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20212025
most citedUser Embedding Model for Personalized Language Prompting

4 citations · 4 across the 6 of their papers we have counts for

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cs.CL2025

REGEN: A Dataset and Benchmarks with Natural Language Critiques and Narratives

Kun Su, Krishna Sayana, Hubert Pham +8

This paper introduces a novel dataset REGEN (Reviews Enhanced with GEnerative Narratives), designed to benchmark the conversational capabilities of recommender Large Language Model…

cs.CL2024

Beyond Retrieval: Generating Narratives in Conversational Recommender Systems

Krishna Sayana, Raghavendra Vasudeva, Yuri Vasilevski +6

The recent advances in Large Language Model's generation and reasoning capabilities present an opportunity to develop truly conversational recommendation systems. However, effectiv…

cs.CL2024

PERSOMA: PERsonalized SOft ProMpt Adapter Architecture for Personalized Language Prompting

Liam Hebert, Krishna Sayana, Ambarish Jash +5

Understanding the nuances of a user's extensive interaction history is key to building accurate and personalized natural language systems that can adapt to evolving user preference…

cs.CL20244 cited

User Embedding Model for Personalized Language Prompting

Sumanth Doddapaneni, Krishna Sayana, Ambarish Jash +2

Modeling long histories plays a pivotal role in enhancing recommendation systems, allowing to capture user's evolving preferences, resulting in more precise and personalized recomm…

cs.CL2023

BiPhone: Modeling Inter Language Phonetic Influences in Text

Abhirut Gupta, Ananya B. Sai, Richard Sproat +5

A large number of people are forced to use the Web in a language they have low literacy in due to technology asymmetries. Written text in the second language (L2) from such users o…