activity
20212025
most citedHierarchically Gated Recurrent Neural Network for Sequence Modeling

25 citations · 87 across the 24 of their papers we have counts for

collaborators

21 papers

cs.AI20241 cited

Label-anticipated Event Disentanglement for Audio-Visual Video Parsing

Jinxing Zhou, Dan Guo, Yuxin Mao +3

Audio-Visual Video Parsing (AVVP) task aims to detect and temporally locate events within audio and visual modalities. Multiple events can overlap in the timeline, making identific…

cs.CL2024

Various Lengths, Constant Speed: Efficient Language Modeling with Lightning Attention

Zhen Qin, Weigao Sun, Dong Li +3

We present Lightning Attention, the first linear attention implementation that maintains a constant training speed for various sequence lengths under fixed memory consumption. Due…

cs.CV2024

TAVGBench: Benchmarking Text to Audible-Video Generation

Yuxin Mao, Xuyang Shen, Jing Zhang +5

The Text to Audible-Video Generation (TAVG) task involves generating videos with accompanying audio based on text descriptions. Achieving this requires skillful alignment of both a…

cs.CL20241 cited

CO2: Efficient Distributed Training with Full Communication-Computation Overlap

Weigao Sun, Zhen Qin, Weixuan Sun +5

The fundamental success of large language models hinges upon the efficacious implementation of large-scale distributed training techniques. Nevertheless, building a vast, high-perf…

cs.CL20242 cited

Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models

Zhen Qin, Weigao Sun, Dong Li +3

Linear attention is an efficient attention mechanism that has recently emerged as a promising alternative to conventional softmax attention. With its ability to process tokens in l…

cs.CL20231 cited

Accelerating Toeplitz Neural Network with Constant-time Inference Complexity

Zhen Qin, Yiran Zhong

Toeplitz Neural Networks (TNNs) have exhibited outstanding performance in various sequence modeling tasks. They outperform commonly used Transformer-based models while benefiting f…