7 citations · 9 across the 8 of their papers we have counts for
8 papers
CoANeRV: Coordinate-Aware Token-Space Neural Video Representation
Jialong Guo, Ke Liu, Mengxuan Li +2
Neural representations for videos (NeRV) have shown strong reconstruction fidelity by storing video-specific information in network weights. However, existing formulations typicall…
SlimVLM: Sensitivity-aware Dynamic Structured Pruning with Adaptive Visual Token Selection for Efficient Vision-Language Models
Yaozhi Wen, Jialong Guo, Zhenliang Ni +2
While Vision-Language Models (VLMs) have demonstrated remarkable performance in processing and understanding both text and images, their large parameter sizes lead to significant c…
SlimLLM: Accurate Structured Pruning for Large Language Models
Jialong Guo, Xinghao Chen, Yehui Tang +1
Large language models(LLMs) have garnered significant attention and demonstrated impressive capabilities in a wide range of applications. However, due to their enormous computation…
Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs
Hanting Chen, Jiarui Qin, Jialong Guo +15
Large Language Models (LLMs) deliver state-of-the-art capabilities across numerous tasks, but their immense size and inference costs pose significant computational challenges for p…
ImputeINR: Time Series Imputation via Implicit Neural Representations for Disease Diagnosis with Missing Data
Mengxuan Li, Ke Liu, Jialong Guo +3
Healthcare data frequently contain a substantial proportion of missing values, necessitating effective time series imputation to support downstream disease diagnosis tasks. However…
Transformer-Enhanced Variational Autoencoder for Crystal Structure Prediction
Ziyi Chen, Yang Yuan, Siming Zheng +4
Crystal structure forms the foundation for understanding the physical and chemical properties of materials. Generative models have emerged as a new paradigm in crystal structure pr…
MetaNeRV: Meta Neural Representations for Videos with Spatial-Temporal Guidance
Jialong Guo, Ke liu, Jiangchao Yao +3
Neural Representations for Videos (NeRV) has emerged as a promising implicit neural representation (INR) approach for video analysis, which represents videos as neural networks wit…
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
Jialong Guo, Xinghao Chen, Yehui Tang +1
Transformers have become foundational architectures for both natural language and computer vision tasks. However, the high computational cost makes it quite challenging to deploy o…