[HTML][HTML] Human evaluation of automatically generated text: Current trends and best practice guidelines

C van der Lee, A Gatt, E van Miltenburg… - Computer Speech & …, 2021 - Elsevier
Currently, there is little agreement as to how Natural Language Generation (NLG) systems
should be evaluated, with a particularly high degree of variation in the way that human …

A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning

E Brochu, VM Cora, N De Freitas - arXiv preprint arXiv:1012.2599, 2010 - arxiv.org
We present a tutorial on Bayesian optimization, a method of finding the maximum of
expensive cost functions. Bayesian optimization employs the Bayesian technique of setting …

Generative agents: Interactive simulacra of human behavior

JS Park, J O'Brien, CJ Cai, MR Morris, P Liang… - Proceedings of the 36th …, 2023 - dl.acm.org
Believable proxies of human behavior can empower interactive applications ranging from
immersive environments to rehearsal spaces for interpersonal communication to prototyping …

Emergent tool use from multi-agent autocurricula

B Baker, I Kanitscheider, T Markov, Y Wu… - arXiv preprint arXiv …, 2019 - arxiv.org
Through multi-agent competition, the simple objective of hide-and-seek, and standard
reinforcement learning algorithms at scale, we find that agents create a self-supervised …

A survey and critique of multiagent deep reinforcement learning

P Hernandez-Leal, B Kartal, ME Taylor - Autonomous Agents and Multi …, 2019 - Springer
Deep reinforcement learning (RL) has achieved outstanding results in recent years. This has
led to a dramatic increase in the number of applications and methods. Recent works have …

Extracting medicinal chemistry intuition via preference machine learning

OH Choung, R Vianello, M Segler, N Stiefl… - Nature …, 2023 - nature.com
The lead optimization process in drug discovery campaigns is an arduous endeavour where
the input of many medicinal chemists is weighed in order to reach a desired molecular …

TaleBrush: Sketching stories with generative pretrained language models

JJY Chung, W Kim, KM Yoo, H Lee, E Adar… - Proceedings of the 2022 …, 2022 - dl.acm.org
While advanced text generation algorithms (eg, GPT-3) have enabled writers to co-create
stories with an AI, guiding the narrative remains a challenge. Existing systems often …

Measuring human perceptions of a large-scale urban region using machine learning

F Zhang, B Zhou, L Liu, Y Liu, HH Fung, H Lin… - Landscape and Urban …, 2018 - Elsevier
Measuring the human sense of place and quantifying the connections among the visual
features of the built environment that impact the human sense of place have long been of …

[图书][B] Mathematics for machine learning

MP Deisenroth, AA Faisal, CS Ong - 2020 - books.google.com
The fundamental mathematical tools needed to understand machine learning include linear
algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability …

Findings of the 2017 conference on machine translation (wmt17)

O Bojar, R Chatterjee, C Federmann, Y Graham… - 2017 - doras.dcu.ie
This paper presents the results of the WMT17 shared tasks, which included three machine
translation (MT) tasks (news, biomedical, and multimodal), two evaluation tasks (metrics and …