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08/20/2023
ThermRad: A Multi-modal Dataset for Robust 3D Object Detection under Challenging Conditions
Robust 3D object detection in extreme weather and illumination condition...
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07/21/2023
Redemption from Range-view for Accurate 3D Object Detection
Most recent approaches for 3D object detection predominantly rely on poi...
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06/29/2023
Restore Translation Using Equivariant Neural Networks
Invariance to spatial transformations such as translations and rotations...
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06/15/2023
Infinite Photorealistic Worlds using Procedural Generation
We introduce Infinigen, a procedural generator of photorealistic 3D scen...
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05/31/2023
Red Teaming Language Model Detectors with Language Models
The prevalence and high capacity of large language models (LLMs) present...
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05/30/2023
Universality and Limitations of Prompt Tuning
Despite the demonstrated empirical efficacy of prompt tuning to adapt a ...
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11/01/2022
Preserving In-Context Learning ability in Large Language Model Fine-tuning
Pretrained large language models (LLMs) are strong in-context learners t...
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10/13/2022
Efficiently Computing Local Lipschitz Constants of Neural Networks via Bound Propagation
Lipschitz constants are connected to many properties of neural networks,...
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05/25/2022
RLPrompt: Optimizing Discrete Text Prompts With Reinforcement Learning
Prompting has shown impressive success in enabling large pretrained lang...
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05/03/2022
Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation
Pose estimation plays a critical role in human-centered vision applicati...
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03/20/2022
Adversarial Parameter Attack on Deep Neural Networks
In this paper, a new parameter perturbation attack on DNNs, called adver...
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03/16/2022
On the Convergence of Certified Robust Training with Interval Bound Propagation
Interval Bound Propagation (IBP) is so far the base of state-of-the-art ...
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03/31/2021
Fast Certified Robust Training via Better Initialization and Shorter Warmup
Recently, bound propagation based certified adversarial defense have bee...
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11/27/2020
Fast and Complete: Enabling Complete Neural Network Verification with Rapid and Massively Parallel Incomplete Verifiers
Formal verification of neural networks (NNs) is a challenging and import...
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08/20/2020
