8 citations · 18 across the 7 of their papers we have counts for
8 papers
OmniInteract: Benchmarking Real-World Streaming Interaction for Real-Time Omnimodal Assistants
Xudong Lu, Xueying Li, Annan Wang +8
We introduce OmniInteract, a streaming benchmark for real-time omnimodal large language models evaluated through native online inference over audio-visual streams. Unlike offline v…
Rethinking Video Tokenization: A Conditioned Diffusion-based Approach
Nianzu Yang, Pandeng Li, Liming Zhao +8
Existing video tokenizers typically use the traditional Variational Autoencoder (VAE) architecture for video compression and reconstruction. However, to achieve good performance, i…
CAPability: A Comprehensive Visual Caption Benchmark for Evaluating Both Correctness and Thoroughness
Zhihang Liu, Chen-Wei Xie, Bin Wen +9
Visual captioning benchmarks have become outdated with the emergence of modern multimodal large language models (MLLMs), as the brief ground-truth sentences and traditional metrics…
Motion Control for Enhanced Complex Action Video Generation
Qiang Zhou, Shaofeng Zhang, Nianzu Yang +2
Existing text-to-video (T2V) models often struggle with generating videos with sufficiently pronounced or complex actions. A key limitation lies in the text prompt's inability to p…
MorphGrower: A Synchronized Layer-by-layer Growing Approach for Plausible Neuronal Morphology Generation
Nianzu Yang, Kaipeng Zeng, Haotian Lu +7
Neuronal morphology is essential for studying brain functioning and understanding neurodegenerative disorders. As acquiring real-world morphology data is expensive, computational a…
EasyDGL: Encode, Train and Interpret for Continuous-time Dynamic Graph Learning
Chao Chen, Haoyu Geng, Nianzu Yang +2
Dynamic graphs arise in various real-world applications, and it is often welcomed to model the dynamics directly in continuous time domain for its flexibility. This paper aims to d…
Learning Self-Modulating Attention in Continuous Time Space with Applications to Sequential Recommendation
Chao Chen, Haoyu Geng, Nianzu Yang +4
User interests are usually dynamic in the real world, which poses both theoretical and practical challenges for learning accurate preferences from rich behavior data. Among existin…
Molecule Generation for Drug Design: a Graph Learning Perspective
Nianzu Yang, Huaijin Wu, Kaipeng Zeng +2
Machine learning, particularly graph learning, is gaining increasing recognition for its transformative impact across various fields. One such promising application is in the realm…