most citedImproving Sequence-to-Sequence Models for Abstractive Text Summarization Using Meta Heuristic Approaches

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.LG2026

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…

cs.CL2024★ 1 cited

Improving Sequence-to-Sequence Models for Abstractive Text Summarization Using Meta Heuristic Approaches

Aditya Saxena, Ashutosh Ranjan

As human society transitions into the information age, reduction in our attention span is a contingency, and people who spend time reading lengthy news articles are decreasing rapi…