1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CV2026
GSTEP: Global Spatio-Temporal Density-Driven Visual Token Pruning for Efficient Video Large Language Models
Mengjie Zhang, Qihui Zhu, Tao Zhang +10
Video large language models (VideoLLMs) achieve strong video understanding performance, but their inference remains expensive due to the large number of redundant spatio-temporal v…
cs.CR2026★ 1 cited
HardSecBench: Benchmarking the Security Awareness of LLMs for Hardware Code Generation
Qirui Chen, Jingxian Shuai, Shuangwu Chen +8
Large language models (LLMs) are increasingly used for hardware and firmware code generation, but existing studies primarily evaluate functional correctness while largely overlooki…
cs.CL2026
Rethinking Table Pruning in TableQA: From Sequential Revisions to Gold Trajectory-Supervised Parallel Search
Yu Guo, Shenghao Ye, Shuangwu Chen +8
Table Question Answering (TableQA) benefits significantly from table pruning, which extracts compact sub-tables by eliminating redundant cells to streamline downstream reasoning. H…