9 citations · 16 across the 9 of their papers we have counts for
9 papers
SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration
Zhuofan Wen, Yang Feng
Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, which leverage the base LLM its…
Multimodal Emotion Regression with Multi-Objective Optimization and VAD-Aware Audio Modeling for the 10th ABAW EMI Track
Jiawen Huang, Chenxi Huang, Zhuofan Wen +7
We participated in the 10th ABAW Challenge, focusing on the Emotional Mimicry Intensity (EMI) Estimation track on the Hume-Vidmimic2 dataset. This task aims to predict six continuo…
Feature-Based Dual Visual Feature Extraction Model for Compound Multimodal Emotion Recognition
Ran Liu, Fengyu Zhang, Cong Yu +7
This article presents our results for the eighth Affective Behavior Analysis in-the-wild (ABAW) competition.Multimodal emotion recognition (ER) has important applications in affect…
Speculative Decoding with CTC-based Draft Model for LLM Inference Acceleration
Zhuofan Wen, Shangtong Gui, Yang Feng
Inference acceleration of large language models (LLMs) has been put forward in many application scenarios and speculative decoding has shown its advantage in addressing inference a…
OV-MER: Towards Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Haiyang Sun, Licai Sun +13
Multimodal Emotion Recognition (MER) is a critical research area that seeks to decode human emotions from diverse data modalities. However, existing machine learning methods predom…
MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Haiyang Sun, Licai Sun +15
Multimodal emotion recognition is an important research topic in artificial intelligence. Over the past few decades, researchers have made remarkable progress by increasing the dat…