaluating Interpretability Methods. NeurIPS 2023 - [c25]Daohan Lu, Sheng-Yu Wang, Nupur Kumari, Rohan Agarwal, Mia Tang, David Bau, Jun-Yan Zhu:
Content-based Search for Deep Generative Models. SIGGRAPH Asia 2023: 71:1-71:12 - [i36]Rohit Gandikota, Joanna Materzynska, Jaden Fiotto-Kaufman, David Bau:
Erasing Concepts from Diffusion Models. CoRR abs/2303.07345 (2023) - [i35]Xander Davies, Max Nadeau, Nikhil Prakash, Tamar Rott Shaham, David Bau:
Discovering Variable Binding Circuitry with Desiderata. CoRR abs/2307.03637 (2023) - [i34]Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau:
Linearity of Relation Decoding in Transformer Language Models. CoRR abs/2308.09124 (2023) - [i33]Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzynska, David Bau:
Unified Concept Editing in Diffusion Models. CoRR abs/2308.14761 (2023) - [i32]Sarah Schwettmann, Tamar Rott Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba:
A Function Interpretation Benchmark for Evaluating Interpretability Methods. CoRR abs/2309.03886 (2023) - [i31]Eric Todd, Millicent L. Li, Arnab Sen Sharma, Aaron Mueller, Byron C. Wallace, David Bau:
Function Vectors in Large Language Models. CoRR abs/2310.15213 (2023) - [i30]Koyena Pal, Jiuding Sun, Andrew Yuan, Byron C. Wallace, David Bau:
Future Lens: Anticipating Subsequent Tokens from a Single Hidden State. CoRR abs/2311.04897 (2023) - [i29]Silen Naihin, David Atkinson, Marc Green, Merwane Hamadi, Craig Swift, Douglas Schonholtz, Adam Tauman Kalai, David Bau:
Testing Language Model Agents Safely in the Wild. CoRR abs/2311.10538 (2023) - [i28]Nicholas Vincent, David Bau, Sarah Schwettmann, Joshua Tan:
An Alternative to Regulation: The Case for Public AI. CoRR abs/2311.11350 (2023) - [i27]Rohit Gandikota, Joanna Materzynska, Tingrui Zhou, Antonio Torralba, David Bau:
Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models. CoRR abs/2311.12092 (2023) - 2022
- [j6]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Rewriting geometric rules of a GAN. ACM Trans. Graph. 41(4): 73:1-73:16 (2022) - [c24]Joanna Materzynska, Antonio Torralba, David Bau:
Disentangling visual and written concepts in CLIP. CVPR 2022: 16389-16398 - [c23]Evan Hernandez, Sarah Schwettmann, David Bau, Teona Bagashvili, Antonio Torralba, Jacob Andreas:
Natural Language Descriptions of Deep Visual Features. ICLR 2022 - [c22]Justin D. Weisz, Mary Lou Maher, Hendrik Strobelt, Lydia B. Chilton, David Bau, Werner Geyer:
HAI-GEN 2022: 3rd Workshop on Human-AI Co-Creation with Generative Models. IUI Companion 2022: 4-6 - [c21]Kevin Meng, David Bau, Alex Andonian, Yonatan Belinkov:
Locating and Editing Factual Associations in GPT. NeurIPS 2022 - [i26]Evan Hernandez, Sarah Schwettmann, David Bau, Teona Bagashvili, Antonio Torralba, Jacob Andreas:
Natural Language Descriptions of Deep Visual Features. CoRR abs/2201.11114 (2022) - [i25]Kevin Meng, David Bau, Alex Andonian, Yonatan Belinkov:
Locating and Editing Factual Knowledge in GPT. CoRR abs/2202.05262 (2022) - [i24]Joanna Materzynska, Antonio Torralba, David Bau:
Disentangling visual and written concepts in CLIP. CoRR abs/2206.07835 (2022) - [i23]Audrey Cui, Ali Jahanian, Àgata Lapedriza, Antonio Torralba, Shahin Mahdizadehaghdam, Rohit Kumar, David Bau:
Local Relighting of Real Scenes. CoRR abs/2207.02774 (2022) - [i22]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Rewriting Geometric Rules of a GAN. CoRR abs/2207.14288 (2022) - [i21]Daohan Lu, Sheng-Yu Wang, Nupur Kumari, Rohan Agarwal, David Bau, Jun-Yan Zhu:
Content-Based Search for Deep Generative Models. CoRR abs/2210.03116 (2022) - [i20]Kevin Meng, Arnab Sen Sharma, Alex Andonian, Yonatan Belinkov, David Bau:
Mass-Editing Memory in a Transformer. CoRR abs/2210.07229 (2022) - [i19]Kenneth Li, Aspen K. Hopkins, David Bau, Fernanda B. Viégas, Hanspeter Pfister, Martin Wattenberg:
Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task. CoRR abs/2210.13382 (2022) - 2021
- [b2]David Bau:
Dissection of Deep Neural Networks. Massachusetts Institute of Technology, USA, 2021 - [c20]Sarah Schwettmann, Evan Hernandez, David Bau, Samuel Klein, Jacob Andreas, Antonio Torralba:
Toward a Visual Concept Vocabulary for GAN Latent Space. ICCV 2021: 6784-6792 - [c19]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Sketch Your Own GAN. ICCV 2021: 14030-14040 - [c18]Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. NeurIPS 2021: 23359-23373 - [c17]Emma Andrews, David Bau, Jeremiah J. Blanchard:
From Droplet to Lilypad: Present and Future of Dual-Modality Environments. VL/HCC 2021: 1-2 - [i18]David Bau, Alex Andonian, Audrey Cui, YeonHwan Park, Ali Jahanian, Aude Oliva, Antonio Torralba:
Paint by Word. CoRR abs/2103.10951 (2021) - [i17]Sheng-Yu Wang, David Bau, Jun-Yan Zhu:
Sketch Your Own GAN. CoRR abs/2108.02774 (2021) - [i16]Sarah Schwettmann, Evan Hernandez, David Bau, Samuel Klein, Jacob Andreas, Antonio Torralba:
Toward a Visual Concept Vocabulary for GAN Latent Space. CoRR abs/2110.04292 (2021) - [i15]Shibani Santurkar, Dimitris Tsipras, Mahalaxmi Elango, David Bau, Antonio Torralba, Aleksander Madry:
Editing a classifier by rewriting its prediction rules. CoRR abs/2112.01008 (2021) - 2020
- [j5]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Àgata Lapedriza, Bolei Zhou, Antonio Torralba:
Understanding the role of individual units in a deep neural network. Proc. Natl. Acad. Sci. USA 117(48): 30071-30078 (2020) - [c16]Steven Liu, Tongzhou Wang, David Bau, Jun-Yan Zhu, Antonio Torralba:
Diverse Image Generation via Self-Conditioned GANs. CVPR 2020: 14274-14283 - [c15]Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What Makes Fake Images Detectable? Understanding Properties that Generalize. ECCV (26) 2020: 103-120 - [c14]David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba:
Rewriting a Deep Generative Model. ECCV (1) 2020: 351-369 - [i14]David Bau, Hendrik Strobelt, William S. Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba:
Semantic Photo Manipulation with a Generative Image Prior. CoRR abs/2005.07727 (2020) - [i13]Steven Liu, Tongzhou Wang, David Bau, Jun-Yan Zhu, Antonio Torralba:
Diverse Image Generation via Self-Conditioned GANs. CoRR abs/2006.10728 (2020) - [i12]David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba:
Rewriting a Deep Generative Model. CoRR abs/2007.15646 (2020) - [i11]Lucy Chai, David Bau, Ser-Nam Lim, Phillip Isola:
What makes fake images detectable? Understanding properties that generalize. CoRR abs/2008.10588 (2020) - [i10]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Àgata Lapedriza, Bolei Zhou, Antonio Torralba:
Understanding the Role of Individual Units in a Deep Neural Network. CoRR abs/2009.05041 (2020)
2010 – 2019
- 2019
- [j4]David Weintrop, David Bau, Uri Wilensky:
The cloud is the limit: A case study of programming on the web, with the web. Int. J. Child Comput. Interact. 20: 1-8 (2019) - [j3]Bolei Zhou, David Bau, Aude Oliva, Antonio Torralba:
Interpreting Deep Visual Representations via Network Dissection. IEEE Trans. Pattern Anal. Mach. Intell. 41(9): 2131-2145 (2019) - [j2]David Bau, Hendrik Strobelt, William S. Peebles, Jonas Wulff, Bolei Zhou, Jun-Yan Zhu, Antonio Torralba:
Semantic photo manipulation with a generative image prior. ACM Trans. Graph. 38(4): 59:1-59:11 (2019) - [c13]Didac Suris, Adrià Recasens, David Bau, David Harwath, James R. Glass, Antonio Torralba:
Learning Words by Drawing Images. CVPR 2019: 2029-2038 - [c12]David Bau, Jun-Yan Zhu, Jonas Wulff, William S. Peebles, Bolei Zhou, Hendrik Strobelt, Antonio Torralba:
Seeing What a GAN Cannot Generate. ICCV 2019: 4501-4510 - [c11]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba:
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks. ICLR (Poster) 2019 - [c10]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba:
Visualizing and Understanding GANs. DGS@ICLR 2019 - [p1]Bolei Zhou, David Bau, Aude Oliva, Antonio Torralba:
Comparing the Interpretability of Deep Networks via Network Dissection. Explainable AI 2019: 243-252 - [i9]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba:
Visualizing and Understanding Generative Adversarial Networks (Extended Abstract). CoRR abs/1901.09887 (2019) - [i8]Jonathan Frankle, David Bau:
Dissecting Pruned Neural Networks. CoRR abs/1907.00262 (2019) - [i7]David Bau, Jun-Yan Zhu, Jonas Wulff, William S. Peebles, Hendrik Strobelt, Bolei Zhou, Antonio Torralba:
Seeing What a GAN Cannot Generate. CoRR abs/1910.11626 (2019) - 2018
- [c9]Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael A. Specter, Lalana Kagal:
Explaining Explanations: An Overview of Interpretability of Machine Learning. DSAA 2018: 80-89 - [c8]Bolei Zhou, Yiyou Sun, David Bau, Antonio Torralba:
Interpretable Basis Decomposition for Visual Explanation. ECCV (8) 2018: 122-138 - [i6]Leilani H. Gilpin, David Bau, Ben Z. Yuan, Ayesha Bajwa, Michael A. Specter, Lalana Kagal:
Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning. CoRR abs/1806.00069 (2018) - [i5]Bolei Zhou, Yiyou Sun, David Bau, Antonio Torralba:
Revisiting the Importance of Individual Units in CNNs via Ablation. CoRR abs/1806.02891 (2018) - [i4]David Bau, Jun-Yan Zhu, Hendrik Strobelt, Bolei Zhou, Joshua B. Tenenbaum, William T. Freeman, Antonio Torralba:
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks. CoRR abs/1811.10597 (2018) - 2017
- [j1]David Bau, Jeff Gray, Caitlin Kelleher, Josh Sheldon, Franklyn A. Turbak:
Learnable programming: blocks and beyond. Commun. ACM 60(6): 72-80 (2017) - [c7]David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, Antonio Torralba:
Network Dissection: Quantifying Interpretability of Deep Visual Representations. CVPR 2017: 3319-3327 - [i3]David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, Antonio Torralba:
Network Dissection: Quantifying Interpretability of Deep Visual Representations. CoRR abs/1704.05796 (2017) - [i2]David Bau, Jeff Gray, Caitlin Kelleher, Josh Sheldon, Franklyn A. Turbak:
Learnable Programming: Blocks and Beyond. CoRR abs/1705.09413 (2017) - [i1]Bolei Zhou, David Bau, Aude Oliva, Antonio Torralba:
Interpreting Deep Visual Representations via Network Dissection. CoRR abs/1711.05611 (2017) - 2015
- [c6]David Bau, D. Anthony Bau, Matthew Dawson, C. Sydney Pickens:
Pencil code: block code for a text world. IDC 2015: 445-448 - [c5]Amy Briggs, David Bau, Caroline Meeks, Pat Yongpradit:
Supporting the Computer Science Learning Process. SIGCSE 2015: 269-270 - [c4]David Bau, Matthew Dawson, Anthony Bau:
Using Pencil Code to Bridge the Gap between Visual and Text-Based Coding (Abstract Only). SIGCSE 2015: 706
2000 – 2009
- 2008
- [c3]Ming Zhao, Jay Yagnik, Hartwig Adam, David Bau:
Large scale learning and recognition of faces in web videos. FG 2008: 1-7 - 2001
- [c2]Vladimir Kotlyar, David Bau, Induprakas Kodukula, Keshav Pingali, Paul Stodghill:
Solving Alignment Using Elementary Linear Algebra. Compiler Optimizations for Scalable Parallel Systems Languages 2001: 385-412
1990 – 1999
- 1997
- [b1]Lloyd N. Trefethen, David Bau:
Numerical linear algebra. SIAM 1997, ISBN 978-0-89871-361-9, pp. I-XII, 1-361 - 1994
- [c1]David Bau, Induprakas Kodukula, Vladimir Kotlyar, Keshav Pingali, Paul Stodghill:
Solving Alignment Using Elementary Linear Algebra. LCPC 1994: 46-60
Coauthor Index
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