21 citations · 122 across the 44 of their papers we have counts for
50 papers
Exploring Collaboration between a language and a non-language agent
Harini S, Somesh Singh, Yaman K Singla +3
LLMs are increasingly deployed as orchestrators that coordinate specialized subagents to solve complex tasks through natural language. However, in many important domains like game…
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…
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…
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…
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…
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…