David Bau

Orcid: 0000-0003-1744-6765

According to our database1, David Bau authored at least 68 papers between 1997 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Erasing Conceptual Knowledge from Language Models.
CoRR, 2024

The Quest for the Right Mediator: A History, Survey, and Theoretical Grounding of Causal Interpretability.
CoRR, 2024

Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models.
CoRR, 2024

NNsight and NDIF: Democratizing Access to Foundation Model Internals.
CoRR, 2024

Locating and Editing Factual Associations in Mamba.
CoRR, 2024

Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models.
CoRR, 2024

Model Lakes.
CoRR, 2024

Measuring and Controlling Persona Drift in Language Model Dialogs.
CoRR, 2024

Unified Concept Editing in Diffusion Models.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Customizing Text-to-Image Models with a Single Image Pair.
Proceedings of the SIGGRAPH Asia 2024 Conference Papers, 2024

Function Vectors in Large Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fine-Tuning Enhances Existing Mechanisms: A Case Study on Entity Tracking.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Linearity of Relation Decoding in Transformer Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024


Token Erasure as a Footprint of Implicit Vocabulary Items in LLMs.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
Testing methods of neural systems understanding.
Cogn. Syst. Res., December, 2023

An Alternative to Regulation: The Case for Public AI.
CoRR, 2023

Testing Language Model Agents Safely in the Wild.
CoRR, 2023

A Function Interpretation Benchmark for Evaluating Interpretability Methods.
CoRR, 2023

Discovering Variable Binding Circuitry with Desiderata.
CoRR, 2023

Content-based Search for Deep Generative Models.
Proceedings of the SIGGRAPH Asia 2023 Conference Papers, 2023

FIND: A Function Description Benchmark for Evaluating Interpretability Methods.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Mass-Editing Memory in a Transformer.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Multimodal Neurons in Pretrained Text-Only Transformers.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Erasing Concepts from Diffusion Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Future Lens: Anticipating Subsequent Tokens from a Single Hidden State.
Proceedings of the 27th Conference on Computational Natural Language Learning, 2023

2022
Rewriting geometric rules of a GAN.
ACM Trans. Graph., 2022

Content-Based Search for Deep Generative Models.
CoRR, 2022

Local Relighting of Real Scenes.
CoRR, 2022

Locating and Editing Factual Knowledge in GPT.
CoRR, 2022

Locating and Editing Factual Associations in GPT.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

HAI-GEN 2022: 3rd Workshop on Human-AI Co-Creation with Generative Models.
Proceedings of the IUI 2022: 27th International Conference on Intelligent User Interfaces, Helsinki, Finland, March 22 - 25, 2022, 2022

Natural Language Descriptions of Deep Visual Features.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Disentangling visual and written concepts in CLIP.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Dissection of Deep Neural Networks.
PhD thesis, 2021

Paint by Word.
CoRR, 2021

From Droplet to Lilypad: Present and Future of Dual-Modality Environments.
Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing, 2021

Editing a classifier by rewriting its prediction rules.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Sketch Your Own GAN.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Toward a Visual Concept Vocabulary for GAN Latent Space.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Understanding the role of individual units in a deep neural network.
Proc. Natl. Acad. Sci. USA, 2020

What Makes Fake Images Detectable? Understanding Properties that Generalize.
Proceedings of the Computer Vision - ECCV 2020, 2020

Rewriting a Deep Generative Model.
Proceedings of the Computer Vision - ECCV 2020, 2020

Diverse Image Generation via Self-Conditioned GANs.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Comparing the Interpretability of Deep Networks via Network Dissection.
Proceedings of the Explainable AI: Interpreting, 2019

Semantic photo manipulation with a generative image prior.
ACM Trans. Graph., 2019

Interpreting Deep Visual Representations via Network Dissection.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

The cloud is the limit: A case study of programming on the web, with the web.
Int. J. Child Comput. Interact., 2019

Dissecting Pruned Neural Networks.
CoRR, 2019

Visualizing and Understanding Generative Adversarial Networks (Extended Abstract).
CoRR, 2019

Visualizing and Understanding GANs.
Proceedings of the Deep Generative Models for Highly Structured Data, 2019

GAN Dissection: Visualizing and Understanding Generative Adversarial Networks.
Proceedings of the 7th International Conference on Learning Representations, 2019

Seeing What a GAN Cannot Generate.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

Learning Words by Drawing Images.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018
Revisiting the Importance of Individual Units in CNNs via Ablation.
CoRR, 2018

Explaining Explanations: An Approach to Evaluating Interpretability of Machine Learning.
CoRR, 2018

Interpretable Basis Decomposition for Visual Explanation.
Proceedings of the Computer Vision - ECCV 2018, 2018

Explaining Explanations: An Overview of Interpretability of Machine Learning.
Proceedings of the 5th IEEE International Conference on Data Science and Advanced Analytics, 2018

2017
Learnable programming: blocks and beyond.
Commun. ACM, 2017

Network Dissection: Quantifying Interpretability of Deep Visual Representations.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2015
Supporting the Computer Science Learning Process.
Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 2015

Using Pencil Code to Bridge the Gap between Visual and Text-Based Coding (Abstract Only).
Proceedings of the 46th ACM Technical Symposium on Computer Science Education, 2015

Pencil code: block code for a text world.
Proceedings of the 14th International Conference on Interaction Design and Children, 2015

2008
Large scale learning and recognition of faces in web videos.
Proceedings of the 8th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2008), 2008

2001
Solving Alignment Using Elementary Linear Algebra.
Proceedings of the Compiler Optimizations for Scalable Parallel Systems Languages, 2001

1997
Numerical linear algebra.
SIAM, ISBN: 978-0-89871-361-9, 1997


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