521 citations · 523 across the 8 of their papers we have counts for
8 papers
Iterative Refinement Improves Compositional Image Generation
Shantanu Jaiswal, Mihir Prabhudesai, Nikash Bhardwaj +5
Text-to-image (T2I) models have achieved remarkable progress, yet they continue to struggle with complex prompts that require simultaneously handling multiple objects, relations, a…
Can LLMs Lie? Investigation beyond Hallucination
Haoran Huan, Mihir Prabhudesai, Mengning Wu +2
Large language models (LLMs) have demonstrated impressive capabilities across a variety of tasks, but their increasing autonomy in real-world applications raises concerns about the…
Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios
Shantanu Jaiswal, Debaditya Roy, Basura Fernando +1
Complex visual reasoning and question answering (VQA) is a challenging task that requires compositional multi-step processing and higher-level reasoning capabilities beyond the imm…
Zero-Shot Visual Reasoning by Vision-Language Models: Benchmarking and Analysis
Aishik Nagar, Shantanu Jaiswal, Cheston Tan
Vision-language models (VLMs) have shown impressive zero- and few-shot performance on real-world visual question answering (VQA) benchmarks, alluding to their capabilities as visua…
Dissecting Multimodality in VideoQA Transformer Models by Impairing Modality Fusion
Ishaan Singh Rawal, Alexander Matyasko, Shantanu Jaiswal +2
While VideoQA Transformer models demonstrate competitive performance on standard benchmarks, the reasons behind their success are not fully understood. Do these models capture the…
A Probabilistic-Logic based Commonsense Representation Framework for Modelling Inferences with Multiple Antecedents and Varying Likelihoods
Shantanu Jaiswal, Liu Yan, Dongkyu Choi +1
Commonsense knowledge-graphs (CKGs) are important resources towards building machines that can 'reason' on text or environmental inputs and make inferences beyond perception. While…
TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs
Shantanu Jaiswal, Basura Fernando, Cheston Tan
Attention modules for Convolutional Neural Networks (CNNs) are an effective method to enhance performance on multiple computer-vision tasks. While existing methods appropriately mo…
graph2vec: Learning Distributed Representations of Graphs
Annamalai Narayanan, Mahinthan Chandramohan, Rajasekar Venkatesan +3
Recent works on representation learning for graph structured data predominantly focus on learning distributed representations of graph substructures such as nodes and subgraphs. Ho…