{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/glove/papers/2","list_of":"/method/glove","method":"GloVe","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":2,"pages_in_order":4,"rows_per_page":100,"rows":[101,200],"of":357,"counts":{"archive_papers_tagged":357,"with_a_code_link":116,"where_syntology_ran_a_sample":10,"not_listed_spam_title":0,"listed":357,"listed_where_code_ran":10,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":8,"every_run_a_failure_of_syntologys_instrument":2,"listed_with_a_run_with_no_instrument_failure":8,"listed_every_run_a_failure_of_syntologys_instrument":2,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/glove","prev":"/method/glove","next":"/method/glove/papers/3","papers":[{"paper":null,"slug":"towards-a-theoretical-understanding-of-word","title":"Towards a Theoretical Understanding of Word and Relation Representation","date":"2022-02-01","arxiv_id":"2202.00486","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-correction-of-syntactic-dependency","title":"Automatic Correction of Syntactic Dependency Annotation Differences","date":"2022-01-15","arxiv_id":"2201.05891","n_code_links":0,"syntology":null},{"paper":null,"slug":"polarity-and-subjectivity-detection-with","title":"Polarity and Subjectivity Detection with Multitask Learning and BERT Embedding","date":"2022-01-14","arxiv_id":"2201.05363","n_code_links":0,"syntology":null},{"paper":null,"slug":"formal-analysis-of-art-proxy-learning-of","title":"Formal Analysis of Art: Proxy Learning of Visual Concepts from Style Through Language Models","date":"2022-01-05","arxiv_id":"2201.01819","n_code_links":0,"syntology":null},{"paper":null,"slug":"new-approaches-to-long-document-summarization","title":"New Approaches to Long Document Summarization: Fourier Transform Based Attention in a Transformer Model","date":"2021-11-25","arxiv_id":"2111.15473","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comparative-study-on-transfer-learning-and","title":"A Comparative Study on Transfer Learning and Distance Metrics in Semantic Clustering over the COVID-19 Tweets","date":"2021-11-16","arxiv_id":"2111.08658","n_code_links":0,"syntology":null},{"paper":null,"slug":"crossword-estimating-unknown-embeddings-using","title":"Crossword: Estimating Unknown Embeddings using Cross Attention and Alignment Strategies","date":"2021-11-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"eigennoise-a-contrastive-prior-to-warm-start","title":"EigenNoise: A Contrastive Prior to Warm-Start Representations","date":"2021-11-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"night-owls-and-majestic-whales-modeling","title":"Night Owls and Majestic Whales: Modeling Metaphor Comprehension as a Rational Speech Act over Vector Representations of Lexical Semantics","date":"2021-11-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"non-linear-relational-information-probing-in","title":"Non-Linear Relational Information Probing in Word Embeddings","date":"2021-11-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"to-know-by-the-company-words-keep-and-what","title":"To Know by the Company Words Keep and What Else Lies in the Vicinity","date":"2021-11-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/guiding-multi-step-rearrangement-tasks-with","slug":"guiding-multi-step-rearrangement-tasks-with","title":"Guiding Multi-Step Rearrangement Tasks with Natural Language Instructions","date":"2021-11-08","arxiv_id":null,"n_code_links":2,"syntology":null},{"paper":null,"slug":"comparative-study-of-long-document","title":"Comparative Study of Long Document Classification","date":"2021-11-01","arxiv_id":"2111.00702","n_code_links":0,"syntology":null},{"paper":null,"slug":"estimation-and-prediction-of-deterministic","title":"Attention-based Estimation and Prediction of Human Intent to augment Haptic Glove aided Control of Robotic Hand","date":"2021-10-15","arxiv_id":"2110.07953","n_code_links":0,"syntology":null},{"paper":"/paper/fake-news-detection-in-spanish-using-deep","slug":"fake-news-detection-in-spanish-using-deep","title":"Fake News Detection in Spanish Using Deep Learning Techniques","date":"2021-10-13","arxiv_id":"2110.06461","n_code_links":1,"syntology":null},{"paper":"/paper/a-comprehensive-comparison-of-word-embeddings","slug":"a-comprehensive-comparison-of-word-embeddings","title":"A Comprehensive Comparison of Word Embeddings in Event & Entity Coreference Resolution","date":"2021-10-11","arxiv_id":"2110.05115","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-sense-specific-static-embeddings","title":"Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy","date":"2021-10-05","arxiv_id":"2110.02204","n_code_links":0,"syntology":null},{"paper":"/paper/edgar-corpus-billions-of-tokens-make-the","slug":"edgar-corpus-billions-of-tokens-make-the","title":"EDGAR-CORPUS: Billions of Tokens Make The World Go Round","date":"2021-09-29","arxiv_id":"2109.14394","n_code_links":0,"syntology":null},{"paper":null,"slug":"graph-based-nearest-neighbor-search-in","title":"Graph-based Nearest Neighbor Search in Hyperbolic Spaces","date":"2021-09-29","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"identifying-and-mitigating-gender-bias-in","title":"Identifying and Mitigating Gender Bias in Hyperbolic Word Embeddings","date":"2021-09-28","arxiv_id":"2109.13767","n_code_links":0,"syntology":null},{"paper":"/paper/effective-use-of-graph-convolution-network","slug":"effective-use-of-graph-convolution-network","title":"Effective Use of Graph Convolution Network and Contextual Sub-Tree forCommodity News Event Extraction","date":"2021-09-27","arxiv_id":"2109.12781","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-comprehensive-review-on-summarizing","title":"A Comprehensive Review on Summarizing Financial News Using Deep Learning","date":"2021-09-21","arxiv_id":"2109.10118","n_code_links":0,"syntology":null},{"paper":null,"slug":"dynamic-modeling-of-hand-object-interactions","title":"Dynamic Modeling of Hand-Object Interactions via Tactile Sensing","date":"2021-09-09","arxiv_id":"2109.04378","n_code_links":0,"syntology":null},{"paper":null,"slug":"sense-representations-for-portuguese","title":"Sense representations for Portuguese: experiments with sense embeddings and deep neural language models","date":"2021-08-31","arxiv_id":"2109.00025","n_code_links":0,"syntology":null},{"paper":"/paper/harms-of-gender-exclusivity-and-challenges-in","slug":"harms-of-gender-exclusivity-and-challenges-in","title":"Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies","date":"2021-08-27","arxiv_id":"2108.12084","n_code_links":1,"syntology":null},{"paper":null,"slug":"investigating-bias-in-automatic-toxic-comment","title":"Investigating Bias In Automatic Toxic Comment Detection: An Empirical Study","date":"2021-08-14","arxiv_id":"2108.06487","n_code_links":0,"syntology":null},{"paper":null,"slug":"offensive-language-and-hate-speech-detection-1","title":"Offensive Language and Hate Speech Detection with Deep Learning and Transfer Learning","date":"2021-08-06","arxiv_id":"2108.03305","n_code_links":0,"syntology":null},{"paper":"/paper/linked-data-triples-enhance-document","slug":"linked-data-triples-enhance-document","title":"Linked Data Triples Enhance Document Relevance Classification","date":"2021-07-20","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"tackling-covid-19-infodemic-using-deep","title":"Tackling COVID-19 Infodemic using Deep Learning","date":"2021-07-01","arxiv_id":"2107.02012","n_code_links":0,"syntology":null},{"paper":"/paper/hate-speech-detection-using-static-bert","slug":"hate-speech-detection-using-static-bert","title":"Hate speech detection using static BERT embeddings","date":"2021-06-29","arxiv_id":"2106.15537","n_code_links":0,"syntology":null},{"paper":"/paper/a-source-criticism-debiasing-method-for-glove","slug":"a-source-criticism-debiasing-method-for-glove","title":"A Source-Criticism Debiasing Method for GloVe Embeddings","date":"2021-06-25","arxiv_id":"2106.13382","n_code_links":1,"syntology":null},{"paper":null,"slug":"palrace-reading-comprehension-dataset-with","title":"PALRACE: Reading Comprehension Dataset with Human Data and Labeled Rationales","date":"2021-06-23","arxiv_id":"2106.12373","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-models-in-detection-of-dietary","title":"Deep Learning Models in Detection of Dietary Supplement Adverse Event Signals from Twitter","date":"2021-06-21","arxiv_id":"2106.11403","n_code_links":0,"syntology":null},{"paper":null,"slug":"sasicm-a-multi-task-benchmark-for-subtext","title":"SASICM A Multi-Task Benchmark For Subtext Recognition","date":"2021-06-13","arxiv_id":"2106.06944","n_code_links":0,"syntology":null},{"paper":null,"slug":"shape-of-elephant-study-of-macro-properties","title":"Shape of Elephant: Study of Macro Properties of Word Embeddings Spaces","date":"2021-06-13","arxiv_id":"2106.06964","n_code_links":0,"syntology":null},{"paper":null,"slug":"corpus-based-paraphrase-detection-experiments","title":"Corpus-Based Paraphrase Detection Experiments and Review","date":"2021-05-31","arxiv_id":"2106.00145","n_code_links":0,"syntology":null},{"paper":null,"slug":"aligning-visual-prototypes-with-bert","title":"Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning","date":"2021-05-21","arxiv_id":"2105.10195","n_code_links":0,"syntology":null},{"paper":"/paper/tf-idf-vs-word-embeddings-for-morbidity","slug":"tf-idf-vs-word-embeddings-for-morbidity","title":"TF-IDF vs Word Embeddings for Morbidity Identification in Clinical Notes: An Initial Study","date":"2021-05-20","arxiv_id":"2105.09632","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-automated-method-to-enrich-consumer-health","title":"An Automated Method to Enrich Consumer Health Vocabularies Using GloVe Word Embeddings and An Auxiliary Lexical Resource","date":"2021-05-18","arxiv_id":"2105.08812","n_code_links":0,"syntology":null},{"paper":null,"slug":"revisiting-additive-compositionality-and-or","title":"Revisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings","date":"2021-05-18","arxiv_id":"2105.08585","n_code_links":0,"syntology":null},{"paper":null,"slug":"wove-incorporating-word-order-in-glove-word","title":"WOVe: Incorporating Word Order in GloVe Word Embeddings","date":"2021-05-18","arxiv_id":"2105.08597","n_code_links":0,"syntology":null},{"paper":null,"slug":"building-a-question-and-answer-system-for","title":"Building a Question and Answer System for News Domain","date":"2021-05-12","arxiv_id":"2105.05744","n_code_links":0,"syntology":null},{"paper":"/paper/playing-codenames-with-language-graphs-and","slug":"playing-codenames-with-language-graphs-and","title":"Playing Codenames with Language Graphs and Word Embeddings","date":"2021-05-12","arxiv_id":"2105.05885","n_code_links":1,"syntology":null},{"paper":null,"slug":"waveglove-transformer-based-hand-gesture","title":"WaveGlove: Transformer-based hand gesture recognition using multiple inertial sensors","date":"2021-05-04","arxiv_id":"2105.01753","n_code_links":0,"syntology":null},{"paper":null,"slug":"recognition-and-processing-of-natom","title":"Recognition and Processing of NATOM","date":"2021-04-29","arxiv_id":"2105.03314","n_code_links":0,"syntology":null},{"paper":null,"slug":"uot-uwf-partai-at-semeval-2021-task-5-self","title":"UoT-UWF-PartAI at SemEval-2021 Task 5: Self Attention Based Bi-GRU with Multi-Embedding Representation for Toxicity Highlighter","date":"2021-04-27","arxiv_id":"2104.13164","n_code_links":0,"syntology":null},{"paper":null,"slug":"analysing-cyberbullying-using-natural","title":"Analysing Cyberbullying using Natural Language Processing by Understanding Jargon in Social Media","date":"2021-04-23","arxiv_id":"2107.08902","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-trustworthy-deception-detection","title":"Towards Trustworthy Deception Detection: Benchmarking Model Robustness across Domains, Modalities, and Languages","date":"2021-04-23","arxiv_id":"2104.11761","n_code_links":0,"syntology":null},{"paper":null,"slug":"are-word-embedding-methods-stable-and-should","title":"Are Word Embedding Methods Stable and Should We Care About It?","date":"2021-04-17","arxiv_id":"2104.08433","n_code_links":0,"syntology":null},{"paper":"/paper/identifying-the-limits-of-cross-domain","slug":"identifying-the-limits-of-cross-domain","title":"Identifying the Limits of Cross-Domain Knowledge Transfer for Pretrained Models","date":"2021-04-17","arxiv_id":"2104.08410","n_code_links":1,"syntology":null},{"paper":"/paper/multi-source-neural-topic-modeling-in-multi","slug":"multi-source-neural-topic-modeling-in-multi","title":"Multi-source Neural Topic Modeling in Multi-view Embedding Spaces","date":"2021-04-17","arxiv_id":"2104.08551","n_code_links":1,"syntology":null},{"paper":"/paper/distributed-word-representation-in-tsetlin","slug":"distributed-word-representation-in-tsetlin","title":"Enhancing Interpretable Clauses Semantically using Pretrained Word Representation","date":"2021-04-14","arxiv_id":"2104.06901","n_code_links":6,"syntology":null},{"paper":null,"slug":"combining-pre-trained-word-embeddings-and","title":"Combining Pre-trained Word Embeddings and Linguistic Features for Sequential Metaphor Identification","date":"2021-04-07","arxiv_id":"2104.03285","n_code_links":0,"syntology":null},{"paper":null,"slug":"covid-19-sentiment-analysis-via-deep-learning","title":"COVID-19 sentiment analysis via deep learning during the rise of novel cases","date":"2021-04-05","arxiv_id":"2104.10662","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-chinese-remainder-theorem-for-compact","title":"The Chinese Remainder Theorem for Compact, Task-Precise, Efficient and Secure Word Embeddings","date":"2021-04-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/afrivec-word-embedding-models-for-african","slug":"afrivec-word-embedding-models-for-african","title":"AfriVEC: Word Embedding Models for African Languages. Case Study of Fon and Nobiin","date":"2021-03-08","arxiv_id":"2103.05132","n_code_links":1,"syntology":null},{"paper":"/paper/paraphrases-do-not-explain-word-analogies","slug":"paraphrases-do-not-explain-word-analogies","title":"Paraphrases do not explain word analogies","date":"2021-02-23","arxiv_id":"2102.11749","n_code_links":1,"syntology":null},{"paper":null,"slug":"artificial-intelligence-prediction-of-stock","title":"Artificial intelligence prediction of stock prices using social media","date":"2021-01-22","arxiv_id":"2101.08986","n_code_links":0,"syntology":null},{"paper":null,"slug":"neural-contract-element-extraction-revisited","title":"Neural Contract Element Extraction Revisited: Letters from Sesame Street","date":"2021-01-12","arxiv_id":"2101.04355","n_code_links":0,"syntology":null},{"paper":"/paper/semglove-semantic-co-occurrences-for-glove","slug":"semglove-semantic-co-occurrences-for-glove","title":"SemGloVe: Semantic Co-occurrences for GloVe from BERT","date":"2020-12-30","arxiv_id":"2012.15197","n_code_links":3,"syntology":null},{"paper":null,"slug":"3218ir-at-semeval-2020-task-11-conv1d-and","title":"3218IR at SemEval-2020 Task 11: Conv1D and Word Embedding in Propaganda Span Identification at News Articles","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/a-mixture-of-experts-model-for-learning-multi","slug":"a-mixture-of-experts-model-for-learning-multi","title":"A Mixture-of-Experts Model for Learning Multi-Facet Entity Embeddings","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"iiitg-adbu-at-semeval-2020-task-8-a","title":"IIITG-ADBU at SemEval-2020 Task 8: A Multimodal Approach to Detect Offensive, Sarcastic and Humorous Memes","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"intrinsic-analysis-for-dual-word-embedding","title":"Intrinsic analysis for dual word embedding space models","date":"2020-12-01","arxiv_id":"2012.00728","n_code_links":0,"syntology":null},{"paper":null,"slug":"ir3218-ui-at-semeval-2020-task-12-emoji","title":"IR3218-UI at SemEval-2020 Task 12: Emoji Effects on Offensive Language IdentifiCation","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/memebusters-at-semeval-2020-task-8-feature","slug":"memebusters-at-semeval-2020-task-8-feature","title":"Memebusters at SemEval-2020 Task 8: Feature Fusion Model for Sentiment Analysis on Memes Using Transfer Learning","date":"2020-12-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"ntuaails-at-semeval-2020-task-11-propaganda","title":"NTUAAILS at SemEval-2020 Task 11: Propaganda Detection and Classification with biLSTMs and ELMo","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"unituebingencl-at-semeval-2020-task-7-humor","title":"UniTuebingenCL at SemEval-2020 Task 7: Humor Detection in News Headlines","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"word-embedding-binarization-with-semantic","title":"Word Embedding Binarization with Semantic Information Preservation","date":"2020-12-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"blind-signal-decomposition-of-various-word","title":"Blind signal decomposition of various word embeddings based on join and individual variance explained","date":"2020-11-30","arxiv_id":"2011.14496","n_code_links":0,"syntology":null},{"paper":null,"slug":"zero-shot-audio-classification-via-semantic","title":"Zero-Shot Audio Classification via Semantic Embeddings","date":"2020-11-24","arxiv_id":"2011.12133","n_code_links":0,"syntology":null},{"paper":null,"slug":"deconstructing-word-embedding-algorithms","title":"Deconstructing word embedding algorithms","date":"2020-11-12","arxiv_id":"2011.07013","n_code_links":0,"syntology":null},{"paper":"/paper/bionerflair-biomedical-named-entity","slug":"bionerflair-biomedical-named-entity","title":"BioNerFlair: biomedical named entity recognition using flair embedding and sequence tagger","date":"2020-11-03","arxiv_id":"2011.01504","n_code_links":1,"syntology":null},{"paper":"/paper/thy-algorithm-shalt-not-bear-false-witness-an","slug":"thy-algorithm-shalt-not-bear-false-witness-an","title":"\"Thy algorithm shalt not bear false witness\": An Evaluation of Multiclass Debiasing Methods on Word Embeddings","date":"2020-10-30","arxiv_id":"2010.16228","n_code_links":1,"syntology":null},{"paper":null,"slug":"robust-and-consistent-estimation-of-word","title":"Robust and Consistent Estimation of Word Embedding for Bangla Language by fine-tuning Word2Vec Model","date":"2020-10-26","arxiv_id":"2010.13404","n_code_links":0,"syntology":null},{"paper":"/paper/embedding-words-in-non-vector-space-with","slug":"embedding-words-in-non-vector-space-with","title":"Embedding Words in Non-Vector Space with Unsupervised Graph Learning","date":"2020-10-06","arxiv_id":"2010.02598","n_code_links":1,"syntology":null},{"paper":null,"slug":"development-of-word-embeddings-for-uzbek","title":"Development of Word Embeddings for Uzbek Language","date":"2020-09-30","arxiv_id":"2009.14384","n_code_links":0,"syntology":null},{"paper":"/paper/leader-prefixing-a-length-for-faster-word","slug":"leader-prefixing-a-length-for-faster-word","title":"Leader: Prefixing a Length for Faster Word Vector Serialization","date":"2020-09-29","arxiv_id":"2009.13699","n_code_links":1,"syntology":null},{"paper":null,"slug":"analyze-the-effects-of-weighting-functions-on","title":"Analyze the Effects of Weighting Functions on Cost Function in the Glove Model","date":"2020-09-10","arxiv_id":"2009.04732","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-modal-embeddings-using-multi-task","title":"Multi-modal embeddings using multi-task learning for emotion recognition","date":"2020-09-10","arxiv_id":"2009.05019","n_code_links":0,"syntology":null},{"paper":null,"slug":"finding-core-members-of-cooperative-games","title":"Finding Core Members of Cooperative Games using Agent-Based Modeling","date":"2020-08-30","arxiv_id":"2009.00519","n_code_links":0,"syntology":null},{"paper":"/paper/ynu-hpcc-at-semeval-2020-task-11-lstm-network","slug":"ynu-hpcc-at-semeval-2020-task-11-lstm-network","title":"YNU-HPCC at SemEval-2020 Task 11: LSTM Network for Detection of Propaganda Techniques in News Articles","date":"2020-08-24","arxiv_id":"2008.10166","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["daojiaxu/semeval_11"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"sgg-spinbot-grammarly-and-glove-based-fake","title":"SGG: Spinbot, Grammarly and GloVe based Fake News Detection","date":"2020-08-16","arxiv_id":"2008.06854","n_code_links":0,"syntology":null},{"paper":null,"slug":"word-embeddings-stability-and-semantic-change","title":"Word Embeddings: Stability and Semantic Change","date":"2020-07-23","arxiv_id":"2007.16006","n_code_links":0,"syntology":null},{"paper":null,"slug":"predicting-job-hopping-likelihood-using","title":"Predicting Job-Hopping Motive of Candidates Using Answers to Open-ended Interview Questions","date":"2020-07-22","arxiv_id":"2007.11189","n_code_links":0,"syntology":null},{"paper":null,"slug":"morphological-skip-gram-using-morphological","title":"Morphological Skip-Gram: Using morphological knowledge to improve word representation","date":"2020-07-20","arxiv_id":"2007.10055","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-holographically-compressed-embeddings","title":"Using Holographically Compressed Embeddings in Question Answering","date":"2020-07-14","arxiv_id":"2007.07287","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-enhanced-text-classification-to-explore","title":"An Enhanced Text Classification to Explore Health based Indian Government Policy Tweets","date":"2020-07-13","arxiv_id":"2007.06511","n_code_links":0,"syntology":null},{"paper":"/paper/gloveinit-at-semeval-2020-task-1-using-glove","slug":"gloveinit-at-semeval-2020-task-1-using-glove","title":"GloVeInit at SemEval-2020 Task 1: Using GloVe Vector Initialization for Unsupervised Lexical Semantic Change Detection","date":"2020-07-10","arxiv_id":"2007.05618","n_code_links":1,"syntology":null},{"paper":"/paper/automatic-detection-of-sexist-statements","slug":"automatic-detection-of-sexist-statements","title":"Automatic Detection of Sexist Statements Commonly Used at the Workplace","date":"2020-07-08","arxiv_id":"2007.04181","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-novel-bgcapsule-network-for-text","title":"A Novel BGCapsule Network for Text Classification","date":"2020-07-02","arxiv_id":"2007.04302","n_code_links":0,"syntology":null},{"paper":null,"slug":"interpreting-pretrained-contextualized","title":"Interpreting Pretrained Contextualized Representations via Reductions to Static Embeddings","date":"2020-07-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-transformer-for-multimodal-machine","slug":"multimodal-transformer-for-multimodal-machine","title":"Multimodal Transformer for Multimodal Machine Translation","date":"2020-07-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"dirichlet-smoothed-word-embeddings-for-low-1","title":"Dirichlet-Smoothed Word Embeddings for Low-Resource Settings","date":"2020-06-22","arxiv_id":"2006.12414","n_code_links":0,"syntology":null},{"paper":null,"slug":"sarcasm-detection-in-tweets-with-bert-and-1","title":"Sarcasm Detection in Tweets with BERT and GloVe Embeddings","date":"2020-06-20","arxiv_id":"2006.11512","n_code_links":0,"syntology":null},{"paper":null,"slug":"hybrid-improved-document-level-embedding-hide","title":"Hybrid Improved Document-level Embedding (HIDE)","date":"2020-06-01","arxiv_id":"2006.01203","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-problem-statements-in-peer","title":"Detecting Problem Statements in Peer Assessments","date":"2020-05-30","arxiv_id":"2006.04532","n_code_links":0,"syntology":null},{"paper":"/paper/mask-a-flexible-framework-to-facilitate-de","slug":"mask-a-flexible-framework-to-facilitate-de","title":"MASK: A flexible framework to facilitate de-identification of clinical texts","date":"2020-05-24","arxiv_id":"2005.11687","n_code_links":1,"syntology":null},{"paper":null,"slug":"crisisbert-robust-transformer-for-crisis","title":"CrisisBERT: a Robust Transformer for Crisis Classification and Contextual Crisis Embedding","date":"2020-05-11","arxiv_id":"2005.06627","n_code_links":0,"syntology":null},{"paper":"/paper/segmenting-scientific-abstracts-into","slug":"segmenting-scientific-abstracts-into","title":"Segmenting Scientific Abstracts into Discourse Categories: A Deep Learning-Based Approach for Sparse Labeled Data","date":"2020-05-11","arxiv_id":"2005.05414","n_code_links":1,"syntology":null}],"record_sha256":"213ffdec953ffd137ede9ddc37822393f78bf7a2892b202a0823d5589a27cde9","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}