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09/29/2022
Unpacking Large Language Models with Conceptual Consistency
If a Large Language Model (LLM) answers "yes" to the question "Are mount...
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06/18/2022
SAViR-T: Spatially Attentive Visual Reasoning with Transformers
We present a novel computational model, "SAViR-T", for the family of vis...
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10/22/2021
Challenges in Procedural Multimodal Machine Comprehension:A Novel Way To Benchmark
We focus on Multimodal Machine Reading Comprehension (M3C) where a model...
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09/27/2021
DAReN: A Collaborative Approach Towards Reasoning And Disentangling
Computational learning approaches to solving visual reasoning tests, suc...
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06/08/2021
Comprehension Based Question Answering using Bloom's Taxonomy
Current pre-trained language models have lots of knowledge, but a more l...
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04/20/2021
Towards Solving Multimodal Comprehension
This paper targets the problem of procedural multimodal machine comprehe...
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11/21/2020
Zero-Shot Learning with Knowledge Enhanced Visual Semantic Embeddings
We improve zero-shot learning (ZSL) by incorporating common-sense knowle...
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09/26/2019
Task-Discriminative Domain Alignment for Unsupervised Domain Adaptation
Domain Adaptation (DA), the process of effectively adapting task models ...
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09/06/2019
Bayes-Factor-VAE: Hierarchical Bayesian Deep Auto-Encoder Models for Factor Disentanglement
We propose a family of novel hierarchical Bayesian deep auto-encoder mod...
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02/23/2019
Unsupervised Visual Domain Adaptation: A Deep Max-Margin Gaussian Process Approach
In unsupervised domain adaptation, it is widely known that the target do...
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02/05/2019
Relevance Factor VAE: Learning and Identifying Disentangled Factors
We propose a novel VAE-based deep auto-encoder model that can learn dise...
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10/26/2018