Search Results for author:
Found 5 papers, 2 papers with code
Exploring Iterative Refinement with Diffusion Models for Video Grounding
In this paper, we propose DiffusionVG, a novel framework with diffusion models that formulates video grounding as a conditional generation task, where the target span is generated from Gaussian noise inputs and interatively refined in the reverse diffusion process.
SSLCL: An Efficient Model-Agnostic Supervised Contrastive Learning Framework for Emotion Recognition in Conversations
To address these challenges, we propose an efficient and model-agnostic SCL framework named Supervised Sample-Label Contrastive Learning with Soft-HGR Maximal Correlation (SSLCL), which eliminates the need for a large batch size and can be seamlessly integrated with existing ERC models without introducing any model-specific assumptions.
Identifying Reaction-Aware Driving Styles of Stochastic Model Predictive Controlled Vehicles by Inverse Reinforcement Learning
Nevertheless, an important indicator of the driving style, i. e., how an AV reacts to its nearby AVs, is not fully incorporated in the feature design of previous ME-IRL methods.
Generalization of group-theoretic coherent states for variational calculations
We introduce new families of pure quantum states that are constructed on top of the well-known Gilmore-Perelomov group-theoretic coherent states.
Quantum Physics Quantum Gases Strongly Correlated Electrons Mathematical Physics Mathematical Physics
Scalable Spectral Algorithms for Community Detection in Directed Networks
Community detection has been one of the central problems in network studies and directed network is particularly challenging due to asymmetry among its links.
