1 citations · 3 across the 11 of their papers we have counts for
11 papers
Bayesian Data Reweighting Improves Multimodal Retrieval for Knowledge-Based Visual Question Answering
Jingchen Sun, Shaobo Han, Ruiyi Zhang +5
Multimodal retrievers are essential for knowledge-based visual question answering, where they retrieve external evidence for image-question pairs. However, existing contrastive tra…
Score-Control for Hallucination Reduction in Diffusion Models
Mahesh Bhosale, Naresh Kumar Devulapally, Abdul Wasi +3
Diffusion models have emerged as the backbone of modern generative AI, powering advances in vision, language, audio and other modalities. Despite their success, they suffer from ha…
OSCAR: Orchestrated Self-verification and Cross-path Refinement
Yash Shah, Abhijit Chakraborty, Naresh Kumar Devulapally +2
Diffusion language models (DLMs) expose their denoising trajectories, offering a natural handle for inference-time control; accordingly, an ideal hallucination mitigation framework…
Forget Less by Learning Together through Concept Consolidation
Arjun Ramesh Kaushik, Naresh Kumar Devulapally, Vishnu Suresh Lokhande +2
Custom Diffusion Models (CDMs) have gained significant attention due to their remarkable ability to personalize generative processes. However, existing CDMs suffer from catastrophi…
Forget Less by Learning from Parents Through Hierarchical Relationships
Arjun Ramesh Kaushik, Naresh Kumar Devulapally, Vishnu Suresh Lokhande +2
Custom Diffusion Models (CDMs) offer impressive capabilities for personalization in generative modeling, yet they remain vulnerable to catastrophic forgetting when learning new con…
Latent Diffusion Unlearning: Protecting Against Unauthorized Personalization Through Trajectory Shifted Perturbations
Naresh Kumar Devulapally, Shruti Agarwal, Tejas Gokhale +1
Text-to-image diffusion models have demonstrated remarkable effectiveness in rapid and high-fidelity personalization, even when provided with only a few user images. However, the e…
Model-Agnostic Gender Bias Control for Text-to-Image Generation via Sparse Autoencoder
Chao Wu, Zhenyi Wang, Kangxian Xie +3
Text-to-image (T2I) diffusion models often exhibit gender bias, particularly by generating stereotypical associations between professions and gendered subjects. This paper presents…
Your Text Encoder Can Be An Object-Level Watermarking Controller
Naresh Kumar Devulapally, Mingzhen Huang, Vishal Asnani +3
Invisible watermarking of AI-generated images can help with copyright protection, enabling detection and identification of AI-generated media. In this work, we present a novel appr…
AM^2-EmoJE: Adaptive Missing-Modality Emotion Recognition in Conversation via Joint Embedding Learning
Naresh Kumar Devulapally, Sidharth Anand, Sreyasee Das Bhattacharjee +1
Human emotion can be presented in different modes i.e., audio, video, and text. However, the contribution of each mode in exhibiting each emotion is not uniform. Furthermore, the a…
AMuSE: Adaptive Multimodal Analysis for Speaker Emotion Recognition in Group Conversations
Naresh Kumar Devulapally, Sidharth Anand, Sreyasee Das Bhattacharjee +2
Analyzing individual emotions during group conversation is crucial in developing intelligent agents capable of natural human-machine interaction. While reliable emotion recognition…
Physical Momentum in the Indian Stock Market
Naresh Kumar Devulapally, Tulasi Narendra Das Tripurana
Our study focuses on determining the presence of abnormal returns for physical momentum portfolios in the context of the Indian market. The physical momentum portfolios, comprising…