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Yo! wiksas? = Hi! how are you? : an illustrated conversation with the invisible girl Siri
\"Hello! Wik'sas? is a book for curious kids who ask big questions - and adults who help them discover the answers. It is an illustrated conversation between Isla and Ethan - son and daughter of Kwakwaka'wakw, Chief Rande Ola K'alapa (Cook), a much loved artist of mixed European and Indigenous decent - and their invisible friend Siri. Isabel Rogers, also a kid, is part of the storytelling process. We want this book to be a bridge, a route to one important thing: kindness... There are serious questions asked in this book, which provide an opportunity to discuss bullying, environmental protection, and inclusivity - all very important topics for children. We want lots and lots of kids to share in our fun and to think about their own questions, and discover the answers to them. This book will also be a useful classroom adjunct to interpersonal relationships and a key to opening the potential for student narratives.\"-- Provided by publisher.
Book
Cosmological reconstruction and Formula omittedCDM universe in Formula omitted gravity
Symmetric Teleparallel Gravity allows for the reformulation of gravity in the form of nonmetricity by vanishing the contorsion term in the generic affine connection. Our focus is on investigating a recently proposed extension of this theory in which the Lagrangian has the form f(Q, C) by incorporating the boundary term C. In this work, we first use a reconstruction approach in f(Q, C) gravity that might admit the [Formula omitted]CDM expansion history. Furthermore, we perform a novel approach for cosmological reconstruction of f(Q, C) gravity in terms of e-folding, and it shows how any FLRW cosmology can arise from a specific f(Q, C) gravity. A variety of instances are provided using this approach in which f(Q, C) gravity is reconstructed to yield the well-known cosmic evolution: [Formula omitted]CDM era, acceleration/deceleration era which is equivalent to the presence of phantom and non-phantom matter, late-time acceleration with the crossing of phantom-divide line and transient phantom era.
Journal Article
Little kids first big book of why 2
\"Following up on the best-selling Little Kids First Big Book of Why, the next book in the hit Little Kids First Big Book series features even more of the endless \"Why?\" questions preschoolers love to ask!\"--Publisher's description.
Book
My book about me, by me myself : I wrote it! I drew it!
A series of questions for the reader to answer about himself: \"I have [teeth] up top. I have [teeth] downstairs.\"
Book
Natural Questions: A Benchmark for Question Answering Research
We present the Natural Questions corpus, a question answering data set. Questions
consist of real anonymized, aggregated queries issued to the Google search
engine. An annotator is presented with a question along with a Wikipedia page
from the top 5 search results, and annotates a long answer (typically a
paragraph) and a short answer (one or more entities) if present on the page, or
marks null if no long/short answer is present. The public release consists of
307,373 training examples with single annotations; 7,830 examples with 5-way
annotations for development data; and a further 7,842 examples with 5-way
annotated sequestered as test data. We present experiments validating quality of
the data. We also describe analysis of 25-way annotations on 302 examples,
giving insights into human variability on the annotation task. We introduce
robust metrics for the purposes of evaluating question answering systems;
demonstrate high human upper bounds on these metrics; and establish baseline
results using competitive methods drawn from related literature.
Journal Article
National Geographic little kids first big book of why
Using a question-and-answer format and content grounded in a child's immediate world this books delivers information on the world around us.
CHILDBOOK
Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies
A key limitation in current datasets for
is that the required steps for answering the question are mentioned in it
. In this work, we introduce S
QA, a question answering (QA) benchmark where the required reasoning steps are
in the question, and should be inferred using a
. A fundamental challenge in this setup is how to elicit such creative questions from crowdsourcing workers, while covering a broad range of potential strategies. We propose a data collection procedure that combines term-based priming to inspire annotators, careful control over the annotator population, and adversarial filtering for eliminating reasoning shortcuts. Moreover, we annotate each question with (1) a decomposition into reasoning steps for answering it, and (2) Wikipedia paragraphs that contain the answers to each step. Overall, S
QA includes 2,780 examples, each consisting of a strategy question, its decomposition, and evidence paragraphs. Analysis shows that questions in S
QA are short, topic-diverse, and cover a wide range of strategies. Empirically, we show that humans perform well (87%) on this task, while our best baseline reaches an accuracy of ∼ 66
.
Journal Article
Can I eat that?
\"This humorous, stylized and entirely unexpected set of food facts will engage both good eaters and resisters alike. With questions both practical ('Can you eat a sea urchin?') and playful ('Do eggs grow on eggplants?'), this read-aloud text offers young children facts to share and the subtle encouragement to taste something new!\"-- Amazon.com.
Book
