activity
20242026
most citedLoRA-Mini : Adaptation Matrices Decomposition and Selective Training

1 citations · 1 across the 9 of their papers we have counts for

collaborators

13 papers

cs.CL2026

Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptions

Shivank Garg, Sankalp Mittal, Manish Gupta

Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically generates scientific architecture…

cs.CL2026

When Prompt Optimization Becomes Jailbreaking: Adaptive Red-Teaming of Large Language Models

Zafir Shamsi, Nikhil Chekuru, Zachary Guzman +1

Large Language Models (LLMs) are increasingly integrated into high-stakes applications, making robust safety guarantees a central practical and commercial concern. Existing safety…

cs.CV2026

MiSCHiEF: A Benchmark in Minimal-Pairs of Safety and Culture for Holistic Evaluation of Fine-Grained Image-Caption Alignment

Sagarika Banerjee, Tangatar Madi, Advait Swaminathan +4

Fine-grained image-caption alignment is crucial for vision-language models (VLMs), especially in socially critical contexts such as identifying real-world risk scenarios or disting…

cs.AI2026

SIDiffAgent: Self-Improving Diffusion Agent

Shivank Garg, Ayush Singh, Gaurav Kumar Nayak

Text-to-image diffusion models have revolutionized generative AI, enabling high-quality and photorealistic image synthesis. However, their practical deployment remains hindered by…

cs.CL2026

ViT Registers and Fractal ViT

Jason Chuan-Chih Chou, Abhinav Kumar, Shivank Garg

Drawing inspiration from recent findings including surprisingly decent performance of transformers without positional encoding (NoPE) in the domain of language models and how regis…

cs.CL2025

Thinking About Thinking: Evaluating Reasoning in Post-Trained Language Models

Pratham Singla, Shivank Garg, Ayush Singh +2

Recent advances in post-training techniques have endowed Large Language Models (LLMs) with enhanced capabilities for tackling complex, logic-intensive tasks through the generation…