A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
ELI5: Long Form Question Answering
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Preserved Fulltext
We introduce the first large-scale corpus for long-form question answering, a task requiring elaborate and in-depth answers to openended questions. ...
Compared to existing datasets, ELI5 comprises diverse questions requiring multi-sentence answers. We provide a large set of web documents to help answer the question. ...
ELI5 contains long-form answers with an average length of 6.6 sentences, or 130 words. ...
doi:10.18653/v1/p19-1346
dblp:conf/acl/FanJPGWA19
fatcat:jpnqlphrt5d7fdidry5cqx4usy
Hurdles to Progress in Long-form Question Answering
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The task of long-form question answering (LFQA) involves retrieving documents relevant to a given question and using them to generate a paragraph-length answer. ...
ELI5 contains significant train / validation overlap, as at least 81% of ELI5 validation questions occur in paraphrased form in the training set; (3) ROUGE-L is not an informative metric of generated answer ...
Longer outputs get higher ROUGE-L A summary of the major hurdles (a-d) to progress in long-form question answering with ELI5. ...
arXiv:2103.06332v2
fatcat:gdogrseicrbefbshlfm7nnv5zy
How Do We Answer Complex Questions: Discourse Structure of Long-form Answers
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
To better understand this complex and understudied task, we study the functional structure of long-form answers collected from three datasets, ELI5, WebGPT and Natural Questions. ...
Long-form answers, consisting of multiple sentences, can provide nuanced and comprehensive answers to a broader set of questions. ...
information presented in a long-form answer. ...
arXiv:2203.11048v1
fatcat:dejy4jem3fantbna2qomvaltiy
New Methods Metrics for LFQA tasks
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Long-form question answering (LFQA) tasks require retrieving the documents pertinent to a query, using them to form a paragraph-length answer. ...
Despite considerable progress in LFQA modeling, fundamental issues impede its progress: i) train/validation/test dataset overlap, ii) absence of automatic metrics and iii) generated answers not being " ...
Enter long-form question answering (LFQA), which remains a fundamental challenge in natural language processing (NLP). ...
arXiv:2112.13432v1
fatcat:neirmp7a2rcsvcslme6wujtqeu
GooAQ: Open Question Answering with Diverse Answer Types
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
This yields a rich space of answer types, containing both textual answers (short and long) as well as more structured ones such as collections. ...
While day-to-day questions come with a variety of answer types, the current question-answering (QA) literature has failed to adequately address the answer diversity of questions. ...
One notable QA dataset with long-form responses is ELI5 (Fan et al., 2019; Krishna et al., 2021) , containing questions/answers mined from Reddit forums. ...
arXiv:2104.08727v2
fatcat:zloaxrwk2re47afc7luqacf5my
WebGPT: Browser-assisted question-answering with human feedback
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We fine-tune GPT-3 to answer long-form questions using a text-based web-browsing environment, which allows the model to search and navigate the web. ...
We train and evaluate our models on ELI5, a dataset of questions asked by Reddit users. ...
For both demonstrations and comparisons, the vast majority of questions were taken from ELI5 [Fan et al., 2019] , a dataset of long-form questions. ...
arXiv:2112.09332v2
fatcat:qmzgb4x6fnfynhewen4bor6wvu
Teaching language models to support answers with verified quotes
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
We measure the performance of GopherCite by conducting human evaluation of answers to questions in a subset of the NaturalQuestions and ELI5 datasets. ...
Recent large language models often answer factual questions correctly. ...
" and "long-answer" fields. ...
arXiv:2203.11147v1
fatcat:xcyia7pag5ayxmbnhbvjkzyrc4
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
2019
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
For two generative tasks with very long text input, long-form question answering and multidocument summarization, feeding graph representations as input can achieve better performance than using retrieved ...
Lattice cnns for matching based chinese question answering. arXiv preprint arXiv:1902.09087. Smith. 2018a. ...
Eli5:
Long form question answering. In Proceedings of
ACL 2019.
Angela Fan, Mike Lewis, and Yann Dauphin. 2018. Hi-
erarchical neural story generation. arXiv preprint
arXiv:1805.04833. ...
doi:10.18653/v1/d19-1428
dblp:conf/emnlp/FanGBB19
fatcat:u4uju6ob7rcnvd3mqcavkgc6ey
Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
For two generative tasks with very long text input, long-form question answering and multi-document summarization, feeding graph representations as input can achieve better performance than using retrieved ...
Query-based open-domain NLP tasks require information synthesis from long and diverse web results. ...
Eli5:
Long form question answering. In Proceedings of
ACL 2019.
Angela Fan, Mike Lewis, and Yann Dauphin. 2018. Hi-
erarchical neural story generation. In ACL. ...
arXiv:1910.08435v1
fatcat:2epldhegyfbsxmqtb5jngtfgra
Improving Conditioning in Context-Aware Sequence to Sequence Models
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this work, we focus on cases where generation is conditioned on both a short query and a long context, such as abstractive question answering or document-level translation. ...
ELI5 : ELI5 Long Form Question Answering We first apply our approach to the recently published ELI5 dataset (Fan et al. 2019) for LFQA. ...
We apply our approach to three context-aware seq2seq tasks: neural machine translation with document-level context, long form question answering, where the system needs to provide a paragraph-length answer ...
arXiv:1911.09728v1
fatcat:ud5cahaphndcdoag4i5ozmsvm4
Discourse Comprehension: A Question Answering Framework to Represent Sentence Connections
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2111.00701v1 fatcat:jq4xylsuo5htfbwgbw5t25t5t4
DCQA captures both discourse and semantic links between sentences in the form of free-form, open-ended questions. ...
all) requires high cognitive load for annotators over long documents. ...
The most related dataset we found is ELI5 (Fan et al., 2019) , a dataset for long-form question answering. ...
arXiv:2111.00701v2
fatcat:5mklcwac7fg35nk2r4cc5thatq
CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In our experiments, we find that pre-training question-answering models on our Common Crawl Question Answering dataset (CCQA) achieves promising results in zero-shot, low resource and fine-tuned settings ...
With the rise of large-scale pre-trained language models, open-domain question-answering (ODQA) has become an important research topic in NLP. ...
ELI5, introduced by Fan et al. ( 2019 ), constitutes the first large-scale long-form dataset for open-ended question-answering. ...
arXiv:2110.07731v2
fatcat:a7iutxmskzhy3hnsk74g7zu5rm
KILT: a Benchmark for Knowledge Intensive Language Tasks
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2021 pre-print arXiv:2009.02252v3 fatcat:m75l4xywqnbcxgvrdctu2muu7uOther Versions
Challenging problems such as open-domain question answering, fact checking, slot filling and entity linking require access to large, external knowledge sources. ...
We find that a shared dense vector index coupled with a seq2seq model is a strong baseline, outperforming more tailor-made approaches for fact checking, open-domain question answering and dialogue, and ...
ELI5:
long form question answering. ...
arXiv:2009.02252v4
fatcat:44gk5nyhrvckriymi7wsrxze7m
The Web Is Your Oyster – Knowledge-Intensive NLP against a Very Large Web Corpus
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Hurdles to progress in long-form question answer-
ing. ...
ELI5:
Sebastian Borgeaud, Arthur Mensch, Jordan Hoff- Long form question answering. ...
arXiv:2112.09924v1
fatcat:khcg2qe2trho3b7useq5navfye
Knowledge Infused Decoding
[article]
2022
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Our experiments find baseline methods tend to generate off-topic and hallucinatory answers when the expected answer length is long (e.g., ELI5 and PIQA). ...
We first sample 200 ELI5 test set questions and generate answers of various lengths {80, 100, ..., 260} (260 is the average sequence length in training set) with beam search, sampling, reflective (West ...
Answer is from 1-not similar at all to 7-very much similar). ...
arXiv:2204.03084v1
fatcat:t3r6mutr7nbflg7uovqo2waapi
« Previous
Showing results 1 — 15 out of 89 results