GEO: Generative Engine Optimization

no code implementations • 16 Nov 2023 • Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, Karthik R Narasimhan, Ameet Deshpande

We facilitate systematic evaluation in this new paradigm by introducing GEO-bench, a benchmark of diverse user queries across multiple domains, coupled with sources required to answer these queries.

Linking Emergent and Natural Languages via Corpus Transfer

1 code implementation • ICLR 2022 • Shunyu Yao, Mo Yu, Yang Zhang, Karthik R Narasimhan, Joshua B. Tenenbaum, Chuang Gan

In this work, we propose a novel way to establish such a link by corpus transfer, i. e. pretraining on a corpus of emergent language for downstream natural language tasks, which is in contrast to prior work that directly transfers speaker and listener parameters.

Attribute Disentanglement +2

Grounding Language to Entities for Generalization in Reinforcement Learning

no code implementations • 1 Jan 2021 • H. J. Austin Wang, Karthik R Narasimhan

EMMA is end-to-end differentiable and can learn a latent grounding of entities and dynamics from text to observations using environment rewards as the only source of supervision.

reinforcement-learning Reinforcement Learning (RL) +1