{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/transformer/papers/96","list_of":"/method/transformer","method":"Transformer","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":96,"pages_in_order":140,"rows_per_page":100,"rows":[9501,9600],"of":13999,"counts":{"archive_papers_tagged":13999,"with_a_code_link":6572,"where_syntology_ran_a_sample":2248,"not_listed_spam_title":0,"listed":13999,"listed_where_code_ran":2248,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1919,"every_run_a_failure_of_syntologys_instrument":329,"listed_with_a_run_with_no_instrument_failure":1919,"listed_every_run_a_failure_of_syntologys_instrument":329,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/transformer","prev":"/method/transformer/papers/95","next":"/method/transformer/papers/97","papers":[{"paper":null,"slug":"pair-detr-contrastive-learning-speeds-up-detr","title":"Pair DETR: Contrastive Learning Speeds Up DETR Training","date":"2022-10-29","arxiv_id":"2210.16476","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-long-term-dependent-and-trustworthy","title":"A Long-term Dependent and Trustworthy Approach to Reactor Accident Prognosis based on Temporal Fusion Transformer","date":"2022-10-28","arxiv_id":"2210.17298","n_code_links":0,"syntology":null},{"paper":"/paper/contextual-learning-in-fourier-complex-field","slug":"contextual-learning-in-fourier-complex-field","title":"Contextual Learning in Fourier Complex Field for VHR Remote Sensing Images","date":"2022-10-28","arxiv_id":"2210.15972","n_code_links":3,"syntology":null},{"paper":null,"slug":"dimensionality-reduced-antenna-array-for","title":"Dimensionality Reduced Antenna Array for Beamforming/steering","date":"2022-10-28","arxiv_id":"2210.16197","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-speech-translation-with-dynamic","slug":"efficient-speech-translation-with-dynamic","title":"Efficient Speech Translation with Dynamic Latent Perceivers","date":"2022-10-28","arxiv_id":"2210.16264","n_code_links":1,"syntology":null},{"paper":"/paper/exploring-spatial-temporal-features-for","slug":"exploring-spatial-temporal-features-for","title":"Exploring Spatial-Temporal Features for Deepfake Detection and Localization","date":"2022-10-28","arxiv_id":"2210.15872","n_code_links":1,"syntology":null},{"paper":null,"slug":"grafting-vision-transformers","title":"Grafting Vision Transformers","date":"2022-10-28","arxiv_id":"2210.15943","n_code_links":0,"syntology":null},{"paper":null,"slug":"modeling-structure-building-in-the-brain-with","title":"Modeling structure-building in the brain with CCG parsing and large language models","date":"2022-10-28","arxiv_id":"2210.16147","n_code_links":0,"syntology":null},{"paper":null,"slug":"parameter-efficient-transfer-learning-of-pre","title":"Parameter-efficient transfer learning of pre-trained Transformer models for speaker verification using adapters","date":"2022-10-28","arxiv_id":"2210.16032","n_code_links":0,"syntology":null},{"paper":null,"slug":"psformer-point-transformer-for-3d-salient","title":"PSFormer: Point Transformer for 3D Salient Object Detection","date":"2022-10-28","arxiv_id":"2210.15933","n_code_links":0,"syntology":null},{"paper":null,"slug":"upainting-unified-text-to-image-diffusion","title":"UPainting: Unified Text-to-Image Diffusion Generation with Cross-modal Guidance","date":"2022-10-28","arxiv_id":"2210.16031","n_code_links":0,"syntology":null},{"paper":"/paper/vlt-vision-language-transformer-and-query","slug":"vlt-vision-language-transformer-and-query","title":"VLT: Vision-Language Transformer and Query Generation for Referring Segmentation","date":"2022-10-28","arxiv_id":"2210.15871","n_code_links":1,"syntology":{"ran":3,"of":6,"n_ran_checked":3,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"3 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; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["henghuiding/Vision-Language-Transformer"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/fast-distilbert-on-cpus","slug":"fast-distilbert-on-cpus","title":"Fast DistilBERT on CPUs","date":"2022-10-27","arxiv_id":"2211.07715","n_code_links":1,"syntology":null},{"paper":"/paper/gaitmixer-skeleton-based-gait-representation","slug":"gaitmixer-skeleton-based-gait-representation","title":"GaitMixer: Skeleton-based Gait Representation Learning via Wide-spectrum Multi-axial Mixer","date":"2022-10-27","arxiv_id":"2210.15491","n_code_links":1,"syntology":null},{"paper":null,"slug":"hydra-hgr-a-hybrid-transformer-based","title":"HYDRA-HGR: A Hybrid Transformer-based Architecture for Fusion of Macroscopic and Microscopic Neural Drive Information","date":"2022-10-27","arxiv_id":"2211.02619","n_code_links":0,"syntology":null},{"paper":null,"slug":"li3detr-a-lidar-based-3d-detection","title":"Li3DeTr: A LiDAR based 3D Detection Transformer","date":"2022-10-27","arxiv_id":"2210.15365","n_code_links":0,"syntology":null},{"paper":null,"slug":"make-more-of-your-data-minimal-effort-data","title":"Make More of Your Data: Minimal Effort Data Augmentation for Automatic Speech Recognition and Translation","date":"2022-10-27","arxiv_id":"2210.15398","n_code_links":0,"syntology":null},{"paper":null,"slug":"masked-transformer-for-image-anomaly","title":"Masked Transformer for image Anomaly Localization","date":"2022-10-27","arxiv_id":"2210.15540","n_code_links":0,"syntology":null},{"paper":null,"slug":"msf3ddetr-multi-sensor-fusion-3d-detection","title":"MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving","date":"2022-10-27","arxiv_id":"2210.15316","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-transformer-distillation-for-audio","slug":"multimodal-transformer-distillation-for-audio","title":"Multimodal Transformer Distillation for Audio-Visual Synchronization","date":"2022-10-27","arxiv_id":"2210.15563","n_code_links":2,"syntology":null},{"paper":"/paper/point-voxel-adaptive-feature-abstraction-for","slug":"point-voxel-adaptive-feature-abstraction-for","title":"Point-Voxel Adaptive Feature Abstraction for Robust Point Cloud Classification","date":"2022-10-27","arxiv_id":"2210.15514","n_code_links":1,"syntology":null},{"paper":"/paper/procontext-exploring-progressive-context","slug":"procontext-exploring-progressive-context","title":"ProContEXT: Exploring Progressive Context Transformer for Tracking","date":"2022-10-27","arxiv_id":"2210.15511","n_code_links":4,"syntology":null},{"paper":null,"slug":"spatio-temporal-hybrid-fusion-of-cae-and-swin","title":"Spatio-Temporal Hybrid Fusion of CAE and SWIn Transformers for Lung Cancer Malignancy Prediction","date":"2022-10-27","arxiv_id":"2210.15297","n_code_links":0,"syntology":null},{"paper":"/paper/the-1st-place-solution-for-eccv-2022-multiple","slug":"the-1st-place-solution-for-eccv-2022-multiple","title":"The 1st-place Solution for ECCV 2022 Multiple People Tracking in Group Dance Challenge","date":"2022-10-27","arxiv_id":"2210.15281","n_code_links":3,"syntology":null},{"paper":"/paper/transformers-meet-stochastic-block-models","slug":"transformers-meet-stochastic-block-models","title":"Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost","date":"2022-10-27","arxiv_id":"2210.15541","n_code_links":1,"syntology":null},{"paper":"/paper/what-language-model-to-train-if-you-have-one","slug":"what-language-model-to-train-if-you-have-one","title":"What Language Model to Train if You Have One Million GPU Hours?","date":"2022-10-27","arxiv_id":"2210.15424","n_code_links":1,"syntology":null},{"paper":"/paper/working-alliance-transformer-for","slug":"working-alliance-transformer-for","title":"Working Alliance Transformer for Psychotherapy Dialogue Classification","date":"2022-10-27","arxiv_id":"2210.15603","n_code_links":1,"syntology":null},{"paper":null,"slug":"automatic-diagnosis-of-myocarditis-disease-in","title":"Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence","date":"2022-10-26","arxiv_id":"2210.14611","n_code_links":0,"syntology":null},{"paper":"/paper/disentangling-past-future-modeling-in","slug":"disentangling-past-future-modeling-in","title":"Disentangling Past-Future Modeling in Sequential Recommendation via Dual Networks","date":"2022-10-26","arxiv_id":"2210.14577","n_code_links":1,"syntology":null},{"paper":"/paper/eeny-meeny-miny-moe-how-to-choose-data-for","slug":"eeny-meeny-miny-moe-how-to-choose-data-for","title":"Eeny, meeny, miny, moe. How to choose data for morphological inflection","date":"2022-10-26","arxiv_id":"2210.14465","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-a-task-specific-descriptor-for","title":"Learning a Task-specific Descriptor for Robust Matching of 3D Point Clouds","date":"2022-10-26","arxiv_id":"2210.14899","n_code_links":0,"syntology":null},{"paper":"/paper/leveraging-demonstrations-with-latent-space","slug":"leveraging-demonstrations-with-latent-space","title":"Leveraging Demonstrations with Latent Space Priors","date":"2022-10-26","arxiv_id":"2210.14685","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":3,"phrase":"2 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; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["facebookresearch/latent-space-priors"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"multilevel-transformer-for-multimodal-emotion","title":"Multilevel Transformer For Multimodal Emotion Recognition","date":"2022-10-26","arxiv_id":"2211.07711","n_code_links":0,"syntology":null},{"paper":"/paper/pretrained-audio-neural-networks-for-speech","slug":"pretrained-audio-neural-networks-for-speech","title":"Pretrained audio neural networks for Speech emotion recognition in Portuguese","date":"2022-10-26","arxiv_id":"2210.14716","n_code_links":1,"syntology":null},{"paper":"/paper/semformer-semantic-guided-activation","slug":"semformer-semantic-guided-activation","title":"SemFormer: Semantic Guided Activation Transformer for Weakly Supervised Semantic Segmentation","date":"2022-10-26","arxiv_id":"2210.14618","n_code_links":1,"syntology":null},{"paper":"/paper/xiaoicesing-2-a-high-fidelity-singing-voice","slug":"xiaoicesing-2-a-high-fidelity-singing-voice","title":"Xiaoicesing 2: A High-Fidelity Singing Voice Synthesizer Based on Generative Adversarial Network","date":"2022-10-26","arxiv_id":"2210.14666","n_code_links":1,"syntology":null},{"paper":"/paper/audio-mfcc-gram-transformers-for-respiratory","slug":"audio-mfcc-gram-transformers-for-respiratory","title":"Audio MFCC-gram Transformers for respiratory insufficiency detection in COVID-19","date":"2022-10-25","arxiv_id":"2210.14085","n_code_links":1,"syntology":null},{"paper":null,"slug":"dynamic-survival-transformers-for-causal","title":"Dynamic Survival Transformers for Causal Inference with Electronic Health Records","date":"2022-10-25","arxiv_id":"2210.15417","n_code_links":0,"syntology":null},{"paper":null,"slug":"end-to-end-transformer-for-compressed-video","title":"End-to-end Transformer for Compressed Video Quality Enhancement","date":"2022-10-25","arxiv_id":"2210.13827","n_code_links":0,"syntology":null},{"paper":"/paper/explicitly-increasing-input-information","slug":"explicitly-increasing-input-information","title":"Explicitly Increasing Input Information Density for Vision Transformers on Small Datasets","date":"2022-10-25","arxiv_id":"2210.14319","n_code_links":1,"syntology":{"ran":4,"of":7,"n_ran_checked":2,"n_instrument":2,"unverified":3,"pointer_only":7,"phrase":"4 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["xiangyu8/densevt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/mew-unet-multi-axis-representation-learning","slug":"mew-unet-multi-axis-representation-learning","title":"MEW-UNet: Multi-axis representation learning in frequency domain for medical image segmentation","date":"2022-10-25","arxiv_id":"2210.14007","n_code_links":1,"syntology":null},{"paper":null,"slug":"minutiae-guided-fingerprint-embeddings-via","title":"Minutiae-Guided Fingerprint Embeddings via Vision Transformers","date":"2022-10-25","arxiv_id":"2210.13994","n_code_links":0,"syntology":null},{"paper":"/paper/moformer-self-supervised-transformer-model","slug":"moformer-self-supervised-transformer-model","title":"MOFormer: Self-Supervised Transformer model for Metal-Organic Framework Property Prediction","date":"2022-10-25","arxiv_id":"2210.14188","n_code_links":1,"syntology":null},{"paper":"/paper/thor-net-end-to-end-graformer-based-realistic","slug":"thor-net-end-to-end-graformer-based-realistic","title":"THOR-Net: End-to-end Graformer-based Realistic Two Hands and Object Reconstruction with Self-supervision","date":"2022-10-25","arxiv_id":"2210.13853","n_code_links":1,"syntology":null},{"paper":"/paper/abductive-action-inference","slug":"abductive-action-inference","title":"Inferring Past Human Actions in Homes with Abductive Reasoning","date":"2022-10-24","arxiv_id":"2210.13984","n_code_links":1,"syntology":null},{"paper":null,"slug":"effective-pre-training-objectives-for","title":"Effective Pre-Training Objectives for Transformer-based Autoencoders","date":"2022-10-24","arxiv_id":"2210.13536","n_code_links":0,"syntology":null},{"paper":"/paper/foreground-guidance-and-multi-layer-feature","slug":"foreground-guidance-and-multi-layer-feature","title":"Foreground Guidance and Multi-Layer Feature Fusion for Unsupervised Object Discovery with Transformers","date":"2022-10-24","arxiv_id":"2210.13053","n_code_links":1,"syntology":null},{"paper":"/paper/high-fidelity-neural-audio-compression","slug":"high-fidelity-neural-audio-compression","title":"High Fidelity Neural Audio Compression","date":"2022-10-24","arxiv_id":"2210.13438","n_code_links":6,"syntology":null},{"paper":"/paper/metaformer-baselines-for-vision","slug":"metaformer-baselines-for-vision","title":"MetaFormer Baselines for Vision","date":"2022-10-24","arxiv_id":"2210.13452","n_code_links":8,"syntology":{"ran":1,"of":4,"n_ran_checked":1,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["rwightman/pytorch-image-models","sail-sg/metaformer"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/perfectly-secure-steganography-using-minimum","slug":"perfectly-secure-steganography-using-minimum","title":"Perfectly Secure Steganography Using Minimum Entropy Coupling","date":"2022-10-24","arxiv_id":"2210.14889","n_code_links":2,"syntology":{"ran":1,"of":4,"n_ran_checked":1,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["schroederdewitt/perfectly-secure-steganography"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/sequential-recommendation-with-auxiliary-item","slug":"sequential-recommendation-with-auxiliary-item","title":"Sequential Recommendation with Auxiliary Item Relationships via Multi-Relational Transformer","date":"2022-10-24","arxiv_id":"2210.13572","n_code_links":1,"syntology":null},{"paper":"/paper/video-based-object-6d-pose-estimation-using","slug":"video-based-object-6d-pose-estimation-using","title":"Video based Object 6D Pose Estimation using Transformers","date":"2022-10-24","arxiv_id":"2210.13540","n_code_links":1,"syntology":null},{"paper":"/paper/vlc-bert-visual-question-answering-with","slug":"vlc-bert-visual-question-answering-with","title":"VLC-BERT: Visual Question Answering with Contextualized Commonsense Knowledge","date":"2022-10-24","arxiv_id":"2210.13626","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["aditya10/vlc-bert"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/anticipative-feature-fusion-transformer-for","slug":"anticipative-feature-fusion-transformer-for","title":"Anticipative Feature Fusion Transformer for Multi-Modal Action Anticipation","date":"2022-10-23","arxiv_id":"2210.12649","n_code_links":1,"syntology":null},{"paper":"/paper/delving-into-masked-autoencoders-for-multi","slug":"delving-into-masked-autoencoders-for-multi","title":"Delving into Masked Autoencoders for Multi-Label Thorax Disease Classification","date":"2022-10-23","arxiv_id":"2210.12843","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"1 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; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["lambert-x/medical_mae"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/holistic-interaction-transformer-network-for","slug":"holistic-interaction-transformer-network-for","title":"Holistic Interaction Transformer Network for Action Detection","date":"2022-10-23","arxiv_id":"2210.12686","n_code_links":1,"syntology":null},{"paper":"/paper/on-cross-domain-pre-trained-language-models","slug":"on-cross-domain-pre-trained-language-models","title":"Exploring the Value of Pre-trained Language Models for Clinical Named Entity Recognition","date":"2022-10-23","arxiv_id":"2210.12770","n_code_links":2,"syntology":null},{"paper":null,"slug":"uia-vit-unsupervised-inconsistency-aware","title":"UIA-ViT: Unsupervised Inconsistency-Aware Method based on Vision Transformer for Face Forgery Detection","date":"2022-10-23","arxiv_id":"2210.12752","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comprehensive-comparison-of-neural-networks","title":"A Comprehensive Comparison of Neural Networks as Cognitive Models of Inflection","date":"2022-10-22","arxiv_id":"2210.12321","n_code_links":0,"syntology":null},{"paper":"/paper/ham-hierarchical-attention-model-with-high","slug":"ham-hierarchical-attention-model-with-high","title":"Learning Point-Language Hierarchical Alignment for 3D Visual Grounding","date":"2022-10-22","arxiv_id":"2210.12513","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":0,"n_instrument":1,"unverified":1,"pointer_only":2,"phrase":"1 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; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ppjmchen/ham"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"ms-dc-unext-an-mlp-based-multi-scale-feature","title":"MS-DCANet: A Novel Segmentation Network For Multi-Modality COVID-19 Medical Images","date":"2022-10-22","arxiv_id":"2210.12361","n_code_links":0,"syntology":null},{"paper":null,"slug":"recurrence-boosts-diversity-revisiting","title":"Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation","date":"2022-10-22","arxiv_id":"2210.12409","n_code_links":0,"syntology":null},{"paper":"/paper/s2wat-image-style-transfer-via-hierarchical","slug":"s2wat-image-style-transfer-via-hierarchical","title":"S2WAT: Image Style Transfer via Hierarchical Vision Transformer using Strips Window Attention","date":"2022-10-22","arxiv_id":"2210.12381","n_code_links":1,"syntology":null},{"paper":null,"slug":"speech-emotion-recognition-via-an-attentive","title":"Speech Emotion Recognition via an Attentive Time-Frequency Neural Network","date":"2022-10-22","arxiv_id":"2210.12430","n_code_links":0,"syntology":null},{"paper":"/paper/syngec-syntax-enhanced-grammatical-error","slug":"syngec-syntax-enhanced-grammatical-error","title":"SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented Parser","date":"2022-10-22","arxiv_id":"2210.12484","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformer-based-conditioned-variational","title":"Transformer-Based Conditioned Variational Autoencoder for Dialogue Generation","date":"2022-10-22","arxiv_id":"2210.12326","n_code_links":0,"syntology":null},{"paper":"/paper/context-enhanced-stereo-transformer","slug":"context-enhanced-stereo-transformer","title":"Context-Enhanced Stereo Transformer","date":"2022-10-21","arxiv_id":"2210.11719","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["guoweiyu/context-enhanced-stereo-transformer"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/diffuser-efficient-transformers-with-multi","slug":"diffuser-efficient-transformers-with-multi","title":"Diffuser: Efficient Transformers with Multi-hop Attention Diffusion for Long Sequences","date":"2022-10-21","arxiv_id":"2210.11794","n_code_links":1,"syntology":null},{"paper":"/paper/do-vision-and-language-transformers-learn","slug":"do-vision-and-language-transformers-learn","title":"Do Vision-and-Language Transformers Learn Grounded Predicate-Noun Dependencies?","date":"2022-10-21","arxiv_id":"2210.12079","n_code_links":1,"syntology":null},{"paper":"/paper/face-pyramid-vision-transformer","slug":"face-pyramid-vision-transformer","title":"Face Pyramid Vision Transformer","date":"2022-10-21","arxiv_id":"2210.11974","n_code_links":1,"syntology":null},{"paper":null,"slug":"is-encoder-decoder-redundant-for-neural","title":"Is Encoder-Decoder Redundant for Neural Machine Translation?","date":"2022-10-21","arxiv_id":"2210.11807","n_code_links":0,"syntology":null},{"paper":"/paper/shift-reduce-task-oriented-semantic-parsing","slug":"shift-reduce-task-oriented-semantic-parsing","title":"Shift-Reduce Task-Oriented Semantic Parsing with Stack-Transformers","date":"2022-10-21","arxiv_id":"2210.11984","n_code_links":1,"syntology":null},{"paper":"/paper/syntax-guided-localized-self-attention-by","slug":"syntax-guided-localized-self-attention-by","title":"Syntax-guided Localized Self-attention by Constituency Syntactic Distance","date":"2022-10-21","arxiv_id":"2210.11759","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":1,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["lumia-group/distance_transformer"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/translist-a-transformer-based-linguistically","slug":"translist-a-transformer-based-linguistically","title":"TransLIST: A Transformer-Based Linguistically Informed Sanskrit Tokenizer","date":"2022-10-21","arxiv_id":"2210.11753","n_code_links":1,"syntology":null},{"paper":null,"slug":"identifying-human-strategies-for-generating","title":"Identifying Human Strategies for Generating Word-Level Adversarial Examples","date":"2022-10-20","arxiv_id":"2210.11598","n_code_links":0,"syntology":null},{"paper":"/paper/self-supervised-learning-with-masked-image","slug":"self-supervised-learning-with-masked-image","title":"Self-Supervised Learning with Masked Image Modeling for Teeth Numbering, Detection of Dental Restorations, and Instance Segmentation in Dental Panoramic Radiographs","date":"2022-10-20","arxiv_id":"2210.11404","n_code_links":1,"syntology":null},{"paper":"/paper/simpleclick-interactive-image-segmentation","slug":"simpleclick-interactive-image-segmentation","title":"SimpleClick: Interactive Image Segmentation with Simple Vision Transformers","date":"2022-10-20","arxiv_id":"2210.11006","n_code_links":2,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"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) · 1 unverified","official":{"repos":["uncbiag/simpleclick"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"single-image-super-resolution-using-2","title":"Single Image Super-Resolution Using Lightweight Networks Based on Swin Transformer","date":"2022-10-20","arxiv_id":"2210.11019","n_code_links":0,"syntology":null},{"paper":null,"slug":"solving-reasoning-tasks-with-a-slot","title":"Solving Reasoning Tasks with a Slot Transformer","date":"2022-10-20","arxiv_id":"2210.11394","n_code_links":0,"syntology":null},{"paper":"/paper/ssit-saliency-guided-self-supervised-image","slug":"ssit-saliency-guided-self-supervised-image","title":"SSiT: Saliency-guided Self-supervised Image Transformer for Diabetic Retinopathy Grading","date":"2022-10-20","arxiv_id":"2210.10969","n_code_links":1,"syntology":null},{"paper":"/paper/a-unified-view-of-masked-image-modeling","slug":"a-unified-view-of-masked-image-modeling","title":"A Unified View of Masked Image Modeling","date":"2022-10-19","arxiv_id":"2210.10615","n_code_links":1,"syntology":null},{"paper":"/paper/biogpt-generative-pre-trained-transformer-for","slug":"biogpt-generative-pre-trained-transformer-for","title":"BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining","date":"2022-10-19","arxiv_id":"2210.10341","n_code_links":4,"syntology":null},{"paper":null,"slug":"grounded-video-situation-recognition","title":"Grounded Video Situation Recognition","date":"2022-10-19","arxiv_id":"2210.10828","n_code_links":0,"syntology":null},{"paper":"/paper/language-detoxification-with-attribute","slug":"language-detoxification-with-attribute","title":"Language Detoxification with Attribute-Discriminative Latent Space","date":"2022-10-19","arxiv_id":"2210.10329","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-view-gait-recognition-based-on-siamese","title":"Multi-view Gait Recognition based on Siamese Vision Transformer","date":"2022-10-19","arxiv_id":"2210.10421","n_code_links":0,"syntology":null},{"paper":"/paper/museformer-transformer-with-fine-and-coarse","slug":"museformer-transformer-with-fine-and-coarse","title":"Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation","date":"2022-10-19","arxiv_id":"2210.10349","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":{"repos":["microsoft/muzic"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":"/paper/posegpt-quantization-based-3d-human-motion","slug":"posegpt-quantization-based-3d-human-motion","title":"PoseGPT: Quantization-based 3D Human Motion Generation and Forecasting","date":"2022-10-19","arxiv_id":"2210.10542","n_code_links":1,"syntology":null},{"paper":"/paper/revision-transformers-getting-rit-of-no-nos","slug":"revision-transformers-getting-rit-of-no-nos","title":"Revision Transformers: Instructing Language Models to Change their Values","date":"2022-10-19","arxiv_id":"2210.10332","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformers-learn-shortcuts-to-automata","title":"Transformers Learn Shortcuts to Automata","date":"2022-10-19","arxiv_id":"2210.10749","n_code_links":0,"syntology":null},{"paper":"/paper/a-hybrid-system-of-sound-event-detection","slug":"a-hybrid-system-of-sound-event-detection","title":"A Hybrid System of Sound Event Detection Transformer and Frame-wise Model for DCASE 2022 Task 4","date":"2022-10-18","arxiv_id":"2210.09529","n_code_links":1,"syntology":null},{"paper":"/paper/cross-domain-aspect-extraction-using","slug":"cross-domain-aspect-extraction-using","title":"Cross-Domain Aspect Extraction using Transformers Augmented with Knowledge Graphs","date":"2022-10-18","arxiv_id":"2210.10144","n_code_links":1,"syntology":null},{"paper":"/paper/ctgan-cloud-transformer-generative","slug":"ctgan-cloud-transformer-generative","title":"CTGAN : Cloud Transformer Generative Adversarial Network","date":"2022-10-18","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"from-play-to-policy-conditional-behavior","title":"From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data","date":"2022-10-18","arxiv_id":"2210.10047","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-image-fusion-based-on-hybrid-cnn","slug":"multimodal-image-fusion-based-on-hybrid-cnn","title":"Multimodal Image Fusion based on Hybrid CNN-Transformer and Non-local Cross-modal Attention","date":"2022-10-18","arxiv_id":"2210.09847","n_code_links":1,"syntology":null},{"paper":"/paper/swinv2-imagen-hierarchical-vision-transformer","slug":"swinv2-imagen-hierarchical-vision-transformer","title":"Swinv2-Imagen: Hierarchical Vision Transformer Diffusion Models for Text-to-Image Generation","date":"2022-10-18","arxiv_id":"2210.09549","n_code_links":0,"syntology":null},{"paper":null,"slug":"transfer-learning-for-video-classification","title":"Transfer-learning for video classification: Video Swin Transformer on multiple domains","date":"2022-10-18","arxiv_id":"2210.09969","n_code_links":0,"syntology":null},{"paper":"/paper/vitcod-vision-transformer-acceleration-via","slug":"vitcod-vision-transformer-acceleration-via","title":"ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design","date":"2022-10-18","arxiv_id":"2210.09573","n_code_links":1,"syntology":null},{"paper":"/paper/deep-bidirectional-language-knowledge-graph","slug":"deep-bidirectional-language-knowledge-graph","title":"Deep Bidirectional Language-Knowledge Graph Pretraining","date":"2022-10-17","arxiv_id":"2210.09338","n_code_links":2,"syntology":{"ran":9,"of":18,"n_ran_checked":8,"n_instrument":1,"unverified":9,"pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 9 unverified","official":{"repos":["michiyasunaga/dragon"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":9,"ran_from_kinds":["official"]}}},{"paper":"/paper/histopathological-image-classification-based","slug":"histopathological-image-classification-based","title":"Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak Labels","date":"2022-10-17","arxiv_id":"2210.09021","n_code_links":1,"syntology":null},{"paper":"/paper/intelligent-resource-allocation-in-joint","slug":"intelligent-resource-allocation-in-joint","title":"Intelligent Resource Allocation in Joint Radar-Communication With Graph Neural Networks","date":"2022-10-17","arxiv_id":null,"n_code_links":1,"syntology":null}],"record_sha256":"88238e5efad6c318abc00ba92a6c168d4f55a3734537ecd55f57252687e90594","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}