id stringclasses 100
values | document stringclasses 100
values | gold_summary stringlengths 76 223 | aspect_selected stringclasses 3
values | prompt_type stringclasses 2
values | objective stringclasses 2
values | prompt stringlengths 2.5k 16.7k | source_dataset stringclasses 1
value | prompt_variant_id int64 0 2 | section stringclasses 1
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|---|---|---|---|---|---|---|---|---|---|
2021.acl-long.67 | Bilingual lexicons map words in one language to their translations in another , and are typically induced by learning linear projections to align monolingual word embedding spaces . In this paper , we show it is possible to produce much higher quality lexicons with methods that combine ( 1 ) unsupervised bitext mining ... | The proposed method achieves the state-of-the-art in the bilingual lexical induction task while keeping the interpretability of their pipeline. | outcome | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
2020.acl-main.75 | Humor plays an important role in human languages and it is essential to model humor when building intelligence systems . Among different forms of humor , puns perform wordplay for humorous effects by employing words with double entendre and high phonetic similarity . However , identifying and modeling puns are challeng... | Puns involve implicit semantic or phonological tricks however there is no general framework to model these two types of signals as a whole. | challenge | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Extract a short summary of the core issue... | sobamchan/aclsum | 2 | full_paper |
P10-1139 | There is a growing research interest in opinion retrieval as on-line users ' opinions are becoming more and more popular in business , social networks , etc . Practically speaking , the goal of opinion retrieval is to retrieve documents , which entail opinions or comments , relevant to a target subject specified by the... | Existing approaches to the opinion retrieval task represent documents using bag-of-words disregarding contextual information between an opinion and its corresponding text. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 0 | full_paper |
P16-1067 | This paper proposes an unsupervised approach for segmenting a multiauthor document into authorial components . The key novelty is that we utilize the sequential patterns hidden among document elements when determining their authorships . For this purpose , we adopt Hidden Markov Model ( HMM ) and construct a sequential... | Experiments with artificial and authentic scientific document datasets show that the proposed model outperforms existing methods and also be able to provide confidence scores. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
P07-1026 | Convolution tree kernel has shown promising results in semantic role classification . However , it only carries out hard matching , which may lead to over-fitting and less accurate similarity measure . To remove the constraint , this paper proposes a grammardriven convolution tree kernel for semantic role classificatio... | They propose to integrate a linguistically motivated grammar-baed convolution tree kernel into a standard tree kernel to achieve better substructure matching and tree node matching. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the method or approach the autho... | sobamchan/aclsum | 0 | full_paper |
N18-1108 | Recurrent neural networks ( RNNs ) have achieved impressive results in a variety of linguistic processing tasks , suggesting that they can induce non-trivial properties of language . We investigate here to what extent RNNs learn to track abstract hierarchical syntactic structure . We test whether RNNs trained with a ge... | The RNNs trained on an LM objective can solve long-distance agreement problems well even on nonsensical sentences consistently across languages indicating their deeper grammatical competence. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the outcomes in a sentence.
---
Docum... | sobamchan/aclsum | 1 | full_paper |
N03-1024 | We describe a syntax-based algorithm that automatically builds Finite State Automata ( word lattices ) from semantically equivalent translation sets . These FSAs are good representations of paraphrases . They can be used to extract lexical and syntactic paraphrase pairs and to generate new , unseen sentences that expre... | They propose a syntax-based algorithm that builds Finite State Automata from translation sets which are good representations of paraphrases. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
P16-1067 | This paper proposes an unsupervised approach for segmenting a multiauthor document into authorial components . The key novelty is that we utilize the sequential patterns hidden among document elements when determining their authorships . For this purpose , we adopt Hidden Markov Model ( HMM ) and construct a sequential... | There is no method for multiauthor segmentation of a document into author components which can be applied to authorship verification, plagiarism detection and author attribution. | challenge | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
E06-1014 | Probabilistic Latent Semantic Analysis ( PLSA ) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis ( LSA ) . However , the parameters of a PLSA model are trained using the Expectation Maximization ( EM ) algorithm , and as a result , the trained model is d... | They propose to use Latent Semantic Analysis to initialize probabilistic latent semantic analysis models, EM algorithm is further used to refine the initial estimate. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
How do the authors address the problem? Pr... | sobamchan/aclsum | 1 | full_paper |
2020.emnlp-main.505 | News headline generation aims to produce a short sentence to attract readers to read the news . One news article often contains multiple keyphrases that are of interest to different users , which can naturally have multiple reasonable headlines . However , most existing methods focus on the single headline generation .... | They propose a multi-source transformer decoder and train it using a new large-scale keyphrase-aware news headline corpus built from a search engine. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
D18-1065 | In this paper we show that a simple beam approximation of the joint distribution between attention and output is an easy , accurate , and efficient attention mechanism for sequence to sequence learning . The method combines the advantage of sharp focus in hard attention and the implementation ease of soft attention . O... | The proposed approach outperforms soft attention models and recent hard attention and Sparsemax models on five translation tasks and also on morphological inflection tasks. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
P19-1352 | Word embedding is central to neural machine translation ( NMT ) , which has attracted intensive research interest in recent years . In NMT , the source embedding plays the role of the entrance while the target embedding acts as the terminal . These layers occupy most of the model parameters for representation learning ... | They propose a language independet method where a model shares embeddings between source and target only when words have some common characteristics. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
How do the authors address the problem? Pr... | sobamchan/aclsum | 1 | full_paper |
2020.emnlp-main.384 | Word embedding models are typically able to capture the semantics of words via the distributional hypothesis , but fail to capture the numerical properties of numbers that appear in a text . This leads to problems with numerical reasoning involving tasks such as question answering . We propose a new methodology to assi... | They propose a deterministic technique to learn numerical embeddings where cosine similarity reflects the actual distance and a regularization approach for a contextual setting. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 2 | full_paper |
D10-1083 | Part-of-speech ( POS ) tag distributions are known to exhibit sparsity -a word is likely to take a single predominant tag in a corpus . Recent research has demonstrated that incorporating this sparsity constraint improves tagging accuracy . However , in existing systems , this expansion come with a steep increase in mo... | They propose an unsupervised method that directly incorporates a one-tag-per-word assumption into a HMM-based model. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Outline the methodology used by the author... | sobamchan/aclsum | 2 | full_paper |
D15-1054 | Sponsored search is at the center of a multibillion dollar market established by search technology . Accurate ad click prediction is a key component for this market to function since the pricing mechanism heavily relies on the estimation of click probabilities . Lexical features derived from the text of both the query ... | They propose several joint word embedding methods to leverage positive and negative click feedback which put query vectors close to relevant ad vectors. | approach | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the method.
---
Document:
Spons... | sobamchan/aclsum | 0 | full_paper |
E17-1022 | We propose UDP , the first training-free parser for Universal Dependencies ( UD ) . Our algorithm is based on PageRank and a small set of head attachment rules . It features two-step decoding to guarantee that function words are attached as leaf nodes . The parser requires no training , and it is competitive with a del... | For dependency parsing, unsupervised methods struggle with learning relations that match conventions of the test data and supervised counterparts suffer from word order target adaptation. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the problem in short form.
---
Docu... | sobamchan/aclsum | 1 | full_paper |
P98-1081 | In this paper we examine how the differences in modelling between different data driven systems performing the same NLP task can be exploited to yield a higher accuracy than the best individual system . We do this by means of an experiment involving the task of morpho-syntactic wordclass tagging . Four well-known tagge... | Different data driven approaches tend to produce different errors and their qualities are limited due to the learning method and available training material. | challenge | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
E09-1032 | We explore the problem of resolving the second person English pronoun you in multi-party dialogue , using a combination of linguistic and visual features . First , we distinguish generic and referential uses , then we classify the referential uses as either plural or singular , and finally , for the latter cases , we i... | They show that visual features can help distinguish the word "you" in multi-party conversations. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
E17-1060 | We investigate the generation of onesentence Wikipedia biographies from facts derived from Wikidata slot-value pairs . We train a recurrent neural network sequence-to-sequence model with attention to select facts and generate textual summaries . Our model incorporates a novel secondary objective that helps ensure it ge... | The proposed model achieves 41 BLEU score outperforming the baseline model and human annotators prefer the 40% of outputs as good as Wikipedia gold references. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 1 | full_paper |
2020.acl-main.75 | Humor plays an important role in human languages and it is essential to model humor when building intelligence systems . Among different forms of humor , puns perform wordplay for humorous effects by employing words with double entendre and high phonetic similarity . However , identifying and modeling puns are challeng... | They propose to jointly model contextualized word embeddings and phonological word representations by breaking each word into a sequence of phonemes for pun detection. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 1 | full_paper |
2021.eacl-main.251 | Current state-of-the-art systems for joint entity relation extraction ( Luan et al . , 2019 ; Wadden et al . , 2019 ) usually adopt the multi-task learning framework . However , annotations for these additional tasks such as coreference resolution and event extraction are always equally hard ( or even harder ) to obtai... | Current joint entity relation extraction models follow a multitask learning setup however datasets with multiple types of annotation are not available for many domains. | challenge | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 0 | full_paper |
2022.acl-long.393 | Motivated by the success of T5 ( Text-To-Text Transfer Transformer ) in pre-trained natural language processing models , we propose a unified-modal SpeechT5 framework that explores the encoder-decoder pre-training for self-supervised speech / text representation learning . The SpeechT5 framework consists of a shared en... | Existing speech pre-training methods ignore the importance of textual data and solely depend on encoders leaving the decoder out of pre-training for generation tasks. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
2021.eacl-main.251 | Current state-of-the-art systems for joint entity relation extraction ( Luan et al . , 2019 ; Wadden et al . , 2019 ) usually adopt the multi-task learning framework . However , annotations for these additional tasks such as coreference resolution and event extraction are always equally hard ( or even harder ) to obtai... | Current joint entity relation extraction models follow a multitask learning setup however datasets with multiple types of annotation are not available for many domains. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the problem in short form.
---
Docu... | sobamchan/aclsum | 1 | full_paper |
P02-1051 | Named entity phrases are some of the most difficult phrases to translate because new phrases can appear from nowhere , and because many are domain specific , not to be found in bilingual dictionaries . We present a novel algorithm for translating named entity phrases using easily obtainable monolingual and bilingual re... | They propose an algorithm for Arabic-English named entity translation which uses easily obtainable monolingual and bilingual resources and a limited amount of hard-to-obtain bilingual resources. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
P10-1072 | We present a game-theoretic model of bargaining over a metaphor in the context of political communication , find its equilibrium , and use it to rationalize observed linguistic behavior . We argue that game theory is well suited for modeling discourse as a dynamic resulting from a number of conflicting pressures , and ... | They show that the proposed framework can rationalize political communications with the use of extended metaphors based on the characteristics of the setting. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
N09-1072 | Automatically extracting social meaning and intention from spoken dialogue is an important task for dialogue systems and social computing . We describe a system for detecting elements of interactional style : whether a speaker is awkward , friendly , or flirtatious . We create and use a new spoken corpus of 991 4-minut... | They found several gender dependent and independent phenomena in conversations related to the speed of speaking, laughing or asking questions. | outcome | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
What are the primary outcomes of the study?... | sobamchan/aclsum | 1 | full_paper |
2021.acl-long.67 | Bilingual lexicons map words in one language to their translations in another , and are typically induced by learning linear projections to align monolingual word embedding spaces . In this paper , we show it is possible to produce much higher quality lexicons with methods that combine ( 1 ) unsupervised bitext mining ... | Existing methods to induce bilingual lexicons use linear projections to align word embeddings that are based on unrealistic simplifying assumptions. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
P18-1159 | While sophisticated neural-based techniques have been developed in reading comprehension , most approaches model the answer in an independent manner , ignoring its relations with other answer candidates . This problem can be even worse in open-domain scenarios , where candidates from multiple passages should be combine... | The proposed model can fuse answer candidates from multiple candidates and significantly outperform existing models on two open-domain reading comprehension tasks. | outcome | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
P18-1256 | We introduce the task of predicting adverbial presupposition triggers such as also and again . Solving such a task requires detecting recurring or similar events in the discourse context , and has applications in natural language generation tasks such as summarization and dialogue systems . We create two new datasets f... | The proposed model outperforms baselines including an LSTM-based language model on most of the triggers on the two datasets. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the results.
---
Document:
We in... | sobamchan/aclsum | 0 | full_paper |
D19-1098 | Pre-training Transformer from large-scale raw texts and fine-tuning on the desired task have achieved state-of-the-art results on diverse NLP tasks . However , it is unclear what the learned attention captures . The attention computed by attention heads seems not to match human intuitions about hierarchical structures ... | This is unclear what attention heads in pre-training transformers models capture and it seems not to match human intuitions about hierarchical structures. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
State the difficulty of the study.
---
D... | sobamchan/aclsum | 2 | full_paper |
P18-1256 | We introduce the task of predicting adverbial presupposition triggers such as also and again . Solving such a task requires detecting recurring or similar events in the discourse context , and has applications in natural language generation tasks such as summarization and dialogue systems . We create two new datasets f... | Adverbaial triggers indicate the event recurrence, continuation, or termination in the discourse context and are frequently found in English but there are few related works. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the problem in short form.
---
Docu... | sobamchan/aclsum | 1 | full_paper |
D12-1011 | Existing techniques for disambiguating named entities in text mostly focus on Wikipedia as a target catalog of entities . Yet for many types of entities , such as restaurants and cult movies , relational databases exist that contain far more extensive information than Wikipedia . This paper introduces a new task , call... | Existing approaches to disambiguate named entities solely use Wikipedia as a catalogue however Many kinds of named entities are missed in Wikipedia. | challenge | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 2 | full_paper |
N09-1032 | Domain adaptation is an important problem in named entity recognition ( NER ) . NER classifiers usually lose accuracy in the domain transfer due to the different data distribution between the source and the target domains . The major reason for performance degrading is that each entity type often has lots of domainspec... | The proposed model improves the performance on the English and Chinese corpus across domains especially on each NE type recognition. | outcome | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
D17-1220 | Comprehending lyrics , as found in songs and poems , can pose a challenge to human and machine readers alike . This motivates the need for systems that can understand the ambiguity and jargon found in such creative texts , and provide commentary to aid readers in reaching the correct interpretation . We introduce the t... | They evaluate translation and retrieval models with automatic and human evaluation and show that different models capture different aspects well. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Describe the conclusions briefly.
---
Docu... | sobamchan/aclsum | 2 | full_paper |
P08-1116 | This paper proposes a novel method that exploits multiple resources to improve statistical machine translation ( SMT ) based paraphrasing . In detail , a phrasal paraphrase table and a feature function are derived from each resource , which are then combined in a log-linear SMT model for sentence-level paraphrase gener... | They show that using multiple resources enhances paraphrase generation quality in precision on phrase and sentence level especially when they are similar to user queries. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 1 | full_paper |
2021.emnlp-main.765 | The clustering-based unsupervised relation discovery method has gradually become one of the important methods of open relation extraction ( OpenRE ) . However , high-dimensional vectors can encode complex linguistic information which leads to the problem that the derived clusters can not explicitly align with the relat... | Even though high-dimensional vectors that can encode complex information used for relation extraction are not guaranteed to be consistent with relational semantic similarity. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 2 | full_paper |
W06-1672 | We present two discriminative methods for name transliteration . The methods correspond to local and global modeling approaches in modeling structured output spaces . Both methods do not require alignment of names in different languages -their features are computed directly from the names themselves . We perform an exp... | The name transliteration task aims to transcribe extracted names into English, and since current extraction systems are fairly fast, applicable techniques for transliteration are limited. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
P01-1026 | We propose a method to generate large-scale encyclopedic knowledge , which is valuable for much NLP research , based on the Web . We first search the Web for pages containing a term in question . Then we use linguistic patterns and HTML structures to extract text fragments describing the term . Finally , we organize ex... | Existing methods that extract encyclopedic knowledge from the Web output unorganized clusters of term descriptions not necessarily related to explicit criteria while clustering is performed. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
What issue is this paper about?
---
Docu... | sobamchan/aclsum | 0 | full_paper |
H05-1023 | Most statistical translation systems are based on phrase translation pairs , or " blocks " , which are obtained mainly from word alignment . We use blocks to infer better word alignment and improved word alignment which , in turn , leads to better inference of blocks . We propose two new probabilistic models based on t... | They propose to use phrase translation pairs to get better word alignments using two new probabilistic models based on EM-algorithm that localizes the alignments. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 2 | full_paper |
P19-1081 | We study a conversational reasoning model that strategically traverses through a largescale common fact knowledge graph ( KG ) to introduce engaging and contextually diverse entities and attributes . For this study , we collect a new Open-ended Dialog ↔ KG parallel corpus called OpenDialKG , where each utterance from 1... | They provide an open-ended dialogue corpus where each utterance is annotated with entities and paths and propose a model that works on this data structure. | approach | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the method.
---
Document:
We st... | sobamchan/aclsum | 0 | full_paper |
E17-1022 | We propose UDP , the first training-free parser for Universal Dependencies ( UD ) . Our algorithm is based on PageRank and a small set of head attachment rules . It features two-step decoding to guarantee that function words are attached as leaf nodes . The parser requires no training , and it is competitive with a del... | The proposed linguistically sound method performs competitively with a delexicalized transfer system while having few parameters and robustness to domain changes across languages. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the outcomes in a sentence.
---
Docum... | sobamchan/aclsum | 1 | full_paper |
D08-1038 | How can the development of ideas in a scientific field be studied over time ? We apply unsupervised topic modeling to the ACL Anthology to analyze historical trends in the field of Computational Linguistics from 1978 to 2006 . We induce topic clusters using Latent Dirichlet Allocation , and examine the strength of each... | How topics or ideas have developed over time in NLP community remains unknown while there are analysis over the ACL anthology citation graph. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
N09-1062 | Tree substitution grammars ( TSGs ) are a compelling alternative to context-free grammars for modelling syntax . However , many popular techniques for estimating weighted TSGs ( under the moniker of Data Oriented Parsing ) suffer from the problems of inconsistency and over-fitting . We present a theoretically principle... | The proposed model learns local structures for latent linguistic phenomena outperforms standard methods and is comparable to state-of-the-art methods on small data. | outcome | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the main results or outcomes repo... | sobamchan/aclsum | 0 | full_paper |
P16-1177 | We present a pairwise context-sensitive Autoencoder for computing text pair similarity . Our model encodes input text into context-sensitive representations and uses them to compute similarity between text pairs . Our model outperforms the state-of-the-art models in two semantic retrieval tasks and a contextual word si... | The proposed model outperforms the state-of-the-art models in two retrieval and word similarity tasks and an unsupervised version performs comparable with several supervised baselines. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the outcomes in a sentence.
---
Docum... | sobamchan/aclsum | 1 | full_paper |
2020.acl-main.528 | Recently , many works have tried to augment the performance of Chinese named entity recognition ( NER ) using word lexicons . As a representative , Lattice-LSTM ( Zhang and Yang , 2018 ) has achieved new benchmark results on several public Chinese NER datasets . However , Lattice-LSTM has a complex model architecture .... | The proposed efficient character-based LSTM method with lexical features achieves 6.15 times faster inference speed and better performance than previous models. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
H05-1023 | Most statistical translation systems are based on phrase translation pairs , or " blocks " , which are obtained mainly from word alignment . We use blocks to infer better word alignment and improved word alignment which , in turn , leads to better inference of blocks . We propose two new probabilistic models based on t... | They propose to use phrase translation pairs to get better word alignments using two new probabilistic models based on EM-algorithm that localizes the alignments. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
How do the authors address the problem? Pr... | sobamchan/aclsum | 1 | full_paper |
N15-1159 | This paper describes a simple and principled approach to automatically construct sentiment lexicons using distant supervision . We induce the sentiment association scores for the lexicon items from a model trained on a weakly supervised corpora . Our empirical findings show that features extracted from such a machine-l... | Using the obtained lexicon with an existing model achieves the state-of-the-art on the SemEval-13 message level task and outperforms baseline models in several other datasets. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the outcomes in a sentence.
---
Docum... | sobamchan/aclsum | 1 | full_paper |
P10-1072 | We present a game-theoretic model of bargaining over a metaphor in the context of political communication , find its equilibrium , and use it to rationalize observed linguistic behavior . We argue that game theory is well suited for modeling discourse as a dynamic resulting from a number of conflicting pressures , and ... | Metaphors used in political arguments provide elaborate conceptual correspondences with a tendency of politicians to be compelled by the rival's metaphorical framework to be explained. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
D09-1115 | Current system combination methods usually use confusion networks to find consensus translations among different systems . Requiring one-to-one mappings between the words in candidate translations , confusion networks have difficulty in handling more general situations in which several words are connected to another se... | They show that their approach significantly outperforms the state-of-the-art confusion-network-based systems on Chinese-to-English translation tasks. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
P10-1077 | Prior use of machine learning in genre classification used a list of labels as classification categories . However , genre classes are often organised into hierarchies , e.g. , covering the subgenres of fiction . In this paper we present a method of using the hierarchy of labels to improve the classification accuracy .... | They propose a structural reformulation of the Support Vector Machine to take hierarchical information of genres into account by using similarities between different genres. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Outline the methodology used by the author... | sobamchan/aclsum | 2 | full_paper |
H05-1023 | Most statistical translation systems are based on phrase translation pairs , or " blocks " , which are obtained mainly from word alignment . We use blocks to infer better word alignment and improved word alignment which , in turn , leads to better inference of blocks . We propose two new probabilistic models based on t... | Automatic word alignment used in statistical machine translations, does not achieve satisfactory performance in some language pairs such as because of the limitations of HMMs. | challenge | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 2 | full_paper |
D18-1065 | In this paper we show that a simple beam approximation of the joint distribution between attention and output is an easy , accurate , and efficient attention mechanism for sequence to sequence learning . The method combines the advantage of sharp focus in hard attention and the implementation ease of soft attention . O... | They propose a method to approximate the joint attention-output distribution which provides sharp attention as hard attention and easy implementation as soft attention. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 1 | full_paper |
N18-1108 | Recurrent neural networks ( RNNs ) have achieved impressive results in a variety of linguistic processing tasks , suggesting that they can induce non-trivial properties of language . We investigate here to what extent RNNs learn to track abstract hierarchical syntactic structure . We test whether RNNs trained with a ge... | They introduce a probing method for syntactic abilities to evaluate long-distance agreement on standard and nonsensical sentences in multiple languages with different morphological systems. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Outline the methodology used by the author... | sobamchan/aclsum | 2 | full_paper |
P17-1024 | In this paper , we aim to understand whether current language and vision ( LaVi ) models truly grasp the interaction between the two modalities . To this end , we propose an extension of the MS-COCO dataset , FOIL-COCO , which associates images with both correct and ' foil ' captions , that is , descriptions of the ima... | Despite the success of language and vision models on visual question answering tasks, what these models are learning remains unknown because of coarse-grained datasets. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
State the difficulty of the study.
---
D... | sobamchan/aclsum | 2 | full_paper |
P01-1026 | We propose a method to generate large-scale encyclopedic knowledge , which is valuable for much NLP research , based on the Web . We first search the Web for pages containing a term in question . Then we use linguistic patterns and HTML structures to extract text fragments describing the term . Finally , we organize ex... | Existing methods that extract encyclopedic knowledge from the Web output unorganized clusters of term descriptions not necessarily related to explicit criteria while clustering is performed. | challenge | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
From the following paper excerpt, summari... | sobamchan/aclsum | 0 | full_paper |
2020.acl-main.443 | There is an increasing interest in studying natural language and computer code together , as large corpora of programming texts become readily available on the Internet . For example , StackOverflow currently has over 15 million programming related questions written by 8.5 million users . Meanwhile , there is still a l... | Resources and fundamental techniques are missing for identifying software-related named entities such as variable names or application names within natural language texts. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 2 | full_paper |
2020.acl-main.282 | The International Classification of Diseases ( ICD ) provides a standardized way for classifying diseases , which endows each disease with a unique code . ICD coding aims to assign proper ICD codes to a medical record . Since manual coding is very laborious and prone to errors , many methods have been proposed for the ... | The proposed model outperforms state-of-the-art methods on two widely used datasets. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
2021.emnlp-main.411 | Language representations are known to carry certain associations ( e.g. , gendered connotations ) which may lead to invalid and harmful predictions in downstream tasks . While existing methods are effective at mitigating such unwanted associations by linear projection , we argue that they are too aggressive : not only ... | NLI-based evaluation on gender-occupation associations shows that the proposed approach is well-balanced ensuring semantic information is retained in the embeddings while mitigating biases. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the outcomes in a sentence.
---
Docum... | sobamchan/aclsum | 1 | full_paper |
E17-1060 | We investigate the generation of onesentence Wikipedia biographies from facts derived from Wikidata slot-value pairs . We train a recurrent neural network sequence-to-sequence model with attention to select facts and generate textual summaries . Our model incorporates a novel secondary objective that helps ensure it ge... | They propose a recurrent neural network sequence-to-sequence model with an attention mechanism trained on a multi-task autoencoding objective to generate one-sentence Wikipedia biographies from Wikidata. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 2 | full_paper |
D09-1072 | We propose a new model for unsupervised POS tagging based on linguistic distinctions between open and closed-class items . Exploiting notions from current linguistic theory , the system uses far less information than previous systems , far simpler computational methods , and far sparser descriptions in learning context... | Current approaches tackle unsupervised POS tagging as a sequential labelling problem and require a complete knowledge of the lexicon. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
D09-1115 | Current system combination methods usually use confusion networks to find consensus translations among different systems . Requiring one-to-one mappings between the words in candidate translations , confusion networks have difficulty in handling more general situations in which several words are connected to another se... | They propose to use lattices to combine systems that enable to process of a sequence of words rather than one word that can mitigate degeneration. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
E17-1022 | We propose UDP , the first training-free parser for Universal Dependencies ( UD ) . Our algorithm is based on PageRank and a small set of head attachment rules . It features two-step decoding to guarantee that function words are attached as leaf nodes . The parser requires no training , and it is competitive with a del... | The proposed linguistically sound method performs competitively with a delexicalized transfer system while having few parameters and robustness to domain changes across languages. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 1 | full_paper |
N09-1072 | Automatically extracting social meaning and intention from spoken dialogue is an important task for dialogue systems and social computing . We describe a system for detecting elements of interactional style : whether a speaker is awkward , friendly , or flirtatious . We create and use a new spoken corpus of 991 4-minut... | They found several gender dependent and independent phenomena in conversations related to the speed of speaking, laughing or asking questions. | outcome | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
P02-1051 | Named entity phrases are some of the most difficult phrases to translate because new phrases can appear from nowhere , and because many are domain specific , not to be found in bilingual dictionaries . We present a novel algorithm for translating named entity phrases using easily obtainable monolingual and bilingual re... | They propose an algorithm for Arabic-English named entity translation which uses easily obtainable monolingual and bilingual resources and a limited amount of hard-to-obtain bilingual resources. | approach | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the approach described.
---
Document... | sobamchan/aclsum | 1 | full_paper |
2021.naacl-main.72 | Multi-layer multi-head self-attention mechanism is widely applied in modern neural language models . Attention redundancy has been observed among attention heads but has not been deeply studied in the literature . Using BERT-base model as an example , this paper provides a comprehensive study on attention redundancy wh... | They perform token and sentence level analysis on redundancy matrices from pre-trained and fine-tuned BERT-base models and further propose a pruning method based on findings. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 1 | full_paper |
2021.naacl-main.458 | Non-autoregressive Transformer is a promising text generation model . However , current non-autoregressive models still fall behind their autoregressive counterparts in translation quality . We attribute this accuracy gap to the lack of dependency modeling among decoder inputs . In this paper , we propose CNAT , which ... | The proposed model achieves state-of-the-art without knowledge distillation and a competitive decoding speedup with an interactive-based model when coupled with knowledge distillation and reranking techniques. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
D18-1065 | In this paper we show that a simple beam approximation of the joint distribution between attention and output is an easy , accurate , and efficient attention mechanism for sequence to sequence learning . The method combines the advantage of sharp focus in hard attention and the implementation ease of soft attention . O... | The proposed approach outperforms soft attention models and recent hard attention and Sparsemax models on five translation tasks and also on morphological inflection tasks. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the results.
---
Document:
In th... | sobamchan/aclsum | 0 | full_paper |
E17-1110 | The growing demand for structured knowledge has led to great interest in relation extraction , especially in cases with limited supervision . However , existing distance supervision approaches only extract relations expressed in single sentences . In general , cross-sentence relation extraction is under-explored , even... | Experiments on extracting drug-gene interactions from biomedical literature show that the proposed method doubles the performance of single-sentence extraction methods. | outcome | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the main results or outcomes repo... | sobamchan/aclsum | 0 | full_paper |
P19-1252 | In this paper , we investigate the importance of social network information compared to content information in the prediction of a Twitter user 's occupational class . We show that the content information of a user 's tweets , the profile descriptions of a user 's follower / following community , and the user 's social... | Existing systems only use limited information from the tweets network to perform occupation classification. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
What issue is this paper about?
---
Docu... | sobamchan/aclsum | 0 | full_paper |
P98-1081 | In this paper we examine how the differences in modelling between different data driven systems performing the same NLP task can be exploited to yield a higher accuracy than the best individual system . We do this by means of an experiment involving the task of morpho-syntactic wordclass tagging . Four well-known tagge... | They propose to combine four different modelling methods for the task of morpho-syntactic wordclass tagging by using several voting strategies and second stage classifiers. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Outline the methodology used by the author... | sobamchan/aclsum | 2 | full_paper |
P01-1026 | We propose a method to generate large-scale encyclopedic knowledge , which is valuable for much NLP research , based on the Web . We first search the Web for pages containing a term in question . Then we use linguistic patterns and HTML structures to extract text fragments describing the term . Finally , we organize ex... | They propose to use word senses and domains for organizing extracted term descriptions on questions extracted from the Web to improve the quality. | approach | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the approach described.
---
Document... | sobamchan/aclsum | 1 | full_paper |
P12-1103 | We propose a novel approach to improve SMT via paraphrase rules which are automatically extracted from the bilingual training data . Without using extra paraphrase resources , we acquire the rules by comparing the source side of the parallel corpus with the target-to-source translations of the target side . Besides the... | Incorporating paraphrases improves statistical machine translation however no works investigate sentence level paraphrases. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the problem in short form.
---
Docu... | sobamchan/aclsum | 1 | full_paper |
P12-1103 | We propose a novel approach to improve SMT via paraphrase rules which are automatically extracted from the bilingual training data . Without using extra paraphrase resources , we acquire the rules by comparing the source side of the parallel corpus with the target-to-source translations of the target side . Besides the... | The acquired paraphrase rules improve translation qualities in oral and news domains. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 1 | full_paper |
2020.acl-main.573 | Continual relation learning aims to continually train a model on new data to learn incessantly emerging novel relations while avoiding catastrophically forgetting old relations . Some pioneering work has proved that storing a handful of historical relation examples in episodic memory and replaying them in subsequent tr... | The proposed method mitigates catastrophic forgetting of old relations and achieves state-of-the-art on several relation extraction datasets showing it can use memorized examples. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the results.
---
Document:
Conti... | sobamchan/aclsum | 0 | full_paper |
D18-1133 | State-of-the-art networks that model relations between two pieces of text often use complex architectures and attention . In this paper , instead of focusing on architecture engineering , we take advantage of small amounts of labelled data that model semantic phenomena in text to encode matching features directly in th... | The proposed model outperforms a tree kernel model and complex neural models while keeping the model simple and the training fast. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the results.
---
Document:
State... | sobamchan/aclsum | 0 | full_paper |
D09-1085 | This paper introduces a new parser evaluation corpus containing around 700 sentences annotated with unbounded dependencies , from seven different grammatical constructions . We run a series of off-theshelf parsers on the corpus to evaluate how well state-of-the-art parsing technology is able to recover such dependencie... | They propose a new corpus with unbounded dependencies from difference grammatical constructions. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 2 | full_paper |
D17-1220 | Comprehending lyrics , as found in songs and poems , can pose a challenge to human and machine readers alike . This motivates the need for systems that can understand the ambiguity and jargon found in such creative texts , and provide commentary to aid readers in reaching the correct interpretation . We introduce the t... | They propose a task of automated lyric annotation with a dataset collected from an online platform which explains lyrics to readers. | approach | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the method.
---
Document:
Compr... | sobamchan/aclsum | 0 | full_paper |
N13-1083 | We investigate two systems for automatic disfluency detection on English and Mandarin conversational speech data . The first system combines various lexical and prosodic features in a Conditional Random Field model for detecting edit disfluencies . The second system combines acoustic and language model scores for detec... | They evaluate a Conditional Random Field-based edit disfluency detection model and a system which combines acoustic and language model that detects filled pauses in Mandarin. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the method or approach the autho... | sobamchan/aclsum | 0 | full_paper |
D09-1030 | Manual evaluation of translation quality is generally thought to be excessively time consuming and expensive . We explore a fast and inexpensive way of doing it using Amazon 's Mechanical Turk to pay small sums to a large number of non-expert annotators . For $ 10 we redundantly recreate judgments from a WMT08 translat... | They found that non-expert judgements with high agreement correlate better with gold standard judgements than BLEU while keeping the cost low. | outcome | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Describe the conclusions briefly.
---
Docu... | sobamchan/aclsum | 2 | full_paper |
2021.emnlp-main.411 | Language representations are known to carry certain associations ( e.g. , gendered connotations ) which may lead to invalid and harmful predictions in downstream tasks . While existing methods are effective at mitigating such unwanted associations by linear projection , we argue that they are too aggressive : not only ... | They propose a method which orthogonalizes and rectifies incorrectly associated subspaces of concepts in an embedding space and a metric for evaluating information retention. | approach | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
2021.naacl-main.458 | Non-autoregressive Transformer is a promising text generation model . However , current non-autoregressive models still fall behind their autoregressive counterparts in translation quality . We attribute this accuracy gap to the lack of dependency modeling among decoder inputs . In this paper , we propose CNAT , which ... | Non-autoregressive translation models fall behind their autoregressive counterparts in translation quality due to the lack of dependency modelling for the target outputs. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 1 | full_paper |
D12-1061 | This paper explores log-based query expansion ( QE ) models for Web search . Three lexicon models are proposed to bridge the lexical gap between Web documents and user queries . These models are trained on pairs of user queries and titles of clicked documents . Evaluations on a real world data set show that the lexicon... | Term mismatches between a query and documents hinder retrievals of relevant documents and black box statistical machine translation models are used to expand queries. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 0 | full_paper |
N09-1072 | Automatically extracting social meaning and intention from spoken dialogue is an important task for dialogue systems and social computing . We describe a system for detecting elements of interactional style : whether a speaker is awkward , friendly , or flirtatious . We create and use a new spoken corpus of 991 4-minut... | They create a spoken corpus from conversations in speed-dating and perform analysis using extracted dialogue features with a focus on genders. | approach | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
What did the authors do?
---
Document:
Au... | sobamchan/aclsum | 2 | full_paper |
P02-1051 | Named entity phrases are some of the most difficult phrases to translate because new phrases can appear from nowhere , and because many are domain specific , not to be found in bilingual dictionaries . We present a novel algorithm for translating named entity phrases using easily obtainable monolingual and bilingual re... | Translating named entities is challenging since they can appear from nowhere, and cannot be found in bilingual dictionaries because they are domain specific. | challenge | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 2 | full_paper |
2021.emnlp-main.185 | Learning sentence embeddings from dialogues has drawn increasing attention due to its low annotation cost and high domain adaptability . Conventional approaches employ the siamese-network for this task , which obtains the sentence embeddings through modeling the context-response semantic relevance by applying a feed-fo... | Existing methods to learn representations from dialogues have a similarity-measurement gap between training and evaluation time and do not exploit the multi-turn structure of data. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the problem in short form.
---
Docu... | sobamchan/aclsum | 1 | full_paper |
N09-1032 | Domain adaptation is an important problem in named entity recognition ( NER ) . NER classifiers usually lose accuracy in the domain transfer due to the different data distribution between the source and the target domains . The major reason for performance degrading is that each entity type often has lots of domainspec... | The proposed model improves the performance on the English and Chinese corpus across domains especially on each NE type recognition. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
P19-1252 | In this paper , we investigate the importance of social network information compared to content information in the prediction of a Twitter user 's occupational class . We show that the content information of a user 's tweets , the profile descriptions of a user 's follower / following community , and the user 's social... | They show that textual feature enables graph neural networks to predict Twitter user occupation well even with a limited amount of training data. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
D19-1098 | Pre-training Transformer from large-scale raw texts and fine-tuning on the desired task have achieved state-of-the-art results on diverse NLP tasks . However , it is unclear what the learned attention captures . The attention computed by attention heads seems not to match human intuitions about hierarchical structures ... | The proposed model achieves better unsupervised tree structure induction, language modelling, and more explainable attention scores which are coherent to human expert annotations. | outcome | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Extract a short summary of the paper’s resu... | sobamchan/aclsum | 2 | full_paper |
N18-1108 | Recurrent neural networks ( RNNs ) have achieved impressive results in a variety of linguistic processing tasks , suggesting that they can induce non-trivial properties of language . We investigate here to what extent RNNs learn to track abstract hierarchical syntactic structure . We test whether RNNs trained with a ge... | The RNNs trained on an LM objective can solve long-distance agreement problems well even on nonsensical sentences consistently across languages indicating their deeper grammatical competence. | outcome | high_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
2021.acl-long.67 | Bilingual lexicons map words in one language to their translations in another , and are typically induced by learning linear projections to align monolingual word embedding spaces . In this paper , we show it is possible to produce much higher quality lexicons with methods that combine ( 1 ) unsupervised bitext mining ... | They propose to use both unsupervised bitext mining and unsupervised word alignment methods to produce higher quality lexicons. | approach | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Outline the methodology used by the author... | sobamchan/aclsum | 2 | full_paper |
2020.acl-main.573 | Continual relation learning aims to continually train a model on new data to learn incessantly emerging novel relations while avoiding catastrophically forgetting old relations . Some pioneering work has proved that storing a handful of historical relation examples in episodic memory and replaying them in subsequent tr... | Storing histories of examples is shown to be effective for continual relation learning however existing methods suffer from overfitting to memorize a few old memories. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
State the difficulty of the study.
---
D... | sobamchan/aclsum | 2 | full_paper |
2020.acl-main.528 | Recently , many works have tried to augment the performance of Chinese named entity recognition ( NER ) using word lexicons . As a representative , Lattice-LSTM ( Zhang and Yang , 2018 ) has achieved new benchmark results on several public Chinese NER datasets . However , Lattice-LSTM has a complex model architecture .... | The proposed efficient character-based LSTM method with lexical features achieves 6.15 times faster inference speed and better performance than previous models. | outcome | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 2 | full_paper |
P18-1222 | Hypertext documents , such as web pages and academic papers , are of great importance in delivering information in our daily life . Although being effective on plain documents , conventional text embedding methods suffer from information loss if directly adapted to hyper-documents . In this paper , we propose a general... | They propose an embedding method for hyper-documents that learns citation information along with four criteria to assess the properties the models should preserve. | approach | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: approach.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported clai... | sobamchan/aclsum | 0 | full_paper |
2020.emnlp-main.500 | Adversarial attacks for discrete data ( such as texts ) have been proved significantly more challenging than continuous data ( such as images ) since it is difficult to generate adversarial samples with gradient-based methods . Current successful attack methods for texts usually adopt heuristic replacement strategies o... | Generating adversarial samples with gradient-based methods for text data is because of its discrete nature and existing complicated heuristic-based methods suffer from finding optimal solutions. | challenge | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: challenge.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported cla... | sobamchan/aclsum | 2 | full_paper |
P06-1073 | Short vowels and other diacritics are not part of written Arabic scripts . Exceptions are made for important political and religious texts and in scripts for beginning students of Arabic . Script without diacritics have considerable ambiguity because many words with different diacritic patterns appear identical in a di... | Short vowels and other diacritics are not expressed in written Arabic, making it difficult to read for beginner readers or system developments. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
What issue is this paper about?
---
Docu... | sobamchan/aclsum | 0 | full_paper |
P10-1139 | There is a growing research interest in opinion retrieval as on-line users ' opinions are becoming more and more popular in business , social networks , etc . Practically speaking , the goal of opinion retrieval is to retrieve documents , which entail opinions or comments , relevant to a target subject specified by the... | Existing approaches to the opinion retrieval task represent documents using bag-of-words disregarding contextual information between an opinion and its corresponding text. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the problem in short form.
---
Docu... | sobamchan/aclsum | 1 | full_paper |
2020.aacl-main.88 | Large pre-trained language models reach stateof-the-art results on many different NLP tasks when fine-tuned individually ; They also come with a significant memory and computational requirements , calling for methods to reduce model sizes ( green AI ) . We propose a twostage model-compression method to reduce a model '... | The proposed method reduces the model size by 0.4x and increases inference speed by 1.45x while keeping the performance degradation minimum on the GLUE benchmark. | outcome | high_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: outcome.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Summarize the main results or outcomes repo... | sobamchan/aclsum | 0 | full_paper |
2020.acl-main.75 | Humor plays an important role in human languages and it is essential to model humor when building intelligence systems . Among different forms of humor , puns perform wordplay for humorous effects by employing words with double entendre and high phonetic similarity . However , identifying and modeling puns are challeng... | The proposed approach outperforms the state-of-the-art methods in pun detection and location tasks. | outcome | low_quality | coverage_first | Objective: COVERAGE-FIRST.
Task: Write a one-sentence summary focused on the aspect: outcome.
Prioritize including the most salient, high-utility information relevant to the aspect.
You may include multiple key points if they fit naturally in one sentence.
Stay faithful to the document; do not add any unsupported claim... | sobamchan/aclsum | 0 | full_paper |
P16-1067 | This paper proposes an unsupervised approach for segmenting a multiauthor document into authorial components . The key novelty is that we utilize the sequential patterns hidden among document elements when determining their authorships . For this purpose , we adopt Hidden Markov Model ( HMM ) and construct a sequential... | They propose a HMM-based sequential probabilistic model that captures the dependencies of sequential sentences and their authors coupled with an unsupervised initialization method. | approach | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: approach.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
Give the approach described.
---
Document... | sobamchan/aclsum | 1 | full_paper |
P18-1222 | Hypertext documents , such as web pages and academic papers , are of great importance in delivering information in our daily life . Although being effective on plain documents , conventional text embedding methods suffer from information loss if directly adapted to hyper-documents . In this paper , we propose a general... | Existing text embedding methods do not take structures of hyper-documents into account losing useful properties for downstream tasks. | challenge | low_quality | adherence_first | Objective: ADHERENCE-FIRST.
Task: Write a one-sentence summary focused ONLY on the aspect: challenge.
Be strict: exclude any information not directly tied to the aspect.
If uncertain, omit rather than speculate.
Stay faithful to the document; do not add any unsupported claims.
State the difficulty of the study.
---
D... | sobamchan/aclsum | 2 | full_paper |
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