most citedTEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis

1 citations · 4 across the 7 of their papers we have counts for

collaborators

7 papers

cs.SD2024

Distil-DCCRN: A Small-footprint DCCRN Leveraging Feature-based Knowledge Distillation in Speech Enhancement

Runduo Han, Weiming Xu, Zihan Zhang +2

The deep complex convolution recurrent network (DCCRN) achieves excellent speech enhancement performance by utilizing the audio spectrum's complex features. However, it has a large…

cs.CL20241 cited

Enhancing the General Agent Capabilities of Low-Parameter LLMs through Tuning and Multi-Branch Reasoning

Qinhao Zhou, Zihan Zhang, Xiang Xiang +3

Open-source pre-trained Large Language Models (LLMs) exhibit strong language understanding and generation capabilities, making them highly successful in a variety of tasks. However…

cs.IR20231 cited

Auto Search Indexer for End-to-End Document Retrieval

Tianchi Yang, Minghui Song, Zihan Zhang +4

Generative retrieval, which is a new advanced paradigm for document retrieval, has recently attracted research interests, since it encodes all documents into the model and directly…

cs.CL2023

CITB: A Benchmark for Continual Instruction Tuning

Zihan Zhang, Meng Fang, Ling Chen +1

Continual learning (CL) is a paradigm that aims to replicate the human ability to learn and accumulate knowledge continually without forgetting previous knowledge and transferring…

eess.AS2023

An Exploration of Task-decoupling on Two-stage Neural Post Filter for Real-time Personalized Acoustic Echo Cancellation

Zihan Zhang, Jiayao Sun, Xianjun Xia +4

Deep learning based techniques have been popularly adopted in acoustic echo cancellation (AEC). Utilization of speaker representation has extended the frontier of AEC, thus attract…

cs.CV20231 cited

TEDi: Temporally-Entangled Diffusion for Long-Term Motion Synthesis

Zihan Zhang, Richard Liu, Kfir Aberman +1

The gradual nature of a diffusion process that synthesizes samples in small increments constitutes a key ingredient of Denoising Diffusion Probabilistic Models (DDPM), which have p…