Vision-language models (VLMs) have recently demonstrated strong efficacy...
The problem of community-level information pathway prediction (CLIPP) ai...
We present a novel framework for probing and improving relational,
compo...
If a Large Language Model (LLM) answers "yes" to the question "Are mount...
One approach to meet the challenges of deep lifelong reinforcement learn...
We present a series of two studies conducted to understand user's affect...
Incorporating interdisciplinary perspectives is seen as an essential ste...
This paper presents an approach to detect out-of-context (OOC) objects i...
We focus on Multimodal Machine Reading Comprehension (M3C) where a model...
Current pre-trained language models have lots of knowledge, but a more
l...
This paper targets the problem of procedural multimodal machine comprehe...
We target the problem of detecting Trojans or backdoors in DNNs. Such mo...
We improve zero-shot learning (ZSL) by incorporating common-sense knowle...
Few-Shot Learning (FSL) aims to improve a model's generalization capabil...
We introduce the eigentask framework for lifelong learning. An eigentask...
We introduce Deep Adaptive Semantic Logic (DASL), a novel framework for
...
Neural Ordinary Differential Equations (NODEs) have proven to be a power...
While models for Visual Question Answering (VQA) have steadily improved ...
Food classification is a challenging problem due to the large number of
...
There has been an explosion of multimodal content generated on social me...
Measuring Mutual Information (MI) between high-dimensional, continuous,
...
Computing author intent from multimodal data like Instagram posts requir...
While there have been many proposals on how to make AI algorithms more
t...
We address the problem of grounding free-form textual phrases by using w...
We propose novel Stacked Spatio-Temporal Graph Convolutional Networks
(S...
We tackle the problem of understanding visual ads where given an ad imag...
We introduce and tackle the problem of zero-shot object detection (ZSD),...
Food classification from images is a fine-grained classification problem...