5 papers
Prompting Policies for Multi-step Reasoning and Tool-Use in Black-box LLMs with Iterative Distillation of Experience
Krishna Sayana, Ketan Todi, Ambarish Jash
The shift toward interacting with frozen, "black-box" Large Language Models (LLMs) has transformed prompt engineering from a heuristic exercise into a critical optimization challen…
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…
FLARE: Fusing Language Models and Collaborative Architectures for Recommender Enhancement
Liam Hebert, Marialena Kyriakidi, Hubert Pham +4
Recent proposals in recommender systems represent items with their textual description, using a large language model. They show better results on standard benchmarks compared to an…
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…
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…