most citedClassifier-guided Gradient Modulation for Enhanced Multimodal Learning

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025

APO: Enhancing Reasoning Ability of MLLMs via Asymmetric Policy Optimization

Minjie Hong, Zirun Guo, Yan Xia +4

Multimodal Large Language Models (MLLMs) are powerful at integrating diverse data, but they often struggle with complex reasoning. While Reinforcement learning (RL) can boost reaso…

cs.SD2025

Unleashing the Power of Natural Audio Featuring Multiple Sound Sources

Xize Cheng, Slytherin Wang, Zehan Wang +3

Universal sound separation aims to extract clean audio tracks corresponding to distinct events from mixed audio, which is critical for artificial auditory perception. However, curr…

cs.CV2025

Towards Transformer-Based Aligned Generation with Self-Coherence Guidance

Shulei Wang, Wang Lin, Hai Huang +8

We introduce a novel, training-free approach for enhancing alignment in Transformer-based Text-Guided Diffusion Models (TGDMs). Existing TGDMs often struggle to generate semantical…

eess.AS2024

Speech Watermarking with Discrete Intermediate Representations

Shengpeng Ji, Ziyue Jiang, Jialong Zuo +4

Speech watermarking techniques can proactively mitigate the potential harmful consequences of instant voice cloning techniques. These techniques involve the insertion of signals in…

cs.LG20241 cited

Classifier-guided Gradient Modulation for Enhanced Multimodal Learning

Zirun Guo, Tao Jin, Jingyuan Chen +1

Multimodal learning has developed very fast in recent years. However, during the multimodal training process, the model tends to rely on only one modality based on which it could l…