1 citations · 1 across the 9 of their papers we have counts for
9 papers
Alignment-Aware Model Adaptation via Feedback-Guided Optimization
Gaurav Bhatt, Aditya Chinchure, Jiawei Zhou +1
Fine-tuning is the primary mechanism for adapting foundation models to downstream tasks; however, standard approaches largely optimize task objectives in isolation and do not accou…
SPIKE-RL: Video-LLMs meet Bayesian Surprise
Sahithya Ravi, Aditya Chinchure, Raymond T. Ng +2
Real-world videos often show routine activities punctuated by memorable, surprising events. However, most Video-LLMs process videos by sampling frames uniformly, likely missing cri…
RewardRank: Optimizing True Learning-to-Rank Utility
Gaurav Bhatt, Kiran Koshy Thekumparampil, Tanmay Gangwani +2
Traditional ranking systems optimize offline proxy objectives that rely on oversimplified assumptions about user behavior, often neglecting factors such as position bias and item d…
Mitigate One, Skew Another? Tackling Intersectional Biases in Text-to-Image Models
Pushkar Shukla, Aditya Chinchure, Emily Diana +5
The biases exhibited by text-to-image (TTI) models are often treated as independent, though in reality, they may be deeply interrelated. Addressing bias along one dimension - such…
Revealing Weaknesses in Text Watermarking Through Self-Information Rewrite Attacks
Yixin Cheng, Hongcheng Guo, Yangming Li +1
Text watermarking aims to subtly embed statistical signals into text by controlling the Large Language Model (LLM)'s sampling process, enabling watermark detectors to verify that t…
BiasConnect: Investigating Bias Interactions in Text-to-Image Models
Pushkar Shukla, Aditya Chinchure, Emily Diana +5
The biases exhibited by Text-to-Image (TTI) models are often treated as if they are independent, but in reality, they may be deeply interrelated. Addressing bias along one dimensio…
Preventing Catastrophic Forgetting through Memory Networks in Continuous Detection
Gaurav Bhatt, James Ross, Leonid Sigal
Modern pre-trained architectures struggle to retain previous information while undergoing continuous fine-tuning on new tasks. Despite notable progress in continual classification,…
TIBET: Identifying and Evaluating Biases in Text-to-Image Generative Models
Aditya Chinchure, Pushkar Shukla, Gaurav Bhatt +4
Text-to-Image (TTI) generative models have shown great progress in the past few years in terms of their ability to generate complex and high-quality imagery. At the same time, thes…
Mitigating the Effect of Incidental Correlations on Part-based Learning
Gaurav Bhatt, Deepayan Das, Leonid Sigal +1
Intelligent systems possess a crucial characteristic of breaking complicated problems into smaller reusable components or parts and adjusting to new tasks using these part represen…