Search Results for author: Manoj Tiwari

Found 4 papers, 2 papers with code

Leveraging Large Language Models in Conversational Recommender Systems

no code implementations13 May 2023 Luke Friedman, Sameer Ahuja, David Allen, Zhenning Tan, Hakim Sidahmed, Changbo Long, Jun Xie, Gabriel Schubiner, Ajay Patel, Harsh Lara, Brian Chu, Zexi Chen, Manoj Tiwari

A Conversational Recommender System (CRS) offers increased transparency and control to users by enabling them to engage with the system through a real-time multi-turn dialogue.

Common Sense Reasoning Dialogue Management +3

Evaluation of Synthetic Datasets for Conversational Recommender Systems

no code implementations12 Dec 2022 Harsh Lara, Manoj Tiwari

The efficiency brought about by LLMs in the data generation phase is impeded during the process of evaluation of the generated data, since it generally requires human-raters to ensure that the data generated is of high quality and has sufficient diversity.

Recommendation Systems

Environment Generation for Zero-Shot Compositional Reinforcement Learning

1 code implementation NeurIPS 2021 Izzeddin Gur, Natasha Jaques, Yingjie Miao, Jongwook Choi, Manoj Tiwari, Honglak Lee, Aleksandra Faust

We learn to generate environments composed of multiple pages or rooms, and train RL agents capable of completing wide-range of complex tasks in those environments.

Navigate reinforcement-learning +1

Adversarial Environment Generation for Learning to Navigate the Web

1 code implementation2 Mar 2021 Izzeddin Gur, Natasha Jaques, Kevin Malta, Manoj Tiwari, Honglak Lee, Aleksandra Faust

The regret objective trains the adversary to design a curriculum of environments that are "just-the-right-challenge" for the navigator agents; our results show that over time, the adversary learns to generate increasingly complex web navigation tasks.

Benchmarking Decision Making +2

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