39 citations · 139 across the 47 of their papers we have counts for
54 papers
Long-Term Ad Memorability: Understanding & Generating Memorable Ads
Harini SI, Somesh Singh, Yaman K Singla +5
Despite the importance of long-term memory in marketing and brand building, until now, there has been no large-scale study on the memorability of ads. All previous memorability stu…
LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-training
Silky Singh, Shripad Deshmukh, Mausoom Sarkar +1
Learning object segmentation in image and video datasets without human supervision is a challenging problem. Humans easily identify moving salient objects in videos using the gesta…
FODVid: Flow-guided Object Discovery in Videos
Silky Singh, Shripad Deshmukh, Mausoom Sarkar +3
Segmentation of objects in a video is challenging due to the nuances such as motion blurring, parallax, occlusions, changes in illumination, etc. Instead of addressing these nuance…
SARC: Soft Actor Retrospective Critic
Sukriti Verma, Ayush Chopra, Jayakumar Subramanian +4
The two-time scale nature of SAC, which is an actor-critic algorithm, is characterised by the fact that the critic estimate has not converged for the actor at any given time, but s…
HyHTM: Hyperbolic Geometry based Hierarchical Topic Models
Simra Shahid, Tanay Anand, Nikitha Srikanth +3
Hierarchical Topic Models (HTMs) are useful for discovering topic hierarchies in a collection of documents. However, traditional HTMs often produce hierarchies where lowerlevel top…
INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Language Models
H S V N S Kowndinya Renduchintala, Krishnateja Killamsetty, Sumit Bhatia +4
A salient characteristic of pre-trained language models (PTLMs) is a remarkable improvement in their generalization capability and emergence of new capabilities with increasing mod…
Explaining RL Decisions with Trajectories
Shripad Vilasrao Deshmukh, Arpan Dasgupta, Balaji Krishnamurthy +4
Explanation is a key component for the adoption of reinforcement learning (RL) in many real-world decision-making problems. In the literature, the explanation is often provided by…
Parameter Efficient Local Implicit Image Function Network for Face Segmentation
Mausoom Sarkar, Nikitha SR, Mayur Hemani +2
Face parsing is defined as the per-pixel labeling of images containing human faces. The labels are defined to identify key facial regions like eyes, lips, nose, hair, etc. In this…
Synthesizing Human Gaze Feedback for Improved NLP Performance
Varun Khurana, Yaman Kumar Singla, Nora Hollenstein +2
Integrating human feedback in models can improve the performance of natural language processing (NLP) models. Feedback can be either explicit (e.g. ranking used in training languag…
Towards Estimating Transferability using Hard Subsets
Tarun Ram Menta, Surgan Jandial, Akash Patil +6
As transfer learning techniques are increasingly used to transfer knowledge from the source model to the target task, it becomes important to quantify which source models are suita…
UMFuse: Unified Multi View Fusion for Human Editing applications
Rishabh Jain, Mayur Hemani, Duygu Ceylan +4
Numerous pose-guided human editing methods have been explored by the vision community due to their extensive practical applications. However, most of these methods still use an ima…
VGFlow: Visibility guided Flow Network for Human Reposing
Rishabh Jain, Krishna Kumar Singh, Mayur Hemani +4
The task of human reposing involves generating a realistic image of a person standing in an arbitrary conceivable pose. There are multiple difficulties in generating perceptually a…
Distilling the Undistillable: Learning from a Nasty Teacher
Surgan Jandial, Yash Khasbage, Arghya Pal +2
The inadvertent stealing of private/sensitive information using Knowledge Distillation (KD) has been getting significant attention recently and has guided subsequent defense effort…
One-Shot Doc Snippet Detection: Powering Search in Document Beyond Text
Abhinav Java, Shripad Deshmukh, Milan Aggarwal +3
Active consumption of digital documents has yielded scope for research in various applications, including search. Traditionally, searching within a document has been cast as a text…
LM-CORE: Language Models with Contextually Relevant External Knowledge
Jivat Neet Kaur, Sumit Bhatia, Milan Aggarwal +2
Large transformer-based pre-trained language models have achieved impressive performance on a variety of knowledge-intensive tasks and can capture factual knowledge in their parame…
Persuasion Strategies in Advertisements
Yaman Kumar Singla, Rajat Jha, Arunim Gupta +7
Modeling what makes an advertisement persuasive, i.e., eliciting the desired response from consumer, is critical to the study of propaganda, social psychology, and marketing. Despi…
Differentiable Agent-based Epidemiology
Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian +4
Mechanistic simulators are an indispensable tool for epidemiology to explore the behavior of complex, dynamic infections under varying conditions and navigate uncertain environment…
CoSe-Co: Text Conditioned Generative CommonSense Contextualizer
Rachit Bansal, Milan Aggarwal, Sumit Bhatia +2
Pre-trained Language Models (PTLMs) have been shown to perform well on natural language tasks. Many prior works have leveraged structured commonsense present in the form of entitie…
INDIGO: Intrinsic Multimodality for Domain Generalization
Puneet Mangla, Shivam Chandhok, Milan Aggarwal +2
For models to generalize under unseen domains (a.k.a domain generalization), it is crucial to learn feature representations that are domain-agnostic and capture the underlying sema…
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models
Vedant Singh, Surgan Jandial, Ayush Chopra +3
Conditional image generation has paved the way for several breakthroughs in image editing, generating stock photos and 3-D object generation. This continues to be a significant are…
Status-quo policy gradient in Multi-Agent Reinforcement Learning
Pinkesh Badjatiya, Mausoom Sarkar, Nikaash Puri +4
Individual rationality, which involves maximizing expected individual returns, does not always lead to high-utility individual or group outcomes in multi-agent problems. For instan…
DeepABM: Scalable, efficient and differentiable agent-based simulations via graph neural networks
Ayush Chopra, Esma Gel, Jayakumar Subramanian +5
We introduce DeepABM, a framework for agent-based modeling that leverages geometric message passing of graph neural networks for simulating action and interactions over large agent…
MINIMAL: Mining Models for Data Free Universal Adversarial Triggers
Swapnil Parekh, Yaman Singla Kumar, Somesh Singh +3
It is well known that natural language models are vulnerable to adversarial attacks, which are mostly input-specific in nature. Recently, it has been shown that there also exist in…
ZFlow: Gated Appearance Flow-based Virtual Try-on with 3D Priors
Ayush Chopra, Rishabh Jain, Mayur Hemani +1
Image-based virtual try-on involves synthesizing perceptually convincing images of a model wearing a particular garment and has garnered significant research interest due to its im…