2 citations · 4 across the 12 of their papers we have counts for
13 papers
Lip-Siri: Contactless Open-Sentence Silent Speech with Wi-Fi Backscatter
Ye Tian, Haohua Du, Chao Gu +5
Silent speech interfaces (SSIs) enable silent interaction in noise-sensitive or privacy-sensitive settings. However, existing SSIs face practical deployment trade-offs among privac…
FiCoTS: Fine-to-Coarse LLM-Enhanced Hierarchical Cross-Modality Interaction for Time Series Forecasting
Yafei Lyu, Hao Zhou, Lu Zhang +2
Time series forecasting is central to data analysis and web technologies. The recent success of Large Language Models (LLMs) offers significant potential for this field, especially…
AudioCodecBench: A Comprehensive Benchmark for Audio Codec Evaluation
Lu Wang, Hao Chen, Siyu Wu +5
Multimodal Large Language Models (MLLMs) have been widely applied in speech and music. This tendency has led to a focus on audio tokenization for Large Models (LMs). Unlike semanti…
Adapting Whisper for Streaming Speech Recognition via Two-Pass Decoding
Haoran Zhou, Xingchen Song, Brendan Fahy +9
OpenAI Whisper is a family of robust Automatic Speech Recognition (ASR) models trained on 680,000 hours of audio. However, its encoder-decoder architecture, trained with a sequence…
Enabling Versatile Controls for Video Diffusion Models
Xu Zhang, Hao Zhou, Haoming Qin +5
Despite substantial progress in text-to-video generation, achieving precise and flexible control over fine-grained spatiotemporal attributes remains a significant unresolved challe…
Erase Diffusion: Empowering Object Removal Through Calibrating Diffusion Pathways
Yi Liu, Hao Zhou, Wenxiang Shang +2
Erase inpainting, or object removal, aims to precisely remove target objects within masked regions while preserving the overall consistency of the surrounding content. Despite diff…
MACS: Multi-source Audio-to-image Generation with Contextual Significance and Semantic Alignment
Hao Zhou, Xiaobao Guo, Yuzhe Zhu +1
Propelled by the breakthrough in deep generative models, audio-to-image generation has emerged as a pivotal cross-modal task that converts complex auditory signals into rich visual…
Assessing the Macro and Micro Effects of Random Seeds on Fine-Tuning Large Language Models
Nghia Bui, Guergana Savova, Lijing Wang
The impact of random seeds in fine-tuning large language models (LLMs) has been largely overlooked despite its potential influence on model performance.In this study, we systematic…
ACDiT: Interpolating Autoregressive Conditional Modeling and Diffusion Transformer
Jinyi Hu, Shengding Hu, Yuxuan Song +6
Autoregressive and diffusion models have achieved remarkable progress in language models and visual generation, respectively. We present ACDiT, a novel Autoregressive blockwise Con…
Gradually Vanishing Gap in Prototypical Network for Unsupervised Domain Adaptation
Shanshan Wang, Hao Zhou, Xun Yang +4
Unsupervised domain adaptation (UDA) is a critical problem for transfer learning, which aims to transfer the semantic information from labeled source domain to unlabeled target dom…
Revisiting the Markov Property for Machine Translation
Cunxiao Du, Hao Zhou, Zhaopeng Tu +1
In this paper, we re-examine the Markov property in the context of neural machine translation. We design a Markov Autoregressive Transformer~(MAT) and undertake a comprehensive ass…
Non-Autoregressive Document-Level Machine Translation
Guangsheng Bao, Zhiyang Teng, Hao Zhou +2
Non-autoregressive translation (NAT) models achieve comparable performance and superior speed compared to auto-regressive translation (AT) models in the context of sentence-level m…
Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning
Lihua Qian, Mingxuan Wang, Yang Liu +1
Previously, non-autoregressive models were widely perceived as being superior in generation efficiency but inferior in generation quality due to the difficulties of modeling multip…