Search Results for author:
Found 9 papers, 5 papers with code
Improvement of Frequency Source Phase Noise Reduction Design under Vibration Condition
Reasonable vibration reduction design is an important way to achieve low phase noise index of airborne frequency source output signal.
Core Challenges in Embodied Vision-Language Planning
Recent advances in the areas of Multimodal Machine Learning and Artificial Intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision, Natural Language Processing, and Robotics.
VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations
Inspired by the CheckList for testing natural language processing, we exploit VL-CheckList, a novel framework to understand the capabilities of VLP models.
Localize, Group, and Select: Boosting Text-VQA by Scene Text Modeling
LOGOS leverages two grounding tasks to better localize the key information of the image, utilizes scene text clustering to group individual OCR tokens, and learns to select the best answer from different sources of OCR (Optical Character Recognition) texts.
CIGLI: Conditional Image Generation from Language & Image
Instead of generating an image based on text as in text-image generation, this task requires the generation of an image from a textual description and an image prompt.
Core Challenges in Embodied Vision-Language Planning
Recent advances in the areas of multimodal machine learning and artificial intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision, Natural Language Processing, and Embodied AI.
SF-QA: Simple and Fair Evaluation Library for Open-domain Question Answering
Although open-domain question answering (QA) draws great attention in recent years, it requires large amounts of resources for building the full system and is often difficult to reproduce previous results due to complex configurations.
VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words
To the best of our knowledge, VisualSparta is the first transformer-based text-to-image retrieval model that can achieve real-time searching for large-scale datasets, with significant accuracy improvement compared to previous state-of-the-art methods.
Ranked #2 on
Image Retrieval
on MS COCO
SPARTA: Efficient Open-Domain Question Answering via Sparse Transformer Matching Retrieval
We validated our approaches on 4 open-domain question answering (OpenQA) tasks and 11 retrieval question answering (ReQA) tasks.
Ranked #1 on
Open-Domain Question Answering
on SQuAD1.1 dev
