David Bau
- Papers
- 21
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Authored papers
21SliderSpace: Decomposing the Visual Capabilities of Diffusion Models
ICCV 2025
Distilling Diversity and Control in Diffusion Models
arXiv 2025
Position-aware Automatic Circuit Discovery
arXiv 2025
NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals
arXiv 2024
Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models
arXiv 2024
Measuring Progress in Dictionary Learning for Language Model Interpretability with Board Game Models
arXiv 2024
Measuring and Controlling Instruction (In)Stability in Language Model Dialogs
arXiv 2024
Locating and Editing Factual Associations in Mamba
arXiv 2024
Erasing Concepts from Diffusion Models
ICCV 2023 1
Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models
arXiv 2023
Unified Concept Editing in Diffusion Models
arXiv 2023
FIND: A Function Description Benchmark for Evaluating Interpretability Methods
find-a-function-description-benchmark-for
Locating and Editing Factual Associations in GPT
arXiv 2022
Mass-Editing Memory in a Transformer
arXiv 2022
Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task
arXiv 2022
Toward a Visual Concept Vocabulary for GAN Latent Space
toward-a-visual-concept-vocabulary-for-gan
Understanding the Role of Individual Units in a Deep Neural Network
arXiv 2020
Rewriting a Deep Generative Model
ECCV 2020 8
Diverse Image Generation via Self-Conditioned GANs
diverse-image-generation-via-self-conditioned
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks
gan-dissection-visualizing-and-understanding-1
Network Dissection: Quantifying Interpretability of Deep Visual Representations
network-dissection-quantifying-1
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