Lianyu Hu is a PhD graduating from Tianjin University, China, supervised by Prof Wei Feng. During his graduate student period, he worked closely with Prof Shenglan Liu. His research interest includes Video Understanding, Sign Lnaguage Understanding and Multimodal Learning.

๐Ÿ”ฅ News

  • We release LightVLM, an highly efficient method for large vision language models with a two-stage design. It improves model efficiency by first conducting visual token merging in the encoding stage and then adopt KV Cache compression in the decoding stage. It could achieve about 2ร— throughput across diffferent benchmarks and 3.21ร— throughput boost when outputting longer sequences.

  • We release iLLaVA, an efficient method for large vision language models by merging visual tokens. It could achieve about 2ร— throughput and 1.7ร— - 2ร— memory reduction with comparable performance through merging redundant visual tokens in some certain layers.

  • We release CorrNet+, an unified model with superior performance on both continuous sign language recognition and sign language translation tasks by using only RGB inputs.

  • We release DSTA-SLR, which performs sign language recognition (SLR) with pure skeleton inputs but ahcieves comparable accuracy and much faster speed than recognition with RGB inputs.

๐Ÿ“ Publications

๐Ÿ“– PrePrint

๐Ÿ–Š๏ธ Selected Publications ($\dagger$ denotes Correspding Author)

๐ŸŽ– Honors and Awards

  • 2025.06, Outstanding Graduate
  • 2024.12, ไผ˜็ง€ๅญฆ็”Ÿๆ ‡ๅ…ต๏ผˆten per year๏ผ‰
  • 2024.10, National Scholarship
  • 2023.10, National Scholarship

๐Ÿ“– Educations

  • 2021-2025, PhD in Computer Science and Technology, Tianjin Univerisity
  • 2018-2021, MEng in Computer Science and Technology, Dalian University of Technology
  • 2014-2018, BSc in Electronics and Information Engineering, Dalian University of Technology