activity
20242026
most citedMeasure what Matters: Psychometric Evaluation of AI with Situational Judgment Tests

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Gotta Catch them all: the modes of Sycophancy

Shreyans Jain, Alexandra Yost, Amirali Abdullah

Large language models often align with users' beliefs at the expense of factual accuracy, a behavior known as sycophancy. Prior mechanistic studies largely treat sycophancy as a si…

cs.AI20261 cited

Measure what Matters: Psychometric Evaluation of AI with Situational Judgment Tests

Alexandra Yost, Shreyans Jain, Shivam Raval +6

Persona conditioning is widely used to steer large language model (LLM) behavior, but it is unclear whether it induces stable behavioral structure or superficial variation. We prop…

cs.LG2026

Unlearning in Diffusion models under Data Constraints: A Variational Inference Approach

Subhodip Panda, Varun M S, Shreyans Jain +2

For a responsible and safe deployment of diffusion models in various domains, regulating the generated outputs from these models is desirable because such models could generate und…

cs.AI2025

Sycophancy as compositions of Atomic Psychometric Traits

Shreyans Jain, Alexandra Yost, Amirali Abdullah

Sycophancy is a key behavioral risk in LLMs, yet is often treated as an isolated failure mode that occurs via a single causal mechanism. We instead propose modeling it as geometric…

cs.CV2024

WavShadow: Wavelet Based Shadow Segmentation and Removal

Shreyans Jain, Viraj Vekaria, Karan Gandhi +1

Shadow removal and segmentation remain challenging tasks in computer vision, particularly in complex real world scenarios. This study presents a novel approach that enhances the Sh…