activity
20242026
collaborators

11 papers

cs.AI2026

ZIPP:Zero-shot Image Personalization from Personas

Harini SI, Somesh Singh, Yaman Kumar Singla +2

Text-to-image diffusion models are increasingly deployed in open-ended creative contexts, yet their outputs remain impersonal, optimized for aggregate aesthetics rather than indivi…

cs.AI2026

Bridging Expert Knowledge and Automated Feature Engineering via Self-Evolution

Varun Khurana, Vijval Ekbote, Vashu Chauhan +3

In high-stakes settings such as brand compliance, clinical care, and content moderation, machine learning cannot be deployed as opaque oracles: practitioners inspect the features d…

cs.AI2026

MEMENTO: Leveraging Web as a Learning Signal for Low-Data Domains

Ashutosh Ojha, Vinay Aggarwal, Ashutosh Srivastava +3

Real-world tasks often lack large labeled datasets, motivating extensive work on learning in low-data regimes. However, existing approaches such as few-shot prompting, instruction…

cs.AI2026

Benchmarking the Personalization Capabilities of Large Language Models

Ashutosh Srivastava, Siddharth Yedlapati, Vinay Aggarwal +4

Personalization, the act of varying a message to induce action from a specific receiver while keeping sender, channel, and time fixed, has a long tradition in psychology and market…

cs.HC2026

How Well Do Large Language Models Capture Human Personality?

Aanisha Bhattacharyya, Yaman Kumar Singla, Rajiv Ratn Shah +2

Large language models (LLMs) are increasingly used to simulate human populations via persona prompting, often under the assumptions that richer persona descriptions improve behavio…

cs.HC2026

Detecting LLM-Assisted Academic Dishonesty using Keystroke Dynamics

Atharva Mehta, Rajesh Kumar, Aman Singla +3

The rapid adoption of generative AI tools has heightened concerns regarding academic integrity, as students increasingly engage in dishonest practices by copying or paraphrasing AI…