1 citations · 2 across the 7 of their papers we have counts for
7 papers
Latent Thought Credit: Multi-Answer Credit Assignment for Latent Reasoning
Xuyang Zhao, Liting Zhang, Zichen Xu +4
Latent reasoning allows language models to carry out intermediate reasoning in continuous latent representations rather than fully externalizing it as discrete chains of thought. H…
EchoEdit: Stabilizing Inversion-Free Audio Editing via Optimal Transport Geometry
Zhongyuan Fu, Yuhang Jia, Hui Wang +6
Text-guided audio editing with pretrained generative models is commonly implemented through inversion or noising. This topology induces a structural trade-off, as stronger edits re…
AudioEditor: A Training-Free Diffusion-Based Audio Editing Framework
Yuhang Jia, Yang Chen, Jinghua Zhao +4
Diffusion-based text-to-audio (TTA) generation has made substantial progress, leveraging latent diffusion model (LDM) to produce high-quality, diverse and instruction-relevant audi…
M2R-Whisper: Multi-stage and Multi-scale Retrieval Augmentation for Enhancing Whisper
Jiaming Zhou, Shiwan Zhao, Jiabei He +6
State-of-the-art models like OpenAI's Whisper exhibit strong performance in multilingual automatic speech recognition (ASR), but they still face challenges in accurately recognizin…
Enhancing Emotion Recognition in Incomplete Data: A Novel Cross-Modal Alignment, Reconstruction, and Refinement Framework
Haoqin Sun, Shiwan Zhao, Shaokai Li +7
Multimodal emotion recognition systems rely heavily on the full availability of modalities, suffering significant performance declines when modal data is incomplete. To tackle this…
Fine-grained Disentangled Representation Learning for Multimodal Emotion Recognition
Haoqin Sun, Shiwan Zhao, Xuechen Wang +3
Multimodal emotion recognition (MMER) is an active research field that aims to accurately recognize human emotions by fusing multiple perceptual modalities. However, inherent heter…
kNN-CTC: Enhancing ASR via Retrieval of CTC Pseudo Labels
Jiaming Zhou, Shiwan Zhao, Yaqi Liu +3
The success of retrieval-augmented language models in various natural language processing (NLP) tasks has been constrained in automatic speech recognition (ASR) applications due to…