Search Results - "Java, Abhinav"

Densely connected convolutional transformer for single image dehazing by Parihar, Anil Singh, Java, Abhinav

“…Image Dehazing is an important low-level vision task that aims to remove the haze from an image. In this paper, we proposed Densely Connected Convolutional…”
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One-Shot Doc Snippet Detection: Powering Search in Document Beyond Text by Java, Abhinav, Deshmukh, Shripad, Aggarwal, Milan, Jandial, Surgan, Sarkar, Mausoom, Krishnamurthy, Balaji

“…Active consumption of digital documents has yielded scope for research in various applications, including search. Traditionally, searching within a document…”
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Towards Operationalizing Right to Data Protection by Java, Abhinav, Shahid, Simra, Agarwal, Chirag

“…The widespread practice of indiscriminate data scraping to fine-tune language models (LMs) raises significant legal and ethical concerns, particularly…”
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LEAST: "Local" text-conditioned image style transfer by Singh, Silky, Jandial, Surgan, Shahid, Simra, Java, Abhinav

“…Text-conditioned style transfer enables users to communicate their desired artistic styles through text descriptions, offering a new and expressive means of…”
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ReEdit: Multimodal Exemplar-Based Image Editing with Diffusion Models by Srivastava, Ashutosh, Menta, Tarun Ram, Java, Abhinav, Jadhav, Avadhoot, Singh, Silky, Jandial, Surgan, Krishnamurthy, Balaji

“…Modern Text-to-Image (T2I) Diffusion models have revolutionized image editing by enabling the generation of high-quality photorealistic images. While the de…”
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Thinking Fair and Slow: On the Efficacy of Structured Prompts for Debiasing Language Models by Furniturewala, Shaz, Jandial, Surgan, Java, Abhinav, Banerjee, Pragyan, Shahid, Simra, Bhatia, Sumit, Jaidka, Kokil

“…Existing debiasing techniques are typically training-based or require access to the model's internals and output distributions, so they are inaccessible to…”
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Dleep Learning based Regularization as defense against Clean Label Targeted Data Poisoning by Parihar, Anil Singh, Singh Kalra, Jushaan, Java, Abhinav

“…Adversarial examples are doctored inputs to predictive models intentionally designed with a malicious purpose - to manipulate the inference time outputs of the…”
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Learning to Censor by Noisy Sampling by Chopra, Ayush, Java, Abhinav, Singh, Abhishek, Sharma, Vivek, Raskar, Ramesh

“…Point clouds are an increasingly ubiquitous input modality and the raw signal can be efficiently processed with recent progress in deep learning. This signal…”
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All Should Be Equal in the Eyes of Language Models: Counterfactually Aware Fair Text Generation by Banerjee, Pragyan, Java, Abhinav, Jandial, Surgan, Shahid, Simra, Furniturewala, Shaz, Krishnamurthy, Balaji, Bhatia, Sumit

“…Fairness in Language Models (LMs) remains a longstanding challenge, given the inherent biases in training data that can be perpetuated by models and affect the…”
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Gatha: Relational Loss for enhancing text-based style transfer by Jandial, Surgan, Deshmukh, Shripad, Java, Abhinav, Shahid, Simra, Krishnamurthy, Balaji

“…Text-based style transfer is a promising area of research that enables the generation of stylistic images from plain text descriptions. However, the existing…”
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Introducing Self-Attention to Target Attentive Graph Neural Networks by Mitheran, Sai, Java, Abhinav, Sahu, Surya Kant, Shaikh, Arshad

“…Session-based recommendation systems suggest relevant items to users by modeling user behavior and preferences using short-term anonymous sessions. Existing…”
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Rethinking Neural Networks With Benford's Law by Sahu, Surya Kant, Java, Abhinav, Shaikh, Arshad, Kilcher, Yannic

“…Benford's Law (BL) or the Significant Digit Law defines the probability distribution of the first digit of numerical values in a data sample. This Law is…”
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One-Shot Doc Snippet Detection: Powering Search in Document Beyond Text by Java, Abhinav, Deshmukh, Shripad, Aggarwal, Milan, Jandial, Surgan, Sarkar, Mausoom, Krishnamurthy, Balaji

“…Active consumption of digital documents has yielded scope for research in various applications, including search. Traditionally, searching within a document…”
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AdaSplit: Adaptive Trade-offs for Resource-constrained Distributed Deep Learning by Chopra, Ayush, Sahu, Surya Kant, Singh, Abhishek, Java, Abhinav, Vepakomma, Praneeth, Sharma, Vivek, Raskar, Ramesh

“…Distributed deep learning frameworks like federated learning (FL) and its variants are enabling personalized experiences across a wide range of web clients and…”
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