Search Results for author:
Found 6 papers, 2 papers with code
Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning
In this work, we propose a novel concept-based interpretability method that provides fine-grained explanations of DRL models at the neuron level.
Enhancing Scene Coordinate Regression with Efficient Keypoint Detection and Sequential Information
In this paper, we propose an efficient and accurate SCR system.
SBoRA: Low-Rank Adaptation with Regional Weight Updates
This paper introduces Standard Basis LoRA (SBoRA), a novel parameter-efficient fine-tuning approach for Large Language Models that builds upon the pioneering works of Low-Rank Adaptation (LoRA) and Orthogonal Adaptation.
MoVL:Exploring Fusion Strategies for the Domain-Adaptive Application of Pretrained Models in Medical Imaging Tasks
Yet, there exists a gap between input medical images and natural pretrained vision model.
Heuristic Hyperparameter Choice for Image Anomaly Detection
Anomaly detection (AD) in images is a fundamental computer vision problem by deep learning neural network to identify images deviating significantly from normality.
1st Place Solution to the EPIC-Kitchens Action Anticipation Challenge 2022
In this report, we describe the technical details of our submission to the EPIC-Kitchens Action Anticipation Challenge 2022.
