{"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":"/task/community-question-answering/papers/2","list_of":"/task/community-question-answering","task":"Community Question Answering","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":2,"pages_in_order":3,"rows_per_page":100,"rows":[101,200],"of":236,"counts":{"archive_papers_tagged":236,"with_a_code_link":50,"where_syntology_ran_a_sample":2,"not_listed_spam_title":0,"listed":236,"listed_where_code_ran":2,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":2,"every_run_a_failure_of_syntologys_instrument":0,"listed_with_a_run_with_no_instrument_failure":2,"listed_every_run_a_failure_of_syntologys_instrument":0,"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":"/task/community-question-answering","prev":"/task/community-question-answering","next":"/task/community-question-answering/papers/3","papers":[{"url":null,"slug":"multi-view-domain-adapted-sentence-embeddings","title":"Multi-View Domain Adapted Sentence Embeddings for Low-Resource Unsupervised Duplicate Question Detection","date":"2019-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-contextualized-pairwise-semantic","title":"Deep Contextualized Pairwise Semantic Similarity for Arabic Language Questions","date":"2019-09-19","arxiv_id":"1909.09490","repositories_listed":0,"syntology":null},{"url":null,"slug":"190600156","title":"Promotion of Answer Value Measurement with Domain Effects in Community Question Answering Systems","date":"2019-06-01","arxiv_id":"1906.00156","repositories_listed":0,"syntology":null},{"url":null,"slug":"autohome-orca-at-semeval-2019-task-8","title":"AUTOHOME-ORCA at SemEval-2019 Task 8: Application of BERT for Fact-Checking in Community Forums","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"blcu_nlp-at-semeval-2019-task-8-a-contextual","title":"BLCU\\_NLP at SemEval-2019 Task 8: A Contextual Knowledge-enhanced GPT Model for Fact Checking","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"codeforthechange-at-semeval-2019-task-8-skip","title":"CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"columbianlp-at-semeval-2019-task-8-the-answer","title":"ColumbiaNLP at SemEval-2019 Task 8: The Answer is Language Model Fine-tuning","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domlin-at-semeval-2019-task-8-automated-fact","title":"DOMLIN at SemEval-2019 Task 8: Automated Fact Checking exploiting Ratings in Community Question Answering Forums","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"duth-at-semeval-2019-task-8-part-of-speech","title":"DUTH at SemEval-2019 Task 8: Part-Of-Speech Features for Question Classification","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fermi-at-semeval-2019-task-8-an-elementary","title":"Fermi at SemEval-2019 Task 8: An elementary but effective approach to Question Discernment in Community QA Forums","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-helpful-posts-in-open-ended","title":"Predicting Helpful Posts in Open-Ended Discussion Forums: A Neural Architecture","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"solomonlab-at-semeval-2019-task-8-question","title":"SolomonLab at SemEval-2019 Task 8: Question Factuality and Answer Veracity Prediction in Community Forums","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"tuefact-at-semeval-2019-task-8-fact-checking","title":"TueFact at SemEval 2019 Task 8: Fact checking in community question answering forums: context matters","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"190601515","title":"TMLab SRPOL at SemEval-2019 Task 8: Fact Checking in Community Question Answering Forums","date":"2019-05-29","arxiv_id":"1906.01515","repositories_listed":0,"syntology":null},{"url":null,"slug":"large-scale-question-paraphrase-retrieval","title":"Large Scale Question Paraphrase Retrieval with Smoothed Deep Metric Learning","date":"2019-05-29","arxiv_id":"1905.12786","repositories_listed":0,"syntology":null},{"url":null,"slug":"question-relatedness-on-stack-overflow-the","title":"Question Relatedness on Stack Overflow: The Task, Dataset, and Corpus-inspired Models","date":"2019-05-03","arxiv_id":"1905.01966","repositories_listed":0,"syntology":null},{"url":null,"slug":"query-expansion-for-cross-language-question","title":"Query Expansion for Cross-Language Question Re-Ranking","date":"2019-04-16","arxiv_id":"1904.07982","repositories_listed":0,"syntology":null},{"url":null,"slug":"implicit-dimension-identification-in-user","title":"Implicit Dimension Identification in User-Generated Text with LSTM Networks","date":"2019-01-26","arxiv_id":"1901.09219","repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-transfer-learning-for-product","title":"Supervised Transfer Learning for Product Information Question Answering","date":"2019-01-08","arxiv_id":"1901.02539","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-generality-and-knowledge-transferability","title":"On Generality and Knowledge Transferability in Cross-Domain Duplicate Question Detection for Heterogeneous Community Question Answering","date":"2018-11-15","arxiv_id":"1811.06596","repositories_listed":0,"syntology":null},{"url":null,"slug":"preferred-answer-selection-in-stack-overflow","title":"Preferred Answer Selection in Stack Overflow: Better Text Representations ... and Metadata, Metadata, Metadata","date":"2018-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"software-expert-discovery-via-knowledge","title":"Software Expert Discovery via Knowledge Domain Embeddings in a Collaborative Network","date":"2018-10-26","arxiv_id":"1810.11305","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-transition-based-parsing-of-web","title":"Neural Transition Based Parsing of Web Queries: An Entity Based Approach","date":"2018-10-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-multitask-learning-for-community","title":"Joint Multitask Learning for Community Question Answering Using Task-Specific Embeddings","date":"2018-09-24","arxiv_id":"1809.08928","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-strong-baseline-for-question-relevancy","title":"A strong baseline for question relevancy ranking","date":"2018-08-27","arxiv_id":"1808.08836","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-on-deep-learning-techniques-applied-1","title":"A Review on Deep Learning Techniques Applied to Answer Selection","date":"2018-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-headline-generation-based-on","title":"Extractive Headline Generation Based on Learning to Rank for Community Question Answering","date":"2018-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"uh-prhlt-at-semeval-2016-task-3-combining","title":"UH-PRHLT at SemEval-2016 Task 3: Combining Lexical and Semantic-based Features for Community Question Answering","date":"2018-07-30","arxiv_id":"1807.11584","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-expert-recommendation-in","title":"A Survey on Expert Recommendation in Community Question Answering","date":"2018-07-15","arxiv_id":"1807.05540","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-flexible-efficient-and-accurate-framework","title":"A Flexible, Efficient and Accurate Framework for Community Question Answering Pipelines","date":"2018-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-domain-framework-for-textual","title":"A Multi-Domain Framework for Textual Similarity. A Case Study on Question-to-Question and Question-Answering Similarity Tasks","date":"2018-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"photoshopquia-a-corpus-of-non-factoid","title":"PhotoshopQuiA: A Corpus of Non-Factoid Questions and Answers for Why-Question Answering","date":"2018-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-equivalence-detection-are","title":"Semantic Equivalence Detection: Are Interrogatives Harder than Declaratives?","date":"2018-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"expert-finding-in-community-question","title":"Expert Finding in Community Question Answering: A Review","date":"2018-04-21","arxiv_id":"1804.07958","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-unsupervised-model-with-attention","title":"An Unsupervised Model with Attention Autoencoders for Question Retrieval","date":"2018-03-09","arxiv_id":"1803.03476","repositories_listed":0,"syntology":null},{"url":null,"slug":"attentive-recurrent-tensor-model-for","title":"Attentive Recurrent Tensor Model for Community Question Answering","date":"2018-01-21","arxiv_id":"1801.06792","repositories_listed":0,"syntology":null},{"url":null,"slug":"ju-nitm-at-ijcnlp-2017-task-5-a","title":"JU NITM at IJCNLP-2017 Task 5: A Classification Approach for Answer Selection in Multi-choice Question Answering System","date":"2017-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"question-retrieval-with-distributed","title":"Question Retrieval with Distributed Representations and Participant Reputation in Community Question Answering","date":"2017-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-exploration-of-data-augmentation-and-rnn","title":"An Exploration of Data Augmentation and RNN Architectures for Question Ranking in Community Question Answering","date":"2017-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"summarizing-lengthy-questions","title":"Summarizing Lengthy Questions","date":"2017-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"constructing-an-alias-list-for-named-entities","title":"Constructing an Alias List for Named Entities during an Event","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mappsent-a-textual-mapping-approach-for","title":"MappSent: a Textual Mapping Approach for Question-to-Question Similarity","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multimedia-summary-generation-from-online","title":"Multimedia Summary Generation from Online Conversations: Current Approaches and Future Directions","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ranking-kernels-for-structures-and-embeddings","title":"Ranking Kernels for Structures and Embeddings: A Hybrid Preference and Classification Model","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-effect-of-negative-sampling-strategy-on","title":"The Effect of Negative Sampling Strategy on Capturing Semantic Similarity in Document Embeddings","date":"2017-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"beihang-msra-at-semeval-2017-task-3-a-ranking","title":"Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bunji-at-semeval-2017-task-3-combination-of","title":"bunji at SemEval-2017 Task 3: Combination of Neural Similarity Features and Comment Plausibility Features","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-language-learning-with-adversarial","title":"Cross-language Learning with Adversarial Neural Networks","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ecnu-at-semeval-2017-task-3-using-traditional","title":"ECNU at SemEval-2017 Task 3: Using Traditional and Deep Learning Methods to Address Community Question Answering Task","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"eica-team-at-semeval-2017-task-3-semantic-and","title":"EICA Team at SemEval-2017 Task 3: Semantic and Metadata-based Features for Community Question Answering","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fa3l-at-semeval-2017-task-3-a-three","title":"FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"furongwang-at-semeval-2017-task-3-deep-neural","title":"FuRongWang at SemEval-2017 Task 3: Deep Neural Networks for Selecting Relevant Answers in Community Question Answering","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"gw_qa-at-semeval-2017-task-3-question-answer","title":"GW\\_QA at SemEval-2017 Task 3: Question Answer Re-ranking on Arabic Fora","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"kelp-at-semeval-2017-task-3-learning-pairwise","title":"KeLP at SemEval-2017 Task 3: Learning Pairwise Patterns in Community Question Answering","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mors-at-semeval-2017-task-3-easy-to-use-svm","title":"MoRS at SemEval-2017 Task 3: Easy to use SVM in Ranking Tasks","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nlm_nih-at-semeval-2017-task-3-from-question","title":"NLM\\_NIH at SemEval-2017 Task 3: from Question Entailment to Question Similarity for Community Question Answering","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"qu-bigir-at-semeval-2017-task-3-using","title":"QU-BIGIR at SemEval 2017 Task 3: Using Similarity Features for Arabic Community Question Answering Forums","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"scir-qa-at-semeval-2017-task-3-cnn-model","title":"SCIR-QA at SemEval-2017 Task 3: CNN Model Based on Similar and Dissimilar Information between Keywords for Question Similarity","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"simbow-at-semeval-2017-task-3-soft-cosine","title":"SimBow at SemEval-2017 Task 3: Soft-Cosine Semantic Similarity between Questions for Community Question Answering","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"takelab-qa-at-semeval-2017-task-3","title":"TakeLab-QA at SemEval-2017 Task 3: Classification Experiments for Answer Retrieval in Community QA","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"talla-at-semeval-2017-task-3-identifying","title":"Talla at SemEval-2017 Task 3: Identifying Similar Questions Through Paraphrase Detection","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"uinsuska-titech-at-semeval-2017-task-3","title":"UINSUSKA-TiTech at SemEval-2017 Task 3: Exploiting Word Importance Levels for Similarity Features for CQA","date":"2017-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"large-scale-goodness-polarity-lexicons-for","title":"Large-Scale Goodness Polarity Lexicons for Community Question Answering","date":"2017-07-20","arxiv_id":"1707.06378","repositories_listed":0,"syntology":null},{"url":null,"slug":"reltextrank-an-open-source-framework-for","title":"RelTextRank: An Open Source Framework for Building Relational Syntactic-Semantic Text Pair Representations","date":"2017-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-language-learning-with-adversarial-1","title":"Cross-language Learning with Adversarial Neural Networks: Application to Community Question Answering","date":"2017-06-21","arxiv_id":"1706.06749","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-community-question-answering","title":"A survey of Community Question Answering","date":"2017-05-11","arxiv_id":"1705.04009","repositories_listed":0,"syntology":null},{"url":null,"slug":"effective-shared-representations-with","title":"Effective shared representations with Multitask Learning for Community Question Answering","date":"2017-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"if-you-cant-beat-them-join-them-handcrafted","title":"If You Can't Beat Them Join Them: Handcrafted Features Complement Neural Nets for Non-Factoid Answer Reranking","date":"2017-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multitask-learning-with-deep-neural-networks","title":"Multitask Learning with Deep Neural Networks for Community Question Answering","date":"2017-02-13","arxiv_id":"1702.03706","repositories_listed":0,"syntology":null},{"url":null,"slug":"community-question-answering-platforms-vs","title":"Community Question Answering Platforms vs. Twitter for Predicting Characteristics of Urban Neighbourhoods","date":"2017-01-17","arxiv_id":"1701.04653","repositories_listed":0,"syntology":null},{"url":null,"slug":"mining-compatibleincompatible-entities-from","title":"Mining Compatible/Incompatible Entities from Question and Answering via Yes/No Answer Classification using Distant Label Expansion","date":"2016-12-14","arxiv_id":"1612.04499","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-entity-based-approach-to-answering","title":"An Entity-Based approach to Answering Recurrent and Non-Recurrent Questions with Past Answers","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"an-interactive-system-for-exploring-community","title":"An Interactive System for Exploring Community Question Answering Forums","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"hand-in-glove-deep-feature-fusion-network","title":"Hand in Glove: Deep Feature Fusion Network Architectures for Answer Quality Prediction in Community Question Answering","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"machine-translation-evaluation-for-arabic","title":"Machine Translation Evaluation for Arabic using Morphologically-enriched Embeddings","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"name-variation-in-community-question","title":"Name Variation in Community Question Answering Systems","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-attention-for-learning-to-rank","title":"Neural Attention for Learning to Rank Questions in Community Question Answering","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"selecting-sentences-versus-selecting-tree","title":"Selecting Sentences versus Selecting Tree Constituents for Automatic Question Ranking","date":"2016-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"it-takes-three-to-tango-triangulation","title":"It Takes Three to Tango: Triangulation Approach to Answer Ranking in Community Question Answering","date":"2016-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"addressing-community-question-answering-in","title":"Addressing Community Question Answering in English and Arabic","date":"2016-10-18","arxiv_id":"1610.05522","repositories_listed":0,"syntology":null},{"url":null,"slug":"docchat-an-information-retrieval-approach-for","title":"DocChat: An Information Retrieval Approach for Chatbot Engines Using Unstructured Documents","date":"2016-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/how-well-do-computers-solve-math-word","slug":"how-well-do-computers-solve-math-word","title":"How well do Computers Solve Math Word Problems? Large-Scale Dataset Construction and Evaluation","date":"2016-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-semantic-relatedness-in-community","title":"Learning Semantic Relatedness in Community Question Answering Using Neural Models","date":"2016-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"together-we-stand-siamese-networks-for","title":"Together we stand: Siamese Networks for Similar Question Retrieval","date":"2016-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-feature-fusion-network-for-answer","title":"Deep Feature Fusion Network for Answer Quality Prediction in Community Question Answering","date":"2016-06-22","arxiv_id":"1606.07103","repositories_listed":0,"syntology":null},{"url":"/paper/convkn-at-semeval-2016-task-3-answer-and","slug":"convkn-at-semeval-2016-task-3-answer-and","title":"ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"crowdsourcing-for-almost-real-time-question","title":"Crowdsourcing for (almost) Real-time Question Answering","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"ecnu-at-semeval-2016-task-3-exploring","title":"ECNU at SemEval-2016 Task 3: Exploring Traditional Method and Deep Learning Method for Question Retrieval and Answer Ranking in Community Question Answering","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"icl00-at-semeval-2016-task-3-translation","title":"ICL00 at SemEval-2016 Task 3: Translation-Based Method for CQA System","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"itnlp-aikf-at-semeval-2016-task-3-a-quesiton","title":"ITNLP-AiKF at SemEval-2016 Task 3 a quesiton answering system using community QA repository","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"joint-learning-with-global-inference-for","title":"Joint Learning with Global Inference for Comment Classification in Community Question Answering","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/kelp-at-semeval-2016-task-3-learning-semantic","slug":"kelp-at-semeval-2016-task-3-learning-semantic","title":"KeLP at SemEval-2016 Task 3: Learning Semantic Relations between Questions and Answers","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"mte-nn-at-semeval-2016-task-3-can-machine","title":"MTE-NN at SemEval-2016 Task 3: Can Machine Translation Evaluation Help Community Question Answering?","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"overfitting-at-semeval-2016-task-3-detecting","title":"Overfitting at SemEval-2016 Task 3: Detecting Semantically Similar Questions in Community Question Answering Forums with Word Embeddings","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pmi-cool-at-semeval-2016-task-3-experiments","title":"PMI-cool at SemEval-2016 Task 3: Experiments with PMI and Goodness Polarity Lexicons for Community Question Answering","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"qu-ir-at-semeval-2016-task-3-learning-to-rank","title":"QU-IR at SemEval 2016 Task 3: Learning to Rank on Arabic Community Question Answering Forums with Word Embedding","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sls-at-semeval-2016-task-3-neural-based","title":"SLS at SemEval-2016 Task 3: Neural-based Approaches for Ranking in Community Question Answering","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"syntactic-parsing-of-web-queries-with","title":"Syntactic Parsing of Web Queries with Question Intent","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"unimelb-at-semeval-2016-task-3-identifying","title":"UniMelb at SemEval-2016 Task 3: Identifying Similar Questions by combining a CNN with String Similarity Measures","date":"2016-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"recurrent-neural-network-encoder-with","title":"Recurrent Neural Network Encoder with Attention for Community Question Answering","date":"2016-03-23","arxiv_id":"1603.07044","repositories_listed":0,"syntology":null}],"record_sha256":"fc63bf6ed940f1ab74cdf8027c4cc39fffd33042e374129a291f16bd4087ad5a","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}