{"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/descriptive/papers/11","list_of":"/task/descriptive","task":"Descriptive","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":11,"pages_in_order":15,"rows_per_page":100,"rows":[1001,1100],"of":1477,"counts":{"archive_papers_tagged":1477,"with_a_code_link":462,"where_syntology_ran_a_sample":99,"not_listed_spam_title":0,"listed":1477,"listed_where_code_ran":99,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":78,"every_run_a_failure_of_syntologys_instrument":21,"listed_with_a_run_with_no_instrument_failure":78,"listed_every_run_a_failure_of_syntologys_instrument":21,"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/descriptive","prev":"/task/descriptive/papers/10","next":"/task/descriptive/papers/12","papers":[{"url":null,"slug":"zero-shot-visual-grounding-of-referring","title":"Zero-Shot Visual Grounding of Referring Utterances in Dialogue","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"internationalizing-ai-evolution-and-impact-of","title":"Internationalizing AI: Evolution and Impact of Distance Factors","date":"2021-11-10","arxiv_id":"2112.01231","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-quantitative-and-qualitative-citation","title":"A quantitative and qualitative open citation analysis of retracted articles in the humanities","date":"2021-11-09","arxiv_id":"2111.05223","repositories_listed":0,"syntology":null},{"url":null,"slug":"what-goes-on-inside-rumour-and-non-rumour","title":"What goes on inside rumour and non-rumour tweets and their reactions: A Psycholinguistic Analyses","date":"2021-11-09","arxiv_id":"2112.03003","repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-entity-knowledge-for-fact","title":"Modeling Entity Knowledge for Fact Verification","date":"2021-11-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-personalized-diagnostic-generation","title":"A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data","date":"2021-10-26","arxiv_id":"2110.13677","repositories_listed":0,"syntology":null},{"url":null,"slug":"genni-human-ai-collaboration-for-data-backed","title":"GenNI: Human-AI Collaboration for Data-Backed Text Generation","date":"2021-10-19","arxiv_id":"2110.10185","repositories_listed":0,"syntology":null},{"url":null,"slug":"gait-based-human-identification-through","title":"Gait-based Human Identification through Minimum Gait-phases and Sensors","date":"2021-10-15","arxiv_id":"2110.09286","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-forest-behind-the-tree-heterogeneity-in","title":"The Forest Behind the Tree: Heterogeneity in How US Governor's Party Affects Black Workers","date":"2021-10-01","arxiv_id":"2110.00582","repositories_listed":0,"syntology":null},{"url":null,"slug":"distributional-perturbation-for-efficient","title":"Distributional Perturbation for Efficient Exploration in Distributional Reinforcement Learning","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-the-quality-of-sources-in-wikidata","title":"Assessing the quality of sources in Wikidata across languages: a hybrid approach","date":"2021-09-20","arxiv_id":"2109.09405","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-modification-attention-based","title":"Cross Modification Attention Based Deliberation Model for Image Captioning","date":"2021-09-17","arxiv_id":"2109.08411","repositories_listed":0,"syntology":null},{"url":null,"slug":"navigation-oriented-scene-understanding-for","title":"Navigation-Oriented Scene Understanding for Robotic Autonomy: Learning to Segment Driveability in Egocentric Images","date":"2021-09-15","arxiv_id":"2109.07245","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-constraints-and-descriptive","title":"Learning Constraints and Descriptive Segmentation for Subevent Detection","date":"2021-09-13","arxiv_id":"2109.06316","repositories_listed":0,"syntology":null},{"url":"/paper/refinecap-concept-aware-refinement-for-image","slug":"refinecap-concept-aware-refinement-for-image","title":"RefineCap: Concept-Aware Refinement for Image Captioning","date":"2021-09-08","arxiv_id":"2109.03529","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-agent-inverse-reinforcement-learning-2","title":"Multi-Agent Inverse Reinforcement Learning: Suboptimal Demonstrations and Alternative Solution Concepts","date":"2021-09-02","arxiv_id":"2109.01178","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-conditionality-for-natural","title":"Multimodal Conditionality for Natural Language Generation","date":"2021-09-02","arxiv_id":"2109.01229","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-learning-system-for-automatic","title":"A Deep Learning System for Automatic Extraction of Typological Linguistic Information from Descriptive Grammars","date":"2021-09-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"extractive-and-abstractive-sentence-labelling","title":"Extractive and Abstractive Sentence Labelling of Sentiment-bearing Topics","date":"2021-08-29","arxiv_id":"2108.12822","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-propaganda-detection-in-news","title":"Interpretable Propaganda Detection in News Articles","date":"2021-08-29","arxiv_id":"2108.12802","repositories_listed":0,"syntology":null},{"url":null,"slug":"goal-driven-text-descriptions-for-images","title":"Goal-driven text descriptions for images","date":"2021-08-28","arxiv_id":"2108.12575","repositories_listed":0,"syntology":null},{"url":"/paper/multi-attributed-and-structured-text-to-face","slug":"multi-attributed-and-structured-text-to-face","title":"Multi-Attributed and Structured Text-to-Face Synthesis","date":"2021-08-25","arxiv_id":"2108.11100","repositories_listed":0,"syntology":null},{"url":null,"slug":"effect-of-share-capital-on-financial-growth","title":"Effect of Share Capital on Financial Growth of Non-Financial Firms Listed at the Nairobi Securities Exchange","date":"2021-08-23","arxiv_id":"2108.10244","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-cute-is-pikachu-gathering-and-ranking","title":"How Cute is Pikachu? Gathering and Ranking Pokémon Properties from Data with Pokémon Word Embeddings","date":"2021-08-21","arxiv_id":"2108.09546","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-cerebellar-disorders-with-wearable","title":"Assessing Cerebellar Disorders With Wearable Inertial Sensor Data Using Time-Frequency and Autoregressive Hidden Markov Model Approaches","date":"2021-08-20","arxiv_id":"2108.08975","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-based-explainable-ai-leveraging","title":"Semantic-Based Explainable AI: Leveraging Semantic Scene Graphs and Pairwise Ranking to Explain Robot Failures","date":"2021-08-08","arxiv_id":"2108.03554","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-enriched-event-causality","title":"Knowledge-Enriched Event Causality Identification via Latent Structure Induction Networks","date":"2021-08-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-thorough-review-on-recent-deep-learning","title":"A Thorough Review on Recent Deep Learning Methodologies for Image Captioning","date":"2021-07-28","arxiv_id":"2107.13114","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-vehicle-pedestrian-interactions","title":"Analyzing vehicle pedestrian interactions combining data cube structure and predictive collision risk estimation model","date":"2021-07-26","arxiv_id":"2107.12507","repositories_listed":0,"syntology":null},{"url":null,"slug":"massive-feature-extraction-for-explaining-and","title":"Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale","date":"2021-07-25","arxiv_id":"2108.00846","repositories_listed":0,"syntology":null},{"url":null,"slug":"disentangling-and-vectorization-a-3d-visual","title":"Disentangling and Vectorization: A 3D Visual Perception Approach for Autonomous Driving Based on Surround-View Fisheye Cameras","date":"2021-07-19","arxiv_id":"2107.08862","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-use-of-corpora-in-an-interdisciplinary","title":"The Use of Corpora in an Interdisciplinary Approach to Localization","date":"2021-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dense-graph-convolutional-neural-networks-on","title":"Dense Graph Convolutional Neural Networks on 3D Meshes for 3D Object Segmentation and Classification","date":"2021-06-30","arxiv_id":"2106.15778","repositories_listed":0,"syntology":null},{"url":null,"slug":"diff2dist-learning-spectrally-distinct-edge","title":"Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis","date":"2021-06-29","arxiv_id":"2106.15716","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-technical-document","title":"Deep Learning for Technical Document Classification","date":"2021-06-27","arxiv_id":"2106.14269","repositories_listed":0,"syntology":null},{"url":null,"slug":"descriptive-modeling-of-textiles-using-fe","title":"Descriptive Modeling of Textiles using FE Simulations and Deep Learning","date":"2021-06-26","arxiv_id":"2106.13982","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-picture-may-be-worth-a-hundred-words-for","title":"A Picture May Be Worth a Hundred Words for Visual Question Answering","date":"2021-06-25","arxiv_id":"2106.13445","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-infused-policy-gradients-with-upper","title":"Knowledge Infused Policy Gradients with Upper Confidence Bound for Relational Bandits","date":"2021-06-25","arxiv_id":"2106.13895","repositories_listed":0,"syntology":null},{"url":null,"slug":"alternative-microfoundations-for-strategic","title":"Alternative Microfoundations for Strategic Classification","date":"2021-06-24","arxiv_id":"2106.12705","repositories_listed":0,"syntology":null},{"url":null,"slug":"multivariate-data-explanation-by-jumping","title":"Multivariate Data Explanation by Jumping Emerging Patterns Visualization","date":"2021-06-21","arxiv_id":"2106.11112","repositories_listed":0,"syntology":null},{"url":null,"slug":"patchwise-generative-convnet-training-energy","title":"Patchwise Generative ConvNet: Training Energy-Based Models From a Single Natural Image for Internal Learning","date":"2021-06-19","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-effect-of-client-appraisal-on-the","title":"The Effect of Client Appraisal on the Efficiency of Micro Finance Bank","date":"2021-06-14","arxiv_id":"2106.07679","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-bridge-between-physiological-and-perceptual","title":"Bridging physiological and perceptual views of autism by means of sampling-based Bayesian inference","date":"2021-06-08","arxiv_id":"2106.04366","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-the-success-of-domain-adaptation","title":"Predicting the Success of Domain Adaptation in Text Similarity","date":"2021-06-08","arxiv_id":"2106.04641","repositories_listed":0,"syntology":null},{"url":null,"slug":"distortion-measure-of-spectrograms-for","title":"Distortion measure of spectrograms for classification of respiratory diseases","date":"2021-06-04","arxiv_id":"2106.02429","repositories_listed":0,"syntology":null},{"url":null,"slug":"mortality-analysis-of-early-covid-19-cases-in","title":"Mortality Analysis of Early COVID-19 Cases in the Philippines Based on Observed Demographic and Clinical Characteristics","date":"2021-06-03","arxiv_id":"2106.03563","repositories_listed":0,"syntology":null},{"url":null,"slug":"measuring-biases-of-word-embeddings-what","title":"Measuring Biases of Word Embeddings: What Similarity Measures and Descriptive Statistics to Use?","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"nlm-at-mediqa-2021-transfer-learning-based","title":"NLM at MEDIQA 2021: Transfer Learning-based Approaches for Consumer Question and Multi-Answer Summarization","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"reconsidering-annotator-disagreement-about","title":"Reconsidering Annotator Disagreement about Racist Language: Noise or Signal?","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"spanpredict-extraction-of-predictive-document","title":"SpanPredict: Extraction of Predictive Document Spans with Neural Attention","date":"2021-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"sketch-and-refine-towards-faithful-and","title":"Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation","date":"2021-05-31","arxiv_id":"2105.14778","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-data-driven-strategy-to-combine-word","title":"A data-driven strategy to combine word embeddings in information retrieval","date":"2021-05-26","arxiv_id":"2105.12788","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-descriptive-clustering","title":"Deep Descriptive Clustering","date":"2021-05-24","arxiv_id":"2105.11549","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-the-effect-of-credit-collection","title":"Evaluating the Effect of Credit Collection Policy on Portfolio Quality of Micro-Finance Bank","date":"2021-05-23","arxiv_id":"2105.10991","repositories_listed":0,"syntology":null},{"url":null,"slug":"gssf-a-generative-sequence-similarity","title":"GSSF: A Generative Sequence Similarity Function based on a Seq2Seq model for clustering online handwritten mathematical answers","date":"2021-05-21","arxiv_id":"2105.10159","repositories_listed":0,"syntology":null},{"url":null,"slug":"prospects-for-multi-omics-in-the-microbial","title":"Prospects for Multi-omics in the Microbial Ecology of Water Engineering","date":"2021-05-18","arxiv_id":"2105.08856","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-risk-based-active-learning-for-structural","title":"On risk-based active learning for structural health monitoring","date":"2021-05-12","arxiv_id":"2105.05622","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-similarity-analysis-for-evaluation-of","title":"Text similarity analysis for evaluation of descriptive answers","date":"2021-05-06","arxiv_id":"2105.02935","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-logic-of-graph-neural-networks","title":"The Logic of Graph Neural Networks","date":"2021-04-29","arxiv_id":"2104.14624","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-generation-of-descriptive-titles","title":"Automatic Generation of Descriptive Titles for Video Clips Using Deep Learning","date":"2021-04-07","arxiv_id":"2104.03337","repositories_listed":0,"syntology":null},{"url":null,"slug":"urysohn-forest-for-aleatoric-uncertainty","title":"Detecting of multi-modality in probabilistic regression models","date":"2021-04-04","arxiv_id":"2104.01714","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploratory-analysis-of-news-sentiment-using","title":"Exploratory Analysis of News Sentiment Using Subgroup Discovery","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"reanalyzing-the-most-probable-sentence","title":"Reanalyzing the Most Probable Sentence Problem: A Case Study in Explicating the Role of Entropy in Algorithmic Complexity","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"using-linguistic-features-to-predict-the","title":"Using Linguistic Features to Predict the Response Process Complexity Associated with Answering Clinical MCQs","date":"2021-04-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-systematic-literature-review-on-process-1","title":"A Systematic Literature Review on Process-Aware Recommender Systems","date":"2021-03-30","arxiv_id":"2103.16654","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial-spectral-hyperspectral-image","title":"Spatial-spectral Hyperspectral Image Classification via Multiple Random Anchor Graphs Ensemble Learning","date":"2021-03-25","arxiv_id":"2103.13710","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-autoencoder-based-vehicle","title":"Variational Autoencoder-Based Vehicle Trajectory Prediction with an Interpretable Latent Space","date":"2021-03-25","arxiv_id":"2103.13726","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-generate-code-comments-from-class","title":"Learning to Generate Code Comments from Class Hierarchies","date":"2021-03-24","arxiv_id":"2103.13426","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-the-inner-life-of-neural-networks","title":"Exploring the Inner Life of Neural Networks with Robust Rules","date":"2021-03-23","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"geometric-change-detection-in-digital-twins","title":"Geometric Change Detection in Digital Twins using 3D Machine Learning","date":"2021-03-15","arxiv_id":"2103.08201","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-driven-description-synthesis-for","title":"Knowledge driven Description Synthesis for Floor Plan Interpretation","date":"2021-03-15","arxiv_id":"2103.08298","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-methods-for-screening-patients","title":"Deep learning methods for screening patients' S-ICD implantation eligibility","date":"2021-03-10","arxiv_id":"2103.06021","repositories_listed":0,"syntology":null},{"url":null,"slug":"2d-histology-meets-3d-topology","title":"2D histology meets 3D topology: Cytoarchitectonic brain mapping with Graph Neural Networks","date":"2021-03-09","arxiv_id":"2103.05259","repositories_listed":0,"syntology":null},{"url":null,"slug":"contextually-guided-convolutional-neural","title":"CG-CNN: Self-Supervised Feature Extraction Through Contextual Guidance and Transfer Learning","date":"2021-03-02","arxiv_id":"2103.01566","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-origination-and-distribution-of-money","title":"The Origination and Distribution of Money Market Instruments: Sterling Bills of Exchange during the First Globalization","date":"2021-03-02","arxiv_id":"2103.01558","repositories_listed":0,"syntology":null},{"url":null,"slug":"integrating-automated-segmentation-and","title":"Integrating Automated Segmentation and Glossing into Documentary and Descriptive Linguistics","date":"2021-03-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"lrg-at-trec-2020-document-ranking-with-xlnet","title":"LRG at TREC 2020: Document Ranking with XLNet-Based Models","date":"2021-02-28","arxiv_id":"2103.00380","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-extraction-from-co-occurring","title":"Information Extraction From Co-Occurring Similar Entities","date":"2021-02-10","arxiv_id":"2102.05444","repositories_listed":0,"syntology":null},{"url":null,"slug":"aps-a-large-scale-multi-modal-indoor-camera","title":"APS: A Large-Scale Multi-Modal Indoor Camera Positioning System","date":"2021-02-08","arxiv_id":"2102.04139","repositories_listed":0,"syntology":null},{"url":null,"slug":"counting-protests-in-news-articles-a-dataset","title":"Counting Protests in News Articles: A Dataset and Semi-Automated Data Collection Pipeline","date":"2021-02-01","arxiv_id":"2102.00917","repositories_listed":0,"syntology":null},{"url":null,"slug":"monotone-additive-statistics","title":"Monotone additive statistics","date":"2021-02-01","arxiv_id":"2102.00618","repositories_listed":0,"syntology":null},{"url":null,"slug":"revamp-enhancing-accessible-information","title":"Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision Users","date":"2021-02-01","arxiv_id":"2102.00576","repositories_listed":0,"syntology":null},{"url":null,"slug":"beyond-expertise-and-roles-a-framework-to","title":"Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs","date":"2021-01-24","arxiv_id":"2101.09824","repositories_listed":0,"syntology":null},{"url":null,"slug":"descriptive-ai-ethics-collecting-and","title":"Descriptive AI Ethics: Collecting and Understanding the Public Opinion","date":"2021-01-15","arxiv_id":"2101.05957","repositories_listed":0,"syntology":null},{"url":null,"slug":"bypassing-the-random-input-mixing-in-mixup","title":"Bypassing the Random Input Mixing in Mixup","date":"2021-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-and-predicting-purchase-intent-in-e","title":"Analyzing and Predicting Purchase Intent in E-commerce: Anonymous vs. Identified Customers","date":"2020-12-16","arxiv_id":"2012.08777","repositories_listed":0,"syntology":null},{"url":null,"slug":"analyzing-the-performance-of-smart-industry-4","title":"Analyzing the Performance of Smart Industry 4.0 Applications on Cloud Computing Systems","date":"2020-12-11","arxiv_id":"2012.06054","repositories_listed":0,"syntology":null},{"url":"/paper/scan2cap-context-aware-dense-captioning-in","slug":"scan2cap-context-aware-dense-captioning-in","title":"Scan2Cap: Context-aware Dense Captioning in RGB-D Scans","date":"2020-12-03","arxiv_id":"2012.02206","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-grammatical-sketch-of-asur-a-north-munda","title":"A Grammatical Sketch of Asur: A North Munda language","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bert-based-simplification-of-japanese","title":"BERT-Based Simplification of Japanese Sentence-Ending Predicates in Descriptive Text","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"retrieval-augmented-controllable-review","title":"Retrieval-Augmented Controllable Review Generation","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"scaa-a-dataset-for-automated-short-answer","title":"ScAA: A Dataset for Automated Short Answer Grading of Children’s free-text Answers in Hindi and Marathi","date":"2020-12-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"vidi-descriptive-visual-data-clustering-as","title":"ViDi: Descriptive Visual Data Clustering as Radiologist Assistant in COVID-19 Streamline Diagnostic","date":"2020-11-30","arxiv_id":"2011.14871","repositories_listed":0,"syntology":null},{"url":null,"slug":"relation-clustering-in-narrative-knowledge","title":"Relation Clustering in Narrative Knowledge Graphs","date":"2020-11-27","arxiv_id":"2011.13647","repositories_listed":0,"syntology":null},{"url":null,"slug":"transdisciplinary-ai-observatory","title":"Transdisciplinary AI Observatory -- Retrospective Analyses and Future-Oriented Contradistinctions","date":"2020-11-26","arxiv_id":"2012.02592","repositories_listed":0,"syntology":null},{"url":null,"slug":"modelling-compositionality-and-structure","title":"Modelling Compositionality and Structure Dependence in Natural Language","date":"2020-11-22","arxiv_id":"2012.02038","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-teacher-student-chatroom-corpus","title":"The Teacher-Student Chatroom Corpus","date":"2020-11-13","arxiv_id":"2011.07109","repositories_listed":0,"syntology":null},{"url":null,"slug":"medical-symptom-recognition-from-patient-text","title":"Medical symptom recognition from patient text: An active learning approach for long-tailed multilabel distributions","date":"2020-11-12","arxiv_id":"2011.06874","repositories_listed":0,"syntology":null},{"url":null,"slug":"effect-of-short-term-debt-on-financial-growth","title":"Effect of Short-Term Debt on Financial Growth of Non-Financial Firms Listed at Nairobi Securities Exchange","date":"2020-11-05","arxiv_id":"2011.03339","repositories_listed":0,"syntology":null},{"url":null,"slug":"dual-attention-on-pyramid-feature-maps-for","title":"Dual Attention on Pyramid Feature Maps for Image Captioning","date":"2020-11-02","arxiv_id":"2011.01385","repositories_listed":0,"syntology":null}],"record_sha256":"c613ab605cf5327e73b50d577713406f0e43d130c4d4160da68843f916882c24","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}