{"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/transfer-learning/papers/66","list_of":"/task/transfer-learning","task":"Transfer 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":66,"pages_in_order":104,"rows_per_page":100,"rows":[6501,6600],"of":10307,"counts":{"archive_papers_tagged":10307,"with_a_code_link":3502,"where_syntology_ran_a_sample":692,"not_listed_spam_title":0,"listed":10307,"listed_where_code_ran":692,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":563,"every_run_a_failure_of_syntologys_instrument":129,"listed_with_a_run_with_no_instrument_failure":563,"listed_every_run_a_failure_of_syntologys_instrument":129,"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/transfer-learning","prev":"/task/transfer-learning/papers/65","next":"/task/transfer-learning/papers/67","papers":[{"url":null,"slug":"pingan-omini-sinitic-at-semeval-2022-task-4","title":"PINGAN Omini-Sinitic at SemEval-2022 Task 4: Multi-prompt Training for Patronizing and Condescending Language Detection","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pruning-adatperfusion-with-lottery-ticket-1","title":"Pruning Adatperfusion with Lottery Ticket Hypothesis","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"team-innovators-at-semeval-2022-for-task-8","title":"Team Innovators at SemEval-2022 for Task 8: Multi-Task Training with Hyperpartisan and Semantic Relation for Multi-Lingual News Article Similarity","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-importance-of-the-instantaneous-phase-for","title":"The Importance of the Instantaneous Phase for classification using Convolutional Neural Networks","date":"2022-07-01","arxiv_id":"2207.00672","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-specificity-and-helpfulness-of-peer-to","title":"The Specificity and Helpfulness of Peer-to-Peer Feedback in Higher Education","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"training-novices-the-role-of-human-ai","title":"Training Novices: The Role of Human-AI Collaboration and Knowledge Transfer","date":"2022-07-01","arxiv_id":"2207.00497","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-and-masked-generation-for","title":"Transfer Learning and Masked Generation for Answer Verbalization","date":"2022-07-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-networks-can-learn-representations","title":"Neural Networks can Learn Representations with Gradient Descent","date":"2022-06-30","arxiv_id":"2206.15144","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial-transformer-network-with-transfer","title":"Spatial Transformer Network with Transfer Learning for Small-scale Fine-grained Skeleton-based Tai Chi Action Recognition","date":"2022-06-30","arxiv_id":"2206.15002","repositories_listed":0,"syntology":null},{"url":null,"slug":"ecg-heartbeat-classification-using-deep","title":"ECG Heartbeat classification using deep transfer learning with Convolutional Neural Network and STFT technique","date":"2022-06-28","arxiv_id":"2206.14200","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-view-independent-classification-framework","title":"A View Independent Classification Framework for Yoga Postures","date":"2022-06-27","arxiv_id":"2206.13577","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-cross-lingual-tts-using-transferable","title":"Few-Shot Cross-Lingual TTS Using Transferable Phoneme Embedding","date":"2022-06-27","arxiv_id":"2206.15427","repositories_listed":0,"syntology":null},{"url":null,"slug":"guillotine-regularization-improving-deep","title":"Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning","date":"2022-06-27","arxiv_id":"2206.13378","repositories_listed":0,"syntology":null},{"url":null,"slug":"linguistic-correlation-analysis-discovering","title":"Discovering Salient Neurons in Deep NLP Models","date":"2022-06-27","arxiv_id":"2206.13288","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-ensembles-reducing","title":"Transfer learning for ensembles: reducing computation time and keeping the diversity","date":"2022-06-27","arxiv_id":"2206.13116","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-via-test-time-neural","title":"Transfer Learning via Test-Time Neural Networks Aggregation","date":"2022-06-27","arxiv_id":"2206.13399","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicting-the-need-for-blood-transfusion-in","title":"Predicting the Need for Blood Transfusion in Intensive Care Units with Reinforcement Learning","date":"2022-06-26","arxiv_id":"2206.14198","repositories_listed":0,"syntology":null},{"url":null,"slug":"asymmetric-transfer-hashing-with-adaptive","title":"Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning","date":"2022-06-25","arxiv_id":"2206.12592","repositories_listed":0,"syntology":null},{"url":null,"slug":"defense-against-adversarial-attacks-on-deep","title":"Defense against adversarial attacks on deep convolutional neural networks through nonlocal denoising","date":"2022-06-25","arxiv_id":"2206.12685","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-approach-for-analysis-of-distributed","title":"An Intensity and Phase Stacked Analysis of Phase-OTDR System using Deep Transfer Learning and Recurrent Neural Networks","date":"2022-06-24","arxiv_id":"2206.12484","repositories_listed":0,"syntology":null},{"url":null,"slug":"aggregated-multi-output-gaussian-processes","title":"Aggregated Multi-output Gaussian Processes with Knowledge Transfer Across Domains","date":"2022-06-24","arxiv_id":"2206.12141","repositories_listed":0,"syntology":null},{"url":null,"slug":"attention-guided-autoencoder-for-automated","title":"Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI","date":"2022-06-24","arxiv_id":"2206.12480","repositories_listed":0,"syntology":null},{"url":null,"slug":"automatic-extraction-of-coronary-arteries","title":"Automatic extraction of coronary arteries using deep learning in invasive coronary angiograms","date":"2022-06-24","arxiv_id":"2206.12300","repositories_listed":0,"syntology":null},{"url":null,"slug":"mutual-information-guided-knowledge-transfer","title":"Mutual Information-guided Knowledge Transfer for Novel Class Discovery","date":"2022-06-24","arxiv_id":"2206.12063","repositories_listed":0,"syntology":null},{"url":null,"slug":"template-based-approach-to-zero-shot-intent","title":"Template-based Approach to Zero-shot Intent Recognition","date":"2022-06-22","arxiv_id":"2206.10914","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-transfer-learning-based-ensemble","title":"A Transfer-Learning Based Ensemble Architecture for ECG Signal Classification","date":"2022-06-21","arxiv_id":"2207.00002","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-efficient-industrial-federated-learning","title":"An Efficient Industrial Federated Learning Framework for AIoT: A Face Recognition Application","date":"2022-06-21","arxiv_id":"2206.13398","repositories_listed":0,"syntology":null},{"url":null,"slug":"mestereo-du2cnn-a-novel-dual-channel-cnn-for","title":"MEStereo-Du2CNN: A Novel Dual Channel CNN for Learning Robust Depth Estimates from Multi-exposure Stereo Images for HDR 3D Applications","date":"2022-06-21","arxiv_id":"2206.10375","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-neural-network-based-method-with-transfer","title":"A Neural Network Based Method with Transfer Learning for Genetic Data Analysis","date":"2022-06-20","arxiv_id":"2206.09872","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-empirical-analysis-on-the-vulnerabilities","title":"An Empirical Analysis on the Vulnerabilities of End-to-End Speech Segregation Models","date":"2022-06-20","arxiv_id":"2206.09556","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-representation-of-eeg-data-from-spatio","title":"Deep representation of EEG data from Spatio-Spectral Feature Images","date":"2022-06-20","arxiv_id":"2206.09807","repositories_listed":0,"syntology":null},{"url":null,"slug":"remote-sensing-image-classification-using","title":"Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network","date":"2022-06-20","arxiv_id":"2206.13392","repositories_listed":0,"syntology":null},{"url":null,"slug":"agricultural-plantation-classification-using","title":"Agricultural Plantation Classification using Transfer Learning Approach based on CNN","date":"2022-06-19","arxiv_id":"2206.09420","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-multi-task-transferable-rewards-via","title":"Learning Multi-Task Transferable Rewards via Variational Inverse Reinforcement Learning","date":"2022-06-19","arxiv_id":"2206.09498","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-neural-data-server-a-data-1","title":"Scalable Neural Data Server: A Data Recommender for Transfer Learning","date":"2022-06-19","arxiv_id":"2206.09386","repositories_listed":0,"syntology":null},{"url":null,"slug":"terrain-classification-using-transfer","title":"Terrain Classification using Transfer Learning on Hyperspectral Images: A Comparative study","date":"2022-06-19","arxiv_id":"2206.09414","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-robust-low-resource","title":"Transfer Learning for Robust Low-Resource Children's Speech ASR with Transformers and Source-Filter Warping","date":"2022-06-19","arxiv_id":"2206.09396","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-computational-intelligence-based","title":"A Survey on Computational Intelligence-based Transfer Learning","date":"2022-06-17","arxiv_id":"2206.10593","repositories_listed":0,"syntology":null},{"url":null,"slug":"covid-19-detection-using-transfer-learning","title":"COVID-19 Detection using Transfer Learning with Convolutional Neural Network","date":"2022-06-17","arxiv_id":"2206.08557","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-classification-of-brain-tumor-images","title":"Multi-Classification of Brain Tumor Images Using Transfer Learning Based Deep Neural Network","date":"2022-06-17","arxiv_id":"2206.08543","repositories_listed":0,"syntology":null},{"url":null,"slug":"tleta-deep-transfer-learning-and-integrated","title":"TLETA: Deep Transfer Learning and Integrated Cellular Knowledge for Estimated Time of Arrival Prediction","date":"2022-06-17","arxiv_id":"2206.08513","repositories_listed":0,"syntology":null},{"url":null,"slug":"assessing-the-value-of-transfer-learning","title":"Assessing the Value of Transfer Learning Metrics for RF Domain Adaptation","date":"2022-06-16","arxiv_id":"2206.08329","repositories_listed":0,"syntology":null},{"url":null,"slug":"draft-a-novel-framework-to-reduce-domain","title":"DRAFT: A Novel Framework to Reduce Domain Shifting in Self-supervised Learning and Its Application to Children's ASR","date":"2022-06-16","arxiv_id":"2206.07931","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-continual-learning-truly-learning","title":"Towards Diverse Evaluation of Class Incremental Learning: A Representation Learning Perspective","date":"2022-06-16","arxiv_id":"2206.08101","repositories_listed":0,"syntology":null},{"url":null,"slug":"longitudinal-detection-of-new-ms-lesions","title":"Longitudinal detection of new MS lesions using Deep Learning","date":"2022-06-16","arxiv_id":"2206.08272","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-scale-feature-extraction-and-fusion-for","title":"Multi scale Feature Extraction and Fusion for Online Knowledge Distillation","date":"2022-06-16","arxiv_id":"2206.08224","repositories_listed":0,"syntology":null},{"url":null,"slug":"recursive-neural-programs-variational","title":"Recursive Neural Programs: Variational Learning of Image Grammars and Part-Whole Hierarchies","date":"2022-06-16","arxiv_id":"2206.08462","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-decision-time-vs-background","title":"A Look at Value-Based Decision-Time vs. Background Planning Methods Across Different Settings","date":"2022-06-16","arxiv_id":"2206.08442","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-novel-implementation-of-machine-learning","title":"A Novel Implementation of Machine Learning for the Efficient, Explainable Diagnosis of COVID-19 from Chest CT","date":"2022-06-15","arxiv_id":"2207.07117","repositories_listed":0,"syntology":null},{"url":null,"slug":"lessons-learned-from-the-neurips-2021-metadl","title":"Lessons learned from the NeurIPS 2021 MetaDL challenge: Backbone fine-tuning without episodic meta-learning dominates for few-shot learning image classification","date":"2022-06-15","arxiv_id":"2206.08138","repositories_listed":0,"syntology":null},{"url":null,"slug":"subsurface-depths-structure-maps","title":"Subsurface Depths Structure Maps Reconstruction with Generative Adversarial Networks","date":"2022-06-15","arxiv_id":"2206.07388","repositories_listed":0,"syntology":null},{"url":null,"slug":"freekd-free-direction-knowledge-distillation","title":"FreeKD: Free-direction Knowledge Distillation for Graph Neural Networks","date":"2022-06-14","arxiv_id":"2206.06561","repositories_listed":0,"syntology":null},{"url":null,"slug":"freetransfer-x-safe-and-label-free-cross","title":"FreeTransfer-X: Safe and Label-Free Cross-Lingual Transfer from Off-the-Shelf Models","date":"2022-06-14","arxiv_id":"2206.06586","repositories_listed":0,"syntology":null},{"url":null,"slug":"physics-informed-transfer-learning-strategy","title":"Residual-based physics-informed transfer learning: A hybrid method for accelerating long-term CFD simulations via deep learning","date":"2022-06-14","arxiv_id":"2206.06817","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-discriminative-mixup-for","title":"Semantic-Discriminative Mixup for Generalizable Sensor-based Cross-domain Activity Recognition","date":"2022-06-14","arxiv_id":"2206.06629","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-for-rapid-extraction-of","title":"Tackling Data Scarcity with Transfer Learning: A Case Study of Thickness Characterization from Optical Spectra of Perovskite Thin Films","date":"2022-06-14","arxiv_id":"2207.02209","repositories_listed":0,"syntology":null},{"url":null,"slug":"anomaly-detection-and-inter-sensor-transfer","title":"Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets","date":"2022-06-13","arxiv_id":"2206.06355","repositories_listed":0,"syntology":null},{"url":null,"slug":"transrec-learning-transferable-recommendation","title":"TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback","date":"2022-06-13","arxiv_id":"2206.06190","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepemotex-classifying-emotion-in-text","title":"DeepEmotex: Classifying Emotion in Text Messages using Deep Transfer Learning","date":"2022-06-12","arxiv_id":"2206.06775","repositories_listed":0,"syntology":null},{"url":null,"slug":"pac-net-a-model-pruning-approach-to-inductive","title":"PAC-Net: A Model Pruning Approach to Inductive Transfer Learning","date":"2022-06-12","arxiv_id":"2206.05703","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-correlation-ratio-transfer-learning-and","title":"A Correlation-Ratio Transfer Learning and Variational Stein's Paradox","date":"2022-06-10","arxiv_id":"2206.06086","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-per-shot-convex-hull-prediction-by","title":"Convex Hull Prediction for Adaptive Video Streaming by Recurrent Learning","date":"2022-06-10","arxiv_id":"2206.04877","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-transfer-learning-in-functional-linear","title":"On Hypothesis Transfer Learning of Functional Linear Models","date":"2022-06-09","arxiv_id":"2206.04277","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-missing-link-finding-label-relations","title":"The Missing Link: Finding label relations across datasets","date":"2022-06-09","arxiv_id":"2206.04453","repositories_listed":0,"syntology":null},{"url":null,"slug":"hub-pathway-transfer-learning-from-a-hub-of","title":"Hub-Pathway: Transfer Learning from A Hub of Pre-trained Models","date":"2022-06-08","arxiv_id":"2206.03726","repositories_listed":0,"syntology":null},{"url":null,"slug":"modularized-transfer-learning-with-multiple-1","title":"Modularized Transfer Learning with Multiple Knowledge Graphs for Zero-shot Commonsense Reasoning","date":"2022-06-08","arxiv_id":"2206.03715","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-collapse-a-review-on-modelling","title":"Neural Collapse: A Review on Modelling Principles and Generalization","date":"2022-06-08","arxiv_id":"2206.04041","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-to-decode-brain-states","title":"Transfer learning to decode brain states reflecting the relationship between cognitive tasks","date":"2022-06-07","arxiv_id":"2206.03950","repositories_listed":0,"syntology":null},{"url":null,"slug":"morisienmt-a-dataset-for-mauritian-creole","title":"MorisienMT: A Dataset for Mauritian Creole Machine Translation","date":"2022-06-06","arxiv_id":"2206.02421","repositories_listed":0,"syntology":null},{"url":null,"slug":"relation-matters-foreground-aware-graph-based","title":"Relation Matters: Foreground-aware Graph-based Relational Reasoning for Domain Adaptive Object Detection","date":"2022-06-06","arxiv_id":"2206.02355","repositories_listed":0,"syntology":null},{"url":null,"slug":"topological-optimized-convolutional-visual","title":"CTVR-EHO TDA-IPH Topological Optimized Convolutional Visual Recurrent Network for Brain Tumor Segmentation and Classification","date":"2022-06-06","arxiv_id":"2207.13021","repositories_listed":0,"syntology":null},{"url":null,"slug":"transbo-hyperparameter-optimization-via-two","title":"TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning","date":"2022-06-06","arxiv_id":"2206.02663","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-based-search-space-design","title":"Transfer Learning based Search Space Design for Hyperparameter Tuning","date":"2022-06-06","arxiv_id":"2206.02511","repositories_listed":0,"syntology":null},{"url":null,"slug":"metanor-a-meta-learnt-nonlocal-operator","title":"MetaNOR: A Meta-Learnt Nonlocal Operator Regression Approach for Metamaterial Modeling","date":"2022-06-04","arxiv_id":"2206.02040","repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-learning-meets-transfer-learning","title":"Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation","date":"2022-06-03","arxiv_id":"2206.01369","repositories_listed":0,"syntology":null},{"url":null,"slug":"enriching-a-fashion-knowledge-graph-from","title":"Enriching a Fashion Knowledge Graph from Product Textual Descriptions","date":"2022-06-02","arxiv_id":"2206.01087","repositories_listed":0,"syntology":null},{"url":null,"slug":"examining-the-behaviour-of-state-of-the-art","title":"Examining the behaviour of state-of-the-art convolutional neural networks for brain tumor detection with and without transfer learning","date":"2022-06-02","arxiv_id":"2206.01735","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-language-selection-for-zero-shot","title":"Transfer Language Selection for Zero-Shot Cross-Lingual Abusive Language Detection","date":"2022-06-02","arxiv_id":"2206.00962","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-corpus-for-commonsense-inference-in-story","title":"A Corpus for Commonsense Inference in Story Cloze Test","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dataset-of-offensive-language-in-kosovo","title":"A Dataset of Offensive Language in Kosovo Social Media","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deep-transfer-learning-method-for-cross","title":"A Deep Transfer Learning Method for Cross-Lingual Natural Language Inference","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-systematic-study-reveals-unexpected","title":"A Systematic Study Reveals Unexpected Interactions in Pre-Trained Neural Machine Translation","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bazinga-a-dataset-for-multi-party-dialogues","title":"Bazinga! A Dataset for Multi-Party Dialogues Structuring","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"bea-base-a-benchmark-for-asr-of-spontaneous-1","title":"BEA-Base: A Benchmark for ASR of Spontaneous Hungarian","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-lingual-and-cross-domain-transfer","title":"Cross-lingual and Cross-domain Transfer Learning for Automatic Term Extraction from Low Resource Data","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"domain-mismatch-doesnt-always-prevent-cross","title":"Domain Mismatch Doesn’t Always Prevent Cross-lingual Transfer Learning","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"embeddings-models-for-buddhist-sanskrit","title":"Embeddings models for Buddhist Sanskrit","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluating-gaussian-grasp-maps-for-generative","title":"Evaluating Gaussian Grasp Maps for Generative Grasping Models","date":"2022-06-01","arxiv_id":"2206.00432","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluation-of-transfer-learning-and-domain","title":"Evaluation of Transfer Learning and Domain Adaptation for Analyzing German-Speaking Job Advertisements","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-transfer-learning-for-urdu-speech","title":"Exploring Transfer Learning for Urdu Speech Synthesis","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-signer-independent-sign-language","title":"Improving Signer Independent Sign Language Recognition for Low Resource Languages","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"multilingual-transfer-learning-for-children","title":"Multilingual Transfer Learning for Children Automatic Speech Recognition","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"negation-detection-in-dutch-spoken-human","title":"Negation Detection in Dutch Spoken Human-Computer Conversations","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"quality-versus-quantity-building-catalan","title":"Quality versus Quantity: Building Catalan-English MT Resources","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"resources-and-experiments-on-sentiment","title":"Resources and Experiments on Sentiment Classification for Georgian","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"supervised-denoising-of-diffusion-weighted","title":"Supervised Denoising of Diffusion-Weighted Magnetic Resonance Images Using a Convolutional Neural Network and Transfer Learning","date":"2022-06-01","arxiv_id":"2206.00305","repositories_listed":0,"syntology":null},{"url":null,"slug":"text-to-speech-for-under-resourced-languages","title":"Text-to-Speech for Under-Resourced Languages: Phoneme Mapping and Source Language Selection in Transfer Learning","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"the-elements-of-flexibility-for-task","title":"The elements of flexibility for task-performing systems","date":"2022-06-01","arxiv_id":"2206.00582","repositories_listed":0,"syntology":null},{"url":null,"slug":"transfer-learning-methods-for-domain","title":"Transfer Learning Methods for Domain Adaptation in Technical Logbook Datasets","date":"2022-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"a-cross-city-federated-transfer-learning","title":"A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling","date":"2022-05-31","arxiv_id":"2206.00007","repositories_listed":0,"syntology":null}],"record_sha256":"6fb39a4c360e35ca9dfb75ec6a9d59edcf02f2e7eba6af01aaf6c4ea95deebb5","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}