16 citations · 36 across the 20 of their papers we have counts for
9 papers · 1 filter
ArtMine: Discovering and Formalizing Artistic Processes
Kaustubh Kumar, Ashutosh Ranjan, Vivek Srivastava +2
Understanding how artworks are created requires reasoning about the iterative decisions, material operations, and contextual influences that shape artistic production. While recent…
Democratic ICAI: Debating Our Way to Steering Principles from Preferences
Kevin Kingslin, Anish Natekar, Ashutosh Ranjan +3
Preference-based alignment often struggles to capture the reasoning that underlies human judgments. Many evaluations rely on multiple interacting criteria, yet pairwise labels reve…
The Silent Brush: Evaluating Artistic Style Leakage in AI Art Generation
Ninad Joshi, Ashutosh Ranjan, Vivek Srivastava +1
Generative text-to-image models are typically trained on large-scale web-scraped datasets that include diverse visual content such as copyrighted and stylistically distinctive artw…
Polaris: A Gödel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair
Aditya Kakade, Vivek Srivastava, Shirish Karande
Gödel agent realize recursive self-improvement: an agent inspects its own policy and traces and then modifies that policy in a tested loop. We introduce Polaris, Gödel agent for co…
Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models
Ashutosh Ranjan, Vivek Srivastava, Shirish Karande +1
Deployed text-to-image diffusion models increasingly require post-hoc concept unlearning for copyright claims, artist opt-outs, safety updates, and protected-content mitigation wit…
Can Physics Informed Neural Operators Self Improve?
Ritam Majumdar, Amey Varhade, Shirish Karande +1
Self-training techniques have shown remarkable value across many deep learning models and tasks. However, such techniques remain largely unexplored when considered in the context o…