7 citations · 13 across the 4 of their papers we have counts for
4 papers · 1 filter
HIVE: Understanding Post-Hallucination Reasoning in Vision Language Models
Feng He, Zhenting Wang, Qifan Wang +4
Hallucinations in vision language models (VLMs) are commonly treated as semantic errors, yet they often arise from partial or ambiguous visual evidence. Prior work mainly focuses o…
Improving Video Retrieval by Adaptive Margin
Feng He, Qi Wang, Zhifan Feng +4
Video retrieval is becoming increasingly important owing to the rapid emergence of videos on the Internet. The dominant paradigm for video retrieval learns video-text representatio…
CLOP: Video-and-Language Pre-Training with Knowledge Regularizations
Guohao Li, Hu Yang, Feng He +4
Video-and-language pre-training has shown promising results for learning generalizable representations. Most existing approaches usually model video and text in an implicit manner,…
A CLIP-Enhanced Method for Video-Language Understanding
Guohao Li, Feng He, Zhifan Feng
This technical report summarizes our method for the Video-And-Language Understanding Evaluation (VALUE) challenge (https://value-benchmark.github.io/challenge\_2021.html). We propo…