{"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/multi-task-learning/papers/12","list_of":"/task/multi-task-learning","task":"Multi-Task Learning","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":12,"pages_in_order":37,"rows_per_page":100,"rows":[1101,1200],"of":3687,"counts":{"archive_papers_tagged":3687,"with_a_code_link":1306,"where_syntology_ran_a_sample":260,"not_listed_spam_title":0,"listed":3687,"listed_where_code_ran":260,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":217,"every_run_a_failure_of_syntologys_instrument":43,"listed_with_a_run_with_no_instrument_failure":217,"listed_every_run_a_failure_of_syntologys_instrument":43,"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/multi-task-learning","prev":"/task/multi-task-learning/papers/11","next":"/task/multi-task-learning/papers/13","papers":[{"url":"/paper/multi-task-reinforcement-learning-with-soft","slug":"multi-task-reinforcement-learning-with-soft","title":"Multi-Task Reinforcement Learning with Soft Modularization","date":"2020-03-30","arxiv_id":"2003.13661","repositories_listed":1,"syntology":null},{"url":"/paper/a-unified-object-motion-and-affinity-model","slug":"a-unified-object-motion-and-affinity-model","title":"A Unified Object Motion and Affinity Model for Online Multi-Object Tracking","date":"2020-03-25","arxiv_id":"2003.11291","repositories_listed":1,"syntology":null},{"url":"/paper/learned-weight-sharing-for-deep-multi-task","slug":"learned-weight-sharing-for-deep-multi-task","title":"Learned Weight Sharing for Deep Multi-Task Learning by Natural Evolution Strategy and Stochastic Gradient Descent","date":"2020-03-23","arxiv_id":"2003.10159","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learned-weight-sharing-for-deep-multi-task#ran","syntology_url":"https://syntology.ai/paper/2003.10159","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2003.10159"}},"official":{"repos":["jprellberg/learned-weight-sharing"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/multi-task-learning-enhanced-single-image-de","slug":"multi-task-learning-enhanced-single-image-de","title":"Multi-Task Learning Enhanced Single Image De-Raining","date":"2020-03-21","arxiv_id":"2003.09689","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-learning-with-coarse-priors-for","slug":"multi-task-learning-with-coarse-priors-for","title":"Multi-task Learning with Coarse Priors for Robust Part-aware Person Re-identification","date":"2020-03-18","arxiv_id":"2003.08069","repositories_listed":1,"syntology":null},{"url":"/paper/evaluating-logical-generalization-in-graph","slug":"evaluating-logical-generalization-in-graph","title":"Evaluating Logical Generalization in Graph Neural Networks","date":"2020-03-14","arxiv_id":"2003.06560","repositories_listed":1,"syntology":null},{"url":"/paper/bi-directional-attention-for-joint-instance","slug":"bi-directional-attention-for-joint-instance","title":"Bi-Directional Attention for Joint Instance and Semantic Segmentation in Point Clouds","date":"2020-03-11","arxiv_id":"2003.05420","repositories_listed":1,"syntology":null},{"url":"/paper/ap-mtl-attention-pruned-multi-task-learning","slug":"ap-mtl-attention-pruned-multi-task-learning","title":"AP-MTL: Attention Pruned Multi-task Learning Model for Real-time Instrument Detection and Segmentation in Robot-assisted Surgery","date":"2020-03-10","arxiv_id":"2003.04769","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-learning-based-neural-bridging","slug":"multi-task-learning-based-neural-bridging","title":"Multi-task Learning Based Neural Bridging Reference Resolution","date":"2020-03-07","arxiv_id":"2003.03666","repositories_listed":1,"syntology":null},{"url":"/paper/is-pos-tagging-necessary-or-even-helpful-for","slug":"is-pos-tagging-necessary-or-even-helpful-for","title":"Is POS Tagging Necessary or Even Helpful for Neural Dependency Parsing?","date":"2020-03-06","arxiv_id":"2003.03204","repositories_listed":1,"syntology":null},{"url":"/paper/unsupervised-and-interpretable-domain","slug":"unsupervised-and-interpretable-domain","title":"Unsupervised and Interpretable Domain Adaptation to Rapidly Filter Tweets for Emergency Services","date":"2020-03-04","arxiv_id":"2003.04991","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-walk-in-the-real-world-with","slug":"learning-to-walk-in-the-real-world-with","title":"Learning to Walk in the Real World with Minimal Human Effort","date":"2020-02-20","arxiv_id":"2002.08550","repositories_listed":1,"syntology":null},{"url":"/paper/speech-to-singing-conversion-in-an-encoder","slug":"speech-to-singing-conversion-in-an-encoder","title":"Speech-to-Singing Conversion in an Encoder-Decoder Framework","date":"2020-02-16","arxiv_id":"2002.06595","repositories_listed":1,"syntology":null},{"url":"/paper/deeper-task-specificity-improves-joint-entity","slug":"deeper-task-specificity-improves-joint-entity","title":"Deeper Task-Specificity Improves Joint Entity and Relation Extraction","date":"2020-02-15","arxiv_id":"2002.06424","repositories_listed":1,"syntology":null},{"url":"/paper/zero-resource-cross-domain-named-entity","slug":"zero-resource-cross-domain-named-entity","title":"Zero-Resource Cross-Domain Named Entity Recognition","date":"2020-02-14","arxiv_id":"2002.05923","repositories_listed":1,"syntology":null},{"url":"/paper/spotnet-self-attention-multi-task-network-for","slug":"spotnet-self-attention-multi-task-network-for","title":"SpotNet: Self-Attention Multi-Task Network for Object Detection","date":"2020-02-13","arxiv_id":"2002.05540","repositories_listed":1,"syntology":null},{"url":"/paper/deep-multi-task-augmented-feature-learning","slug":"deep-multi-task-augmented-feature-learning","title":"Deep Multi-Task Augmented Feature Learning via Hierarchical Graph Neural Network","date":"2020-02-12","arxiv_id":"2002.04813","repositories_listed":1,"syntology":null},{"url":"/paper/learning-to-incorporate-structure-knowledge","slug":"learning-to-incorporate-structure-knowledge","title":"Learning to Incorporate Structure Knowledge for Image Inpainting","date":"2020-02-11","arxiv_id":"2002.04170","repositories_listed":1,"syntology":{"n":4,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":4,"phrase":"3 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; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/learning-to-incorporate-structure-knowledge#ran","syntology_url":"https://syntology.ai/paper/2002.04170","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.04170"}},"official":{"repos":["YoungGod/sturcture-inpainting"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/lane-detection-in-low-light-conditions-using","slug":"lane-detection-in-low-light-conditions-using","title":"Lane Detection in Low-light Conditions Using an Efficient Data Enhancement : Light Conditions Style Transfer","date":"2020-02-04","arxiv_id":"2002.01177","repositories_listed":1,"syntology":null},{"url":"/paper/facial-affect-recognition-in-the-wild-using","slug":"facial-affect-recognition-in-the-wild-using","title":"Facial Affect Recognition in the Wild Using Multi-Task Learning Convolutional Network","date":"2020-02-03","arxiv_id":"2002.00606","repositories_listed":1,"syntology":null},{"url":"/paper/bridging-text-and-video-a-universal","slug":"bridging-text-and-video-a-universal","title":"Bridging Text and Video: A Universal Multimodal Transformer for Video-Audio Scene-Aware Dialog","date":"2020-02-01","arxiv_id":"2002.00163","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":3,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/bridging-text-and-video-a-universal#ran","syntology_url":"https://syntology.ai/paper/2002.00163","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2002.00163"}},"official":null}},{"url":"/paper/incorporating-joint-embeddings-into-goal","slug":"incorporating-joint-embeddings-into-goal","title":"Incorporating Joint Embeddings into Goal-Oriented Dialogues with Multi-Task Learning","date":"2020-01-28","arxiv_id":"2001.10468","repositories_listed":1,"syntology":null},{"url":"/paper/deepfl-iqa-weak-supervision-for-deep-iqa","slug":"deepfl-iqa-weak-supervision-for-deep-iqa","title":"DeepFL-IQA: Weak Supervision for Deep IQA Feature Learning","date":"2020-01-20","arxiv_id":"2001.08113","repositories_listed":1,"syntology":null},{"url":"/paper/mti-net-multi-scale-task-interaction-networks","slug":"mti-net-multi-scale-task-interaction-networks","title":"MTI-Net: Multi-Scale Task Interaction Networks for Multi-Task Learning","date":"2020-01-19","arxiv_id":"2001.06902","repositories_listed":1,"syntology":null},{"url":"/paper/a-knowledge-enhanced-pretraining-model-for","slug":"a-knowledge-enhanced-pretraining-model-for","title":"A Knowledge-Enhanced Pretraining Model for Commonsense Story Generation","date":"2020-01-15","arxiv_id":"2001.05139","repositories_listed":1,"syntology":null},{"url":"/paper/stance-detection-benchmark-how-robust-is-your","slug":"stance-detection-benchmark-how-robust-is-your","title":"Stance Detection Benchmark: How Robust Is Your Stance Detection?","date":"2020-01-06","arxiv_id":"2001.01565","repositories_listed":1,"syntology":{"n":10,"n_ran":9,"n_constructed":0,"n_ran_checked":9,"n_instrument":0,"n_unverified":1,"n_honours":2,"n_violates":0,"n_no_contract":7,"n_pointer_only":2,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 2 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/stance-detection-benchmark-how-robust-is-your#ran","syntology_url":"https://syntology.ai/paper/2001.01565","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2001.01565"}},"official":{"repos":["UKPLab/mdl-stance-robustness"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/on-identifying-hashtags-in-disaster-twitter","slug":"on-identifying-hashtags-in-disaster-twitter","title":"On Identifying Hashtags in Disaster Twitter Data","date":"2020-01-05","arxiv_id":"2001.01323","repositories_listed":1,"syntology":null},{"url":"/paper/two-level-transformer-and-auxiliary-coherence","slug":"two-level-transformer-and-auxiliary-coherence","title":"Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentation","date":"2020-01-03","arxiv_id":"2001.00891","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-learning-with-user-preferences","slug":"multi-task-learning-with-user-preferences","title":"Multi-Task Learning with User Preferences: Gradient Descent with Controlled Ascent in Pareto Optimization","date":"2020-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/pareto-multi-task-learning-1","slug":"pareto-multi-task-learning-1","title":"Pareto Multi-Task Learning","date":"2019-12-30","arxiv_id":"1912.12854","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"0 ran · 1 unverified","sample_list":"/paper/pareto-multi-task-learning-1#ran","syntology_url":"https://syntology.ai/paper/1912.12854","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.12854"}},"official":{"repos":["Xi-L/ParetoMTL"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"url":"/paper/an-attention-based-graph-neural-network-for","slug":"an-attention-based-graph-neural-network-for","title":"An Attention-based Graph Neural Network for Heterogeneous Structural Learning","date":"2019-12-19","arxiv_id":"1912.10832","repositories_listed":1,"syntology":{"n":3,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"0 ran · 3 unverified","sample_list":"/paper/an-attention-based-graph-neural-network-for#ran","syntology_url":"https://syntology.ai/paper/1912.10832","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1912.10832"}},"official":{"repos":["didi/hetsann"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":[]}}},{"url":"/paper/internal-transfer-weighting-of-multi-task","slug":"internal-transfer-weighting-of-multi-task","title":"Internal-transfer Weighting of Multi-task Learning for Lung Cancer Detection","date":"2019-12-16","arxiv_id":"1912.07167","repositories_listed":1,"syntology":null},{"url":"/paper/synchronous-speech-recognition-and-speech-to","slug":"synchronous-speech-recognition-and-speech-to","title":"Synchronous Speech Recognition and Speech-to-Text Translation with Interactive Decoding","date":"2019-12-16","arxiv_id":"1912.07240","repositories_listed":1,"syntology":null},{"url":"/paper/regularizing-deep-multi-task-networks-using-1","slug":"regularizing-deep-multi-task-networks-using-1","title":"Regularizing Deep Multi-Task Networks using Orthogonal Gradients","date":"2019-12-14","arxiv_id":"1912.06844","repositories_listed":1,"syntology":null},{"url":"/paper/generalized-block-diagonal-structure-pursuit","slug":"generalized-block-diagonal-structure-pursuit","title":"Generalized Block-Diagonal Structure Pursuit: Learning Soft Latent Task Assignment against Negative Transfer","date":"2019-12-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/constructing-multiple-tasks-for-augmentation","slug":"constructing-multiple-tasks-for-augmentation","title":"Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means Features","date":"2019-11-18","arxiv_id":"1911.07518","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-learning-of-height-and-semantics","slug":"multi-task-learning-of-height-and-semantics","title":"Multi-Task Learning of Height and Semantics from Aerial Images","date":"2019-11-18","arxiv_id":"1911.07543","repositories_listed":1,"syntology":null},{"url":"/paper/an-application-of-multiple-instance-learning","slug":"an-application-of-multiple-instance-learning","title":"Simplified and Unified Analysis of Various Learning Problems by Reduction to Multiple-Instance Learning","date":"2019-11-14","arxiv_id":"1911.05999","repositories_listed":1,"syntology":null},{"url":"/paper/a-syntax-aware-multi-task-learning-framework-1","slug":"a-syntax-aware-multi-task-learning-framework-1","title":"A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling","date":"2019-11-12","arxiv_id":"1911.04641","repositories_listed":1,"syntology":null},{"url":"/paper/learning-sparse-sharing-architectures-for","slug":"learning-sparse-sharing-architectures-for","title":"Learning Sparse Sharing Architectures for Multiple Tasks","date":"2019-11-12","arxiv_id":"1911.05034","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-deep-multi-task-learning-for","slug":"dynamic-deep-multi-task-learning-for","title":"Dynamic Deep Multi-task Learning for Caricature-Visual Face Recognition","date":"2019-11-08","arxiv_id":"1911.03341","repositories_listed":1,"syntology":null},{"url":"/paper/dynamic-multi-task-learning-for-face","slug":"dynamic-multi-task-learning-for-face","title":"Dynamic Multi-Task Learning for Face Recognition with Facial Expression","date":"2019-11-08","arxiv_id":"1911.03281","repositories_listed":1,"syntology":null},{"url":"/paper/a-joint-model-for-definition-extraction-with","slug":"a-joint-model-for-definition-extraction-with","title":"A Joint Model for Definition Extraction with Syntactic Connection and Semantic Consistency","date":"2019-11-05","arxiv_id":"1911.01678","repositories_listed":1,"syntology":null},{"url":"/paper/fcsr-gan-joint-face-completion-and-super","slug":"fcsr-gan-joint-face-completion-and-super","title":"FCSR-GAN: Joint Face Completion and Super-resolution via Multi-task Learning","date":"2019-11-04","arxiv_id":"1911.01045","repositories_listed":1,"syntology":null},{"url":"/paper/d-net-a-pre-training-and-fine-tuning","slug":"d-net-a-pre-training-and-fine-tuning","title":"D-NET: A Pre-Training and Fine-Tuning Framework for Improving the Generalization of Machine Reading Comprehension","date":"2019-11-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/select-answer-and-explain-interpretable-multi","slug":"select-answer-and-explain-interpretable-multi","title":"Select, Answer and Explain: Interpretable Multi-hop Reading Comprehension over Multiple Documents","date":"2019-11-01","arxiv_id":"1911.00484","repositories_listed":1,"syntology":{"n":15,"n_ran":12,"n_constructed":0,"n_ran_checked":12,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":12,"n_pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/select-answer-and-explain-interpretable-multi#ran","syntology_url":"https://syntology.ai/paper/1911.00484","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1911.00484"}},"official":null}},{"url":"/paper/decoupling-adaptation-from-modeling-with-meta-1","slug":"decoupling-adaptation-from-modeling-with-meta-1","title":"When MAML Can Adapt Fast and How to Assist When It Cannot","date":"2019-10-30","arxiv_id":"1910.13603","repositories_listed":1,"syntology":null},{"url":"/paper/drvot-measuring-positive-and-negative-voice","slug":"drvot-measuring-positive-and-negative-voice","title":"Dr.VOT : Measuring Positive and Negative Voice Onset Time in the Wild","date":"2019-10-27","arxiv_id":"1910.13255","repositories_listed":1,"syntology":null},{"url":"/paper/human-keypoint-detection-by-progressive","slug":"human-keypoint-detection-by-progressive","title":"Human Keypoint Detection by Progressive Context Refinement","date":"2019-10-27","arxiv_id":"1910.12223","repositories_listed":1,"syntology":null},{"url":"/paper/mrqa-2019-shared-task-evaluating","slug":"mrqa-2019-shared-task-evaluating","title":"MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension","date":"2019-10-22","arxiv_id":"1910.09753","repositories_listed":1,"syntology":{"n":3,"n_ran":3,"n_constructed":0,"n_ran_checked":2,"n_instrument":1,"n_unverified":0,"n_honours":1,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 1 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/mrqa-2019-shared-task-evaluating#ran","syntology_url":"https://syntology.ai/paper/1910.09753","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1910.09753"}},"official":{"repos":["mrqa/MRQA-Shared-Task-2019"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/rethinking-data-augmentation-self-supervision-1","slug":"rethinking-data-augmentation-self-supervision-1","title":"Self-supervised Label Augmentation via Input Transformations","date":"2019-10-14","arxiv_id":"1910.05872","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-learning-for-conversational","slug":"multi-task-learning-for-conversational","title":"Multi-Task Learning for Conversational Question Answering over a Large-Scale Knowledge Base","date":"2019-10-11","arxiv_id":"1910.05069","repositories_listed":1,"syntology":null},{"url":"/paper/neurreg-neural-registration-and-its","slug":"neurreg-neural-registration-and-its","title":"NeurReg: Neural Registration and Its Application to Image Segmentation","date":"2019-10-04","arxiv_id":"1910.01763","repositories_listed":1,"syntology":null},{"url":"/paper/on-the-detection-of-digital-face-manipulation","slug":"on-the-detection-of-digital-face-manipulation","title":"On the Detection of Digital Face Manipulation","date":"2019-10-03","arxiv_id":"1910.01717","repositories_listed":1,"syntology":null},{"url":"/paper/joint-acne-image-grading-and-counting-via","slug":"joint-acne-image-grading-and-counting-via","title":"Joint Acne Image Grading and Counting via Label Distribution Learning","date":"2019-10-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/gated-task-interaction-framework-for-multi","slug":"gated-task-interaction-framework-for-multi","title":"Gated Task Interaction Framework for Multi-task Sequence Tagging","date":"2019-09-29","arxiv_id":"1909.13193","repositories_listed":1,"syntology":null},{"url":"/paper/learning-a-unified-named-entity-tagger-from","slug":"learning-a-unified-named-entity-tagger-from","title":"Learning A Unified Named Entity Tagger From Multiple Partially Annotated Corpora For Efficient Adaptation","date":"2019-09-25","arxiv_id":"1909.11535","repositories_listed":1,"syntology":null},{"url":"/paper/190910008","slug":"190910008","title":"Multi-task Learning and Catastrophic Forgetting in Continual Reinforcement Learning","date":"2019-09-22","arxiv_id":"1909.10008","repositories_listed":1,"syntology":null},{"url":"/paper/meta-neighborhoods","slug":"meta-neighborhoods","title":"Meta-Neighborhoods","date":"2019-09-18","arxiv_id":"1909.09140","repositories_listed":1,"syntology":null},{"url":"/paper/progression-modelling-for-online-and-early","slug":"progression-modelling-for-online-and-early","title":"Progression Modelling for Online and Early Gesture Detection","date":"2019-09-14","arxiv_id":"1909.06672","repositories_listed":1,"syntology":null},{"url":"/paper/towards-open-domain-named-entity-recognition","slug":"towards-open-domain-named-entity-recognition","title":"Neural Correction Model for Open-Domain Named Entity Recognition","date":"2019-09-13","arxiv_id":"1909.06058","repositories_listed":1,"syntology":null},{"url":"/paper/learning-vector-valued-functions-with-local","slug":"learning-vector-valued-functions-with-local","title":"Semi-supervised Vector-valued Learning: Improved Bounds and Algorithms","date":"2019-09-11","arxiv_id":"1909.04883","repositories_listed":1,"syntology":null},{"url":"/paper/joint-learning-of-saliency-detection-and","slug":"joint-learning-of-saliency-detection-and","title":"Joint Learning of Saliency Detection and Weakly Supervised Semantic Segmentation","date":"2019-09-09","arxiv_id":"1909.04161","repositories_listed":1,"syntology":null},{"url":"/paper/informing-unsupervised-pretraining-with","slug":"informing-unsupervised-pretraining-with","title":"Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity","date":"2019-09-05","arxiv_id":"1909.02339","repositories_listed":1,"syntology":null},{"url":"/paper/ncls-neural-cross-lingual-summarization","slug":"ncls-neural-cross-lingual-summarization","title":"NCLS: Neural Cross-Lingual Summarization","date":"2019-08-31","arxiv_id":"1909.00156","repositories_listed":1,"syntology":null},{"url":"/paper/improving-neural-story-generation-by-targeted","slug":"improving-neural-story-generation-by-targeted","title":"Improving Neural Story Generation by Targeted Common Sense Grounding","date":"2019-08-26","arxiv_id":"1908.09451","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":0,"n_instrument":4,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/improving-neural-story-generation-by-targeted#ran","syntology_url":"https://syntology.ai/paper/1908.09451","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.09451"}},"official":{"repos":["calclavia/story-generation"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/a-neural-model-for-dialogue-coherence","slug":"a-neural-model-for-dialogue-coherence","title":"Dialogue Coherence Assessment Without Explicit Dialogue Act Labels","date":"2019-08-22","arxiv_id":"1908.08486","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/a-neural-model-for-dialogue-coherence#ran","syntology_url":"https://syntology.ai/paper/1908.08486","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1908.08486"}},"official":{"repos":["UKPLab/acl2020-dialogue-coherence-assessment"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/190807885","slug":"190807885","title":"Representation Disentanglement for Multi-task Learning with application to Fetal Ultrasound","date":"2019-08-21","arxiv_id":"1908.07885","repositories_listed":1,"syntology":null},{"url":"/paper/a-single-shot-arbitrarily-shaped-text","slug":"a-single-shot-arbitrarily-shaped-text","title":"A Single-Shot Arbitrarily-Shaped Text Detector based on Context Attended Multi-Task Learning","date":"2019-08-15","arxiv_id":"1908.05498","repositories_listed":1,"syntology":null},{"url":"/paper/conv-mcd-a-plug-and-play-multi-task-module","slug":"conv-mcd-a-plug-and-play-multi-task-module","title":"Conv-MCD: A Plug-and-Play Multi-task Module for Medical Image Segmentation","date":"2019-08-14","arxiv_id":"1908.05311","repositories_listed":1,"syntology":null},{"url":"/paper/detecting-semantic-anomalies","slug":"detecting-semantic-anomalies","title":"Detecting semantic anomalies","date":"2019-08-13","arxiv_id":"1908.04388","repositories_listed":1,"syntology":null},{"url":"/paper/um-adapt-unsupervised-multi-task-adaptation","slug":"um-adapt-unsupervised-multi-task-adaptation","title":"UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation","date":"2019-08-11","arxiv_id":"1908.03884","repositories_listed":1,"syntology":null},{"url":"/paper/improving-robustness-of-neural-machine","slug":"improving-robustness-of-neural-machine","title":"Improving Robustness of Neural Machine Translation with Multi-task Learning","date":"2019-08-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/city-classification-from-multiple-real-world","slug":"city-classification-from-multiple-real-world","title":"City classification from multiple real-world sound scenes","date":"2019-07-29","arxiv_id":"1905.00979","repositories_listed":1,"syntology":null},{"url":"/paper/multidepth-single-image-depth-estimation-via","slug":"multidepth-single-image-depth-estimation-via","title":"MultiDepth: Single-Image Depth Estimation via Multi-Task Regression and Classification","date":"2019-07-25","arxiv_id":"1907.11111","repositories_listed":1,"syntology":null},{"url":"/paper/joint-learning-of-multiple-image-restoration","slug":"joint-learning-of-multiple-image-restoration","title":"Restoring Images with Unknown Degradation Factors by Recurrent Use of a Multi-branch Network","date":"2019-07-10","arxiv_id":"1907.04508","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-learning-for-coherence-modeling","slug":"multi-task-learning-for-coherence-modeling","title":"Multi-Task Learning for Coherence Modeling","date":"2019-07-04","arxiv_id":"1907.02427","repositories_listed":1,"syntology":null},{"url":"/paper/semi-supervised-domain-adaptation-for","slug":"semi-supervised-domain-adaptation-for","title":"Semi-supervised Domain Adaptation for Dependency Parsing","date":"2019-07-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/text-categorization-by-learning-predominant","slug":"text-categorization-by-learning-predominant","title":"Text Categorization by Learning Predominant Sense of Words as Auxiliary Task","date":"2019-07-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/multi-criteria-chinese-word-segmentation-with","slug":"multi-criteria-chinese-word-segmentation-with","title":"A Concise Model for Multi-Criteria Chinese Word Segmentation with Transformer Encoder","date":"2019-06-28","arxiv_id":"1906.12035","repositories_listed":1,"syntology":null},{"url":"/paper/compositional-semantic-parsing-across","slug":"compositional-semantic-parsing-across","title":"Compositional Semantic Parsing Across Graphbanks","date":"2019-06-27","arxiv_id":"1906.11746","repositories_listed":1,"syntology":null},{"url":"/paper/semi-supervised-learning-with-self-supervised","slug":"semi-supervised-learning-with-self-supervised","title":"Exploring Self-Supervised Regularization for Supervised and Semi-Supervised Learning","date":"2019-06-25","arxiv_id":"1906.10343","repositories_listed":1,"syntology":null},{"url":"/paper/equant-enhanced-question-answer-network","slug":"equant-enhanced-question-answer-network","title":"EQuANt (Enhanced Question Answer Network)","date":"2019-06-24","arxiv_id":"1907.00708","repositories_listed":1,"syntology":null},{"url":"/paper/graph-star-net-for-generalized-multi-task-1","slug":"graph-star-net-for-generalized-multi-task-1","title":"Graph Star Net for Generalized Multi-Task Learning","date":"2019-06-21","arxiv_id":"1906.12330","repositories_listed":1,"syntology":{"n":6,"n_ran":2,"n_constructed":0,"n_ran_checked":1,"n_instrument":1,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/graph-star-net-for-generalized-multi-task-1#ran","syntology_url":"https://syntology.ai/paper/1906.12330","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.12330"}},"official":null}},{"url":"/paper/improving-sentiment-analysis-with-multi-task","slug":"improving-sentiment-analysis-with-multi-task","title":"Improving Sentiment Analysis with Multi-task Learning of Negation","date":"2019-06-18","arxiv_id":"1906.07610","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-learning-for-detecting-and","slug":"multi-task-learning-for-detecting-and","title":"Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos","date":"2019-06-17","arxiv_id":"1906.06876","repositories_listed":1,"syntology":{"n":5,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_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) · 3 unverified","sample_list":"/paper/multi-task-learning-for-detecting-and#ran","syntology_url":"https://syntology.ai/paper/1906.06876","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.06876"}},"official":null}},{"url":"/paper/continual-and-multi-task-architecture-search","slug":"continual-and-multi-task-architecture-search","title":"Continual and Multi-Task Architecture Search","date":"2019-06-12","arxiv_id":"1906.05226","repositories_listed":1,"syntology":{"n":12,"n_ran":11,"n_constructed":0,"n_ran_checked":10,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":1,"n_no_contract":9,"n_pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 1 violated, 9 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/continual-and-multi-task-architecture-search#ran","syntology_url":"https://syntology.ai/paper/1906.05226","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1906.05226"}},"official":{"repos":["ramakanth-pasunuru/CAS-MAS"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/multitask-learning-for-network-traffic","slug":"multitask-learning-for-network-traffic","title":"Multitask Learning for Network Traffic Classification","date":"2019-06-12","arxiv_id":"1906.05248","repositories_listed":1,"syntology":null},{"url":"/paper/demo-net-degree-specific-graph-neural","slug":"demo-net-degree-specific-graph-neural","title":"DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification","date":"2019-06-05","arxiv_id":"1906.02319","repositories_listed":1,"syntology":null},{"url":"/paper/multi-task-semantic-dependency-parsing-with","slug":"multi-task-semantic-dependency-parsing-with","title":"Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies","date":"2019-06-04","arxiv_id":"1906.01239","repositories_listed":1,"syntology":null},{"url":"/paper/cyclic-guidance-for-weakly-supervised-joint","slug":"cyclic-guidance-for-weakly-supervised-joint","title":"Cyclic Guidance for Weakly Supervised Joint Detection and Segmentation","date":"2019-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/veritatem-dies-aperit-temporally-consistent-1","slug":"veritatem-dies-aperit-temporally-consistent-1","title":"Veritatem Dies Aperit - Temporally Consistent Depth Prediction Enabled by a Multi-Task Geometric and Semantic Scene Understanding Approach","date":"2019-06-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/190600097","slug":"190600097","title":"Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains","date":"2019-05-31","arxiv_id":"1906.00097","repositories_listed":1,"syntology":null},{"url":"/paper/which-tasks-should-be-learned-together-in","slug":"which-tasks-should-be-learned-together-in","title":"Which Tasks Should Be Learned Together in Multi-task Learning?","date":"2019-05-18","arxiv_id":"1905.07553","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/which-tasks-should-be-learned-together-in#ran","syntology_url":"https://syntology.ai/paper/1905.07553","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1905.07553"}},"official":{"repos":["tstandley/taskgrouping"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/conversion-prediction-using-multi-task","slug":"conversion-prediction-using-multi-task","title":"Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative","date":"2019-05-17","arxiv_id":"1905.07289","repositories_listed":1,"syntology":null},{"url":"/paper/190602127","slug":"190602127","title":"An Approach for Process Model Extraction By Multi-Grained Text Classification","date":"2019-05-16","arxiv_id":"1906.02127","repositories_listed":1,"syntology":null},{"url":"/paper/tucker-tensor-factorization-for-knowledge-1","slug":"tucker-tensor-factorization-for-knowledge-1","title":"TuckER: Tensor Factorization for Knowledge Graph Completion","date":"2019-05-16","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/image-captioning-with-clause-focused-metrics","slug":"image-captioning-with-clause-focused-metrics","title":"Image Captioning with Clause-Focused Metrics in a Multi-Modal Setting for Marketing","date":"2019-05-06","arxiv_id":"1905.01919","repositories_listed":1,"syntology":null},{"url":"/paper/routing-networks-and-the-challenges-of","slug":"routing-networks-and-the-challenges-of","title":"Routing Networks and the Challenges of Modular and Compositional Computation","date":"2019-04-29","arxiv_id":"1904.12774","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_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","sample_list":"/paper/routing-networks-and-the-challenges-of#ran","syntology_url":"https://syntology.ai/paper/1904.12774","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1904.12774"}},"official":null}},{"url":"/paper/holistic-large-scale-video-understanding","slug":"holistic-large-scale-video-understanding","title":"Large Scale Holistic Video Understanding","date":"2019-04-25","arxiv_id":"1904.11451","repositories_listed":1,"syntology":null}],"record_sha256":"bcdd0e846117372b97a0d2ce61c4f76e141b9da933aff9300b06c5f02e709a8d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}