3 papers
cs.AI2026
Benchmarking the Personalization Capabilities of Large Language Models
Ashutosh Srivastava, Siddharth Yedlapati, Vinay Aggarwal +4
Personalization is classically a two-party problem: a sender chooses what to say, and a receiver with independent objectives decides whether to act. A salesperson pitching the same…
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. Existing approaches such as few-shot prompting, instruction tuning, a…
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…