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Found 8 papers, 1 papers with code
DialogueTRM: Exploring Multi-Modal Emotional Dynamics in a Conversation
Emotion dynamics formulates principles explaining the emotional fluctuation during conversations.
A More Stable Accelerated Gradient Method Inspired by Continuous-Time Perspective
Experiments of matrix completion and handwriting digit recognition demonstrate that the stability of our new method is better.
SOFT: Softmax-free Transformer with Linear Complexity
Crucially, with a linear complexity, much longer token sequences are permitted in SOFT, resulting in superior trade-off between accuracy and complexity.
A Diversity-Enhanced and Constraints-Relaxed Augmentation for Low-Resource Classification
Previous studies mostly use a fine-tuned Language Model (LM) to strengthen the constraints but ignore the fact that the potential of diversity could improve the effectiveness of generated data.
Adversarial Mixing Policy for Relaxing Locally Linear Constraints in Mixup
To address these issues, we propose the Adversarial Mixing Policy (AMP), organized in a min-max-rand formulation, to relax the Locally Linear Constraints in Mixup.
A new accelerated gradient method inspired by continuous-time perspective
To give more insight about the acceleration phenomenon, an ordinary differential equation was obtained from Nesterov's accelerated method by taking step sizes approaching zero, and the relationship between Nesterov's method and the differential equation is still of research interest.
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems.
Ranked #7 on
Emotion Recognition in Conversation
on IEMOCAP
Hierarchical Context Enhanced Multi-Domain Dialogue System for Multi-domain Task Completion
Task 1 of the DSTC8-track1 challenge aims to develop an end-to-end multi-domain dialogue system to accomplish complex users' goals under tourist information desk settings.
