source_id stringlengths 8 30 | source_year stringdate 2016-01-01 00:00:00 2022-01-01 00:00:00 | source_title stringlengths 0 176 | source_related_works listlengths 1 4 | source_paper_full listlengths 4 77 | cited_papers listlengths 1 40 |
|---|---|---|---|---|---|
Q16-1035 | 2016 | The Galactic Dependencies Treebanks: Getting More Data by Synthesizing New Languages | [
{
"section_name": "Related Work",
"paragraphs": [
"Synthetic data generation is a well-known trick for effectively training a large model on a small dataset. Abu-Mostafa reviews early work that provided \"hints\" to a learning system in the form of virtual training examples. While datasets have grown ... | [
{
"section_name": "Abstract",
"paragraphs": [
"We release Galactic Dependencies 1.0-a large set of synthetic languages not found on Earth, but annotated in Universal Dependencies format. This new resource aims to provide training and development data for NLP 491"
]
},
{
"section_name": "Un... | [
{
"paper_id": "P16-1056",
"year": 2016,
"title": "Generating Factoid Questions With Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus",
"sections": [
{
"section_name": "Uncategorized",
"paragraphs": [
"Over the past decade, large-scale supervised learn... |
D17-1013 | 2017 | Neural Machine Translation with Word Predictions | [{"section_name":"Related Work","paragraphs":["Many previous works have noticed the problem of train(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["In the encoder-decoder architecture for neural machine tr(...TRUNCATED) | [{"paper_id":"D15-1166","year":2015,"title":"Effective Approaches to Attention-based Neural Machine (...TRUNCATED) |
D17-1106 | 2017 | Mapping Instructions and Visual Observations to Actions with Reinforcement Learning | [{"section_name":"Related Work","paragraphs":["Learning to follow instructions was studied extensive(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["We propose to directly map raw visual observations and te(...TRUNCATED) | [{"paper_id":"P15-1096","year":2015,"title":"Environment-Driven Lexicon Induction for High-Level Ins(...TRUNCATED) |
D17-1141 | 2017 | Patterns of Argumentation Strategies across Topics | [{"section_name":"Related Work","paragraphs":["In addition to the work on argumentation strategies i(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["This paper presents an analysis of argumentation strategi(...TRUNCATED) | [{"paper_id":"D14-1006","year":2014,"title":"Identifying Argumentative Discourse Structures in Persu(...TRUNCATED) |
D17-1220 | 2017 | Break it Down for Me: A Study in Automated Lyric Annotation | [{"section_name":"Related Work","paragraphs":["Work on modeling of social annotations has mainly foc(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["Comprehending lyrics, as found in songs and poems, can po(...TRUNCATED) | [{"paper_id":"P15-2073","year":2015,"title":"BLEU: A Discriminative Metric for Generation Tasks with(...TRUNCATED) |
K17-1008 | 2017 | Named Entity Disambiguation for Noisy Text | [{"section_name":"Related Work","paragraphs":["Local vs Global NED Early work on Named Entity Disamb(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["We address the task of Named Entity Disambiguation (NED) (...TRUNCATED) | [{"paper_id":"N15-1026","year":2015,"title":"Personalized Page Rank for Named Entity Disambiguation"(...TRUNCATED) |
K17-1011 | 2017 | Top-Rank Enhanced Listwise Optimization for Statistical Machine Translation | [{"section_name":"Related Work","paragraphs":["The ranking problem is well studied in IR community. (...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["Pairwise ranking methods are the basis of many widely use(...TRUNCATED) | [{"paper_id":"N15-1106","year":2015,"title":"APRO: All-Pairs Ranking Optimization for MT Tuning","se(...TRUNCATED) |
K17-1039 | 2017 | Optimizing Differentiable Relaxations of Coreference Evaluation Metrics | [{"section_name":"Related work","paragraphs":["Mention ranking and entity centricity are two main st(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["Coreference evaluation metrics are hard to optimize direc(...TRUNCATED) | [{"paper_id":"N16-1114","year":2016,"title":"Learning Global Features for Coreference Resolution","s(...TRUNCATED) |
K17-1040 | 2017 | Neural Structural Correspondence Learning for Domain Adaptation | [{"section_name":"Background and Contribution","paragraphs":["Domain adaptation is a fundamental, lo(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["We introduce a neural network model that marries together(...TRUNCATED) | [{"paper_id":"P15-1071","year":2015,"title":"Unsupervised Cross-Domain Word Representation Learning"(...TRUNCATED) |
K17-2011 | 2017 | Seq2seq for Morphological Reinflection: When Deep Learning Fails | [{"section_name":"Related Work","paragraphs":["Morphological inflection has a long-tradition in natu(...TRUNCATED) | [{"section_name":"Abstract","paragraphs":["Recent studies showed that the sequenceto-sequence (seq2s(...TRUNCATED) | [{"paper_id":"N15-1107","year":2015,"title":"Paradigm classification in supervised learning of morph(...TRUNCATED) |
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