190 citations · 283 across the 10 of their papers we have counts for
10 papers
Consistency and Uncertainty: Identifying Unreliable Responses From Black-Box Vision-Language Models for Selective Visual Question Answering
Zaid Khan, Yun Fu
The goal of selective prediction is to allow an a model to abstain when it may not be able to deliver a reliable prediction, which is important in safety-critical contexts. Existin…
Self-Training Large Language Models for Improved Visual Program Synthesis With Visual Reinforcement
Zaid Khan, Vijay Kumar BG, Samuel Schulter +2
Visual program synthesis is a promising approach to exploit the reasoning abilities of large language models for compositional computer vision tasks. Previous work has used few-sho…
Exploring Question Decomposition for Zero-Shot VQA
Zaid Khan, Vijay Kumar BG, Samuel Schulter +2
Visual question answering (VQA) has traditionally been treated as a single-step task where each question receives the same amount of effort, unlike natural human question-answering…
Q: How to Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!
Zaid Khan, Vijay Kumar BG, Samuel Schulter +3
Finetuning a large vision language model (VLM) on a target dataset after large scale pretraining is a dominant paradigm in visual question answering (VQA). Datasets for specialized…
Contrastive Alignment of Vision to Language Through Parameter-Efficient Transfer Learning
Zaid Khan, Yun Fu
Contrastive vision-language models (e.g. CLIP) are typically created by updating all the parameters of a vision model and language model through contrastive training. Can such mode…
Single-Stream Multi-Level Alignment for Vision-Language Pretraining
Zaid Khan, Vijay Kumar BG, Xiang Yu +3
Self-supervised vision-language pretraining from pure images and text with a contrastive loss is effective, but ignores fine-grained alignment due to a dual-stream architecture tha…
Exploiting BERT For Multimodal Target Sentiment Classification Through Input Space Translation
Zaid Khan, Yun Fu
Multimodal target/aspect sentiment classification combines multimodal sentiment analysis and aspect/target sentiment classification. The goal of the task is to combine vision and l…
One Label, One Billion Faces: Usage and Consistency of Racial Categories in Computer Vision
Zaid Khan, Yun Fu
Computer vision is widely deployed, has highly visible, society altering applications, and documented problems with bias and representation. Datasets are critical for benchmarking…
Families In Wild Multimedia: A Multimodal Database for Recognizing Kinship
Joseph P. Robinson, Zaid Khan, Yu Yin +2
Kinship, a soft biometric detectable in media, is fundamental for a myriad of use-cases. Despite the difficulty of detecting kinship, annual data challenges using still-images have…
Recognizing Families In the Wild: White Paper for the 4th Edition Data Challenge
Joseph P. Robinson, Yu Yin, Zaid Khan +7
Recognizing Families In the Wild (RFIW): an annual large-scale, multi-track automatic kinship recognition evaluation that supports various visual kin-based problems on scales much…