409 citations · 443 across the 6 of their papers we have counts for
6 papers
What Are We Measuring When We Evaluate Large Vision-Language Models? An Analysis of Latent Factors and Biases
Anthony Meng Huat Tiong, Junqi Zhao, Boyang Li +3
Vision-language (VL) models, pretrained on colossal image-text datasets, have attained broad VL competence that is difficult to evaluate. A common belief is that a small number of…
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
Wenliang Dai, Junnan Li, Dongxu Li +6
Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence. However, building general-purpose vision-lan…
Plug-and-Play VQA: Zero-shot VQA by Conjoining Large Pretrained Models with Zero Training
Anthony Meng Huat Tiong, Junnan Li, Boyang Li +2
Visual question answering (VQA) is a hallmark of vision and language reasoning and a challenging task under the zero-shot setting. We propose Plug-and-Play VQA (PNP-VQA), a modular…
Improving Tail-Class Representation with Centroid Contrastive Learning
Anthony Meng Huat Tiong, Junnan Li, Guosheng Lin +3
In vision domain, large-scale natural datasets typically exhibit long-tailed distribution which has large class imbalance between head and tail classes. This distribution poses dif…
Performance evaluation of a foot-controlled human-robot interface
Yanpei Huang, Etienne Burdet, Lin Cao +4
Robotic minimally invasive interventions typically require using more than two instruments. We thus developed a foot pedal interface which allows the user to control a robotic arm…
A Subject-Specific Four-Degree-of-Freedom Foot Interface to Control a Robot Arm
Yanpei Huang, Etienne Burdet, Lin Cao +3
In robotic surgery, the surgeon controls robotic instruments using dedicated interfaces. One critical limitation of current interfaces is that they are designed to be operated by o…