{"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/dense-connections/papers/203","list_of":"/method/dense-connections","method":"Dense Connections","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":203,"pages_in_order":293,"rows_per_page":100,"rows":[20201,20300],"of":29230,"counts":{"archive_papers_tagged":29230,"with_a_code_link":12972,"where_syntology_ran_a_sample":3929,"not_listed_spam_title":0,"listed":29230,"listed_where_code_ran":3929,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3303,"every_run_a_failure_of_syntologys_instrument":626,"listed_with_a_run_with_no_instrument_failure":3303,"listed_every_run_a_failure_of_syntologys_instrument":626,"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/dense-connections","prev":"/method/dense-connections/papers/202","next":"/method/dense-connections/papers/204","papers":[{"paper":null,"slug":"neural-architecture-search-for-inversion","title":"Neural Architecture Search for Inversion","date":"2022-01-05","arxiv_id":"2201.01772","n_code_links":0,"syntology":null},{"paper":"/paper/relationship-extraction-for-knowledge-graph","slug":"relationship-extraction-for-knowledge-graph","title":"Comparison of biomedical relationship extraction methods and models for knowledge graph creation","date":"2022-01-05","arxiv_id":"2201.01647","n_code_links":0,"syntology":null},{"paper":"/paper/a-transformer-based-siamese-network-for","slug":"a-transformer-based-siamese-network-for","title":"A Transformer-Based Siamese Network for Change Detection","date":"2022-01-04","arxiv_id":"2201.01293","n_code_links":3,"syntology":{"ran":4,"of":6,"n_ran_checked":2,"n_instrument":2,"unverified":2,"pointer_only":3,"phrase":"4 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; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["wgcban/changeformer"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"efficient-dyn-dynamic-graph-representation","title":"Sparse-Dyn: Sparse Dynamic Graph Multi-representation Learning via Event-based Sparse Temporal Attention Network","date":"2022-01-04","arxiv_id":"2201.01384","n_code_links":0,"syntology":null},{"paper":"/paper/pyramidtnt-improved-transformer-in","slug":"pyramidtnt-improved-transformer-in","title":"PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture","date":"2022-01-04","arxiv_id":"2201.00978","n_code_links":1,"syntology":null},{"paper":null,"slug":"short-range-correlation-transformer-for","title":"Short Range Correlation Transformer for Occluded Person Re-Identification","date":"2022-01-04","arxiv_id":"2201.01090","n_code_links":0,"syntology":null},{"paper":"/paper/sign-pose-based-transformer-for-word-level","slug":"sign-pose-based-transformer-for-word-level","title":"Sign Pose-Based Transformer for Word-Level Sign Language Recognition","date":"2022-01-04","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"stain-normalized-breast-histopathology-image","title":"Stain Normalized Breast Histopathology Image Recognition using Convolutional Neural Networks for Cancer Detection","date":"2022-01-04","arxiv_id":"2201.00957","n_code_links":0,"syntology":null},{"paper":null,"slug":"submix-practical-private-prediction-for-large-1","title":"Submix: Practical Private Prediction for Large-Scale Language Models","date":"2022-01-04","arxiv_id":"2201.00971","n_code_links":0,"syntology":null},{"paper":"/paper/swin-unetr-swin-transformers-for-semantic","slug":"swin-unetr-swin-transformers-for-semantic","title":"Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images","date":"2022-01-04","arxiv_id":"2201.01266","n_code_links":3,"syntology":null},{"paper":"/paper/an-adversarial-benchmark-for-fake-news","slug":"an-adversarial-benchmark-for-fake-news","title":"An Adversarial Benchmark for Fake News Detection Models","date":"2022-01-03","arxiv_id":"2201.00912","n_code_links":1,"syntology":null},{"paper":null,"slug":"asymptotic-convergence-of-deep-multi-agent","title":"3DPG: Distributed Deep Deterministic Policy Gradient Algorithms for Networked Multi-Agent Systems","date":"2022-01-03","arxiv_id":"2201.00570","n_code_links":0,"syntology":null},{"paper":null,"slug":"caft-clustering-and-filter-on-tokens-of","title":"CaFT: Clustering and Filter on Tokens of Transformer for Weakly Supervised Object Localization","date":"2022-01-03","arxiv_id":"2201.00475","n_code_links":0,"syntology":null},{"paper":"/paper/d-former-a-u-shaped-dilated-transformer-for","slug":"d-former-a-u-shaped-dilated-transformer-for","title":"D-Former: A U-shaped Dilated Transformer for 3D Medical Image Segmentation","date":"2022-01-03","arxiv_id":"2201.00462","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-feature-extraction-from","title":"Improving Feature Extraction from Histopathological Images Through A Fine-tuning ImageNet Model","date":"2022-01-03","arxiv_id":"2201.00636","n_code_links":0,"syntology":null},{"paper":"/paper/language-as-queries-for-referring-video","slug":"language-as-queries-for-referring-video","title":"Language as Queries for Referring Video Object Segmentation","date":"2022-01-03","arxiv_id":"2201.00487","n_code_links":1,"syntology":{"ran":7,"of":8,"n_ran_checked":5,"n_instrument":2,"unverified":1,"pointer_only":8,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["wjn922/referformer"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"tfcn-temporal-frequential-convolutional","title":"TFCN: Temporal-Frequential Convolutional Network for Single-Channel Speech Enhancement","date":"2022-01-03","arxiv_id":"2201.00480","n_code_links":0,"syntology":null},{"paper":"/paper/vision-transformer-slimming-multi-dimension","slug":"vision-transformer-slimming-multi-dimension","title":"Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space","date":"2022-01-03","arxiv_id":"2201.00814","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 1 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":["arnav0400/vit-slim"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/vision-transformer-with-deformable-attention","slug":"vision-transformer-with-deformable-attention","title":"Vision Transformer with Deformable Attention","date":"2022-01-03","arxiv_id":"2201.00520","n_code_links":2,"syntology":{"ran":8,"of":10,"n_ran_checked":4,"n_instrument":4,"unverified":2,"pointer_only":0,"phrase":"8 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 4 where Syntology's instrument failed) · 2 unverified","official":{"repos":["leaplabthu/dat"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"which-student-is-best-a-comprehensive","title":"Which Student is Best? A Comprehensive Knowledge Distillation Exam for Task-Specific BERT Models","date":"2022-01-03","arxiv_id":"2201.00558","n_code_links":0,"syntology":null},{"paper":"/paper/detail-preserving-transformer-for-light-field","slug":"detail-preserving-transformer-for-light-field","title":"Detail-Preserving Transformer for Light Field Image Super-Resolution","date":"2022-01-02","arxiv_id":"2201.00346","n_code_links":1,"syntology":{"ran":10,"of":21,"n_ran_checked":6,"n_instrument":4,"unverified":11,"pointer_only":21,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 4 where Syntology's instrument failed) · 11 unverified","official":{"repos":["bitszwang/dpt"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":11,"ran_from_kinds":["official"]}}},{"paper":"/paper/informed-multi-context-entity-alignment","slug":"informed-multi-context-entity-alignment","title":"Informed Multi-context Entity Alignment","date":"2022-01-02","arxiv_id":"2201.00304","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-sensitivity-of-deep-learning-based-text","title":"On Sensitivity of Deep Learning Based Text Classification Algorithms to Practical Input Perturbations","date":"2022-01-02","arxiv_id":"2201.00318","n_code_links":0,"syntology":null},{"paper":"/paper/splicing-vit-features-for-semantic-appearance","slug":"splicing-vit-features-for-semantic-appearance","title":"Splicing ViT Features for Semantic Appearance Transfer","date":"2022-01-02","arxiv_id":"2201.00424","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":["omerbt/Splice"],"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":"/paper/a-brand-new-dance-partner-music-conditioned","slug":"a-brand-new-dance-partner-music-conditioned","title":"A Brand New Dance Partner: Music-Conditioned Pluralistic Dancing Controlled by Multiple Dance Genres","date":"2022-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"a-graph-matching-perspective-with","title":"A Graph Matching Perspective With Transformers on Video Instance Segmentation","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/cadtransformer-panoptic-symbol-spotting","slug":"cadtransformer-panoptic-symbol-spotting","title":"CADTransformer: Panoptic Symbol Spotting Transformer for CAD Drawings","date":"2022-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/chitransformer-towards-reliable-stereo-from-1","slug":"chitransformer-towards-reliable-stereo-from-1","title":"Chitransformer: Towards Reliable Stereo From Cues","date":"2022-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"continual-learning-with-lifelong-vision","title":"Continual Learning With Lifelong Vision Transformer","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/continual-stereo-matching-of-continuous","slug":"continual-stereo-matching-of-continuous","title":"Continual Stereo Matching of Continuous Driving Scenes With Growing Architecture","date":"2022-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"destr-object-detection-with-split-transformer","title":"DESTR: Object Detection With Split Transformer","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"dlformer-discrete-latent-transformer-for","title":"DLFormer: Discrete Latent Transformer for Video Inpainting","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"dynamic-scene-graph-generation-via","title":"Dynamic Scene Graph Generation via Anticipatory Pre-Training","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"expanding-large-pre-trained-unimodal-models","title":"Expanding Large Pre-Trained Unimodal Models With Multimodal Information Injection for Image-Text Multimodal Classification","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/hairmapper-removing-hair-from-portraits-using","slug":"hairmapper-removing-hair-from-portraits-using","title":"HairMapper: Removing Hair From Portraits Using GANs","date":"2022-01-01","arxiv_id":null,"n_code_links":2,"syntology":null},{"paper":"/paper/image-dehazing-transformer-with-transmission","slug":"image-dehazing-transformer-with-transmission","title":"Image Dehazing Transformer With Transmission-Aware 3D Position Embedding","date":"2022-01-01","arxiv_id":null,"n_code_links":2,"syntology":null},{"paper":null,"slug":"instance-segmentation-with-mask-supervised","title":"Instance Segmentation With Mask-Supervised Polygonal Boundary Transformers","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"knn-local-attention-for-image-restoration","title":"KNN Local Attention for Image Restoration","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/learning-transferable-human-object","slug":"learning-transferable-human-object","title":"Learning Transferable Human-Object Interaction Detector With Natural Language Supervision","date":"2022-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"lift-learning-4d-lidar-image-fusion","title":"LIFT: Learning 4D LiDAR Image Fusion Transformer for 3D Object Detection","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/likert-scoring-with-grade-decoupling-for-long","slug":"likert-scoring-with-grade-decoupling-for-long","title":"Likert Scoring With Grade Decoupling for Long-Term Action Assessment","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"ltp-lane-based-trajectory-prediction-for","title":"LTP: Lane-Based Trajectory Prediction for Autonomous Driving","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/m3t-three-dimensional-medical-image","slug":"m3t-three-dimensional-medical-image","title":"M3T: Three-Dimensional Medical Image Classifier Using Multi-Plane and Multi-Slice Transformer","date":"2022-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"mr-biq-post-training-non-uniform-quantization","title":"Mr.BiQ: Post-Training Non-Uniform Quantization Based on Minimizing the Reconstruction Error","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/multi-modal-dynamic-graph-transformer-for","slug":"multi-modal-dynamic-graph-transformer-for","title":"Multi-Modal Dynamic Graph Transformer for Visual Grounding","date":"2022-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"neural-window-fully-connected-crfs-for","title":"Neural Window Fully-Connected CRFs for Monocular Depth Estimation","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"patchtrack-multiple-object-tracking-using","title":"PatchTrack: Multiple Object Tracking Using Frame Patches","date":"2022-01-01","arxiv_id":"2201.00080","n_code_links":0,"syntology":null},{"paper":null,"slug":"recurring-the-transformer-for-video-action","title":"Recurring the Transformer for Video Action Recognition","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"smooth-maximum-unit-smooth-activation","title":"Smooth Maximum Unit: Smooth Activation Function for Deep Networks Using Smoothing Maximum Technique","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"spaceedit-learning-a-unified-editing-space-1","title":"SpaceEdit: Learning a Unified Editing Space for Open-Domain Image Color Editing","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"tencent-mvse-a-large-scale-benchmark-dataset","title":"Tencent-MVSE: A Large-Scale Benchmark Dataset for Multi-Modal Video Similarity Evaluation","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/the-gatedtabtransformer-an-enhanced-deep","slug":"the-gatedtabtransformer-an-enhanced-deep","title":"The GatedTabTransformer. An enhanced deep learning architecture for tabular modeling","date":"2022-01-01","arxiv_id":"2201.00199","n_code_links":2,"syntology":null},{"paper":null,"slug":"think-twice-before-detecting-gan-generated","title":"Think Twice Before Detecting GAN-Generated Fake Images From Their Spectral Domain Imprints","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"toward-pareto-efficient-fairness-utility","title":"Toward Pareto Efficient Fairness-Utility Trade-off inRecommendation through Reinforcement Learning","date":"2022-01-01","arxiv_id":"2201.00140","n_code_links":0,"syntology":null},{"paper":null,"slug":"training-object-detectors-from-scratch-an","title":"Training Object Detectors From Scratch: An Empirical Study in the Era of Vision Transformer","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"transformer-based-line-segment-classifier","title":"Transformer Based Line Segment Classifier With Image Context for Real-Time Vanishing Point Detection in Manhattan World","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"uncertainty-guided-probabilistic-transformer","title":"Uncertainty-Guided Probabilistic Transformer for Complex Action Recognition","date":"2022-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/a-neural-network-solves-and-generates","slug":"a-neural-network-solves-and-generates","title":"A Neural Network Solves, Explains, and Generates University Math Problems by Program Synthesis and Few-Shot Learning at Human Level","date":"2021-12-31","arxiv_id":"2112.15594","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":4,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["idrori/mathq"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"actor-loss-of-soft-actor-critic-explained","title":"Actor Loss of Soft Actor Critic Explained","date":"2021-12-31","arxiv_id":"2112.15568","n_code_links":0,"syntology":null},{"paper":"/paper/clustering-vietnamese-conversations-from","slug":"clustering-vietnamese-conversations-from","title":"Clustering Vietnamese Conversations From Facebook Page To Build Training Dataset For Chatbot","date":"2021-12-31","arxiv_id":"2112.15338","n_code_links":1,"syntology":null},{"paper":"/paper/csformer-bridging-convolution-and-transformer","slug":"csformer-bridging-convolution-and-transformer","title":"CSformer: Bridging Convolution and Transformer for Compressive Sensing","date":"2021-12-31","arxiv_id":"2112.15299","n_code_links":1,"syntology":null},{"paper":"/paper/efficient-single-image-super-resolution-using-1","slug":"efficient-single-image-super-resolution-using-1","title":"Efficient Single Image Super-Resolution Using Dual Path Connections with Multiple Scale Learning","date":"2021-12-31","arxiv_id":"2112.15386","n_code_links":1,"syntology":null},{"paper":null,"slug":"evaluating-deep-music-generation-methods","title":"Evaluating Deep Music Generation Methods Using Data Augmentation","date":"2021-12-31","arxiv_id":"2201.00052","n_code_links":0,"syntology":null},{"paper":"/paper/multi-dimensional-model-compression-of-vision","slug":"multi-dimensional-model-compression-of-vision","title":"Multi-Dimensional Model Compression of Vision Transformer","date":"2021-12-31","arxiv_id":"2201.00043","n_code_links":1,"syntology":null},{"paper":null,"slug":"openqa-hybrid-qa-system-relying-on-structured","title":"OpenQA: Hybrid QA System Relying on Structured Knowledge Base as well as Non-structured Data","date":"2021-12-31","arxiv_id":"2112.15356","n_code_links":0,"syntology":null},{"paper":null,"slug":"scene-adaptive-attention-network-for-crowd","title":"Scene-Adaptive Attention Network for Crowd Counting","date":"2021-12-31","arxiv_id":"2112.15509","n_code_links":0,"syntology":null},{"paper":null,"slug":"splitbrain-hybrid-data-and-model-parallel","title":"SplitBrain: Hybrid Data and Model Parallel Deep Learning","date":"2021-12-31","arxiv_id":"2112.15317","n_code_links":0,"syntology":null},{"paper":"/paper/transformer-embeddings-of-irregularly-spaced-1","slug":"transformer-embeddings-of-irregularly-spaced-1","title":"Transformer Embeddings of Irregularly Spaced Events and Their Participants","date":"2021-12-31","arxiv_id":"2201.00044","n_code_links":2,"syntology":null},{"paper":"/paper/vinmt-neural-machine-translation-tookit","slug":"vinmt-neural-machine-translation-tookit","title":"ViNMT: Neural Machine Translation Toolkit","date":"2021-12-31","arxiv_id":"2112.15272","n_code_links":1,"syntology":null},{"paper":"/paper/a-lightweight-and-accurate-spatial-temporal","slug":"a-lightweight-and-accurate-spatial-temporal","title":"A Lightweight and Accurate Spatial-Temporal Transformer for Traffic Forecasting","date":"2021-12-30","arxiv_id":"2201.00008","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-resolution-enhancement-plug-in-for","title":"A Resolution Enhancement Plug-in for Deformable Registration of Medical Images","date":"2021-12-30","arxiv_id":"2112.15180","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-mixed-precision-quantization-search","title":"Automatic Mixed-Precision Quantization Search of BERT","date":"2021-12-30","arxiv_id":"2112.14938","n_code_links":0,"syntology":null},{"paper":null,"slug":"chunkformer-learning-long-time-series-with","title":"ChunkFormer: Learning Long Time Series with Multi-stage Chunked Transformer","date":"2021-12-30","arxiv_id":"2112.15087","n_code_links":0,"syntology":null},{"paper":"/paper/constraint-sampling-reinforcement-learning","slug":"constraint-sampling-reinforcement-learning","title":"Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning","date":"2021-12-30","arxiv_id":"2112.15221","n_code_links":1,"syntology":null},{"paper":"/paper/contrastive-fine-grained-class-clustering-via-1","slug":"contrastive-fine-grained-class-clustering-via-1","title":"Contrastive Fine-grained Class Clustering via Generative Adversarial Networks","date":"2021-12-30","arxiv_id":"2112.14971","n_code_links":1,"syntology":{"ran":0,"of":3,"n_ran_checked":0,"n_instrument":0,"unverified":3,"pointer_only":3,"phrase":"0 ran · 3 unverified","official":{"repos":["naver-ai/c3-gan"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":[]}}},{"paper":"/paper/persformer-a-transformer-architecture-for","slug":"persformer-a-transformer-architecture-for","title":"Persformer: A Transformer Architecture for Topological Machine Learning","date":"2021-12-30","arxiv_id":"2112.15210","n_code_links":1,"syntology":null},{"paper":"/paper/the-benchmark-transferable-representation","slug":"the-benchmark-transferable-representation","title":"THE Benchmark: Transferable Representation Learning for Monocular Height Estimation","date":"2021-12-30","arxiv_id":"2112.14985","n_code_links":0,"syntology":null},{"paper":"/paper/dense-to-sparse-gate-for-mixture-of-experts-1","slug":"dense-to-sparse-gate-for-mixture-of-experts-1","title":"EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate","date":"2021-12-29","arxiv_id":"2112.14397","n_code_links":2,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"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) · 0 unverified","official":{"repos":["codecaution/evomoe"],"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"]}}},{"paper":"/paper/learning-inception-attention-for-image","slug":"learning-inception-attention-for-image","title":"Learning Spatially-Adaptive Squeeze-Excitation Networks for Image Synthesis and Image Recognition","date":"2021-12-29","arxiv_id":"2112.14804","n_code_links":1,"syntology":null},{"paper":null,"slug":"temporal-attention-augmented-transformer","title":"Temporal Attention Augmented Transformer Hawkes Process","date":"2021-12-29","arxiv_id":"2112.14472","n_code_links":0,"syntology":null},{"paper":"/paper/april-finding-the-achilles-heel-on-privacy","slug":"april-finding-the-achilles-heel-on-privacy","title":"APRIL: Finding the Achilles' Heel on Privacy for Vision Transformers","date":"2021-12-28","arxiv_id":"2112.14087","n_code_links":1,"syntology":null},{"paper":null,"slug":"extended-self-critical-pipeline-for","title":"Extended Self-Critical Pipeline for Transforming Videos to Text (TRECVID-VTT Task 2021) -- Team: MMCUniAugsburg","date":"2021-12-28","arxiv_id":"2112.14100","n_code_links":0,"syntology":null},{"paper":"/paper/pale-transformer-a-general-vision-transformer","slug":"pale-transformer-a-general-vision-transformer","title":"Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped Attention","date":"2021-12-28","arxiv_id":"2112.14000","n_code_links":2,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["BR-IDL/PaddleViT"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"synchronized-audio-visual-frames-with","title":"Synchronized Audio-Visual Frames with Fractional Positional Encoding for Transformers in Video-to-Text Translation","date":"2021-12-28","arxiv_id":"2112.14088","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-university-of-texas-at-dallas-hltri-s","title":"The University of Texas at Dallas HLTRI's Participation in EPIC-QA: Searching for Entailed Questions Revealing Novel Answer Nuggets","date":"2021-12-28","arxiv_id":"2112.13946","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-graph-attention-learning-approach-to","title":"A Graph Attention Learning Approach to Antenna Tilt Optimization","date":"2021-12-27","arxiv_id":"2112.14843","n_code_links":0,"syntology":null},{"paper":"/paper/a-passage-to-india-pre-trained-word-1","slug":"a-passage-to-india-pre-trained-word-1","title":"\"A Passage to India\": Pre-trained Word Embeddings for Indian Languages","date":"2021-12-27","arxiv_id":"2112.13800","n_code_links":0,"syntology":null},{"paper":null,"slug":"classification-of-histopathology-images-of","title":"Classification of Histopathology Images of Lung Cancer Using Convolutional Neural Network (CNN)","date":"2021-12-27","arxiv_id":"2112.13553","n_code_links":0,"syntology":null},{"paper":null,"slug":"contextual-sentence-analysis-for-the","title":"Contextual Sentence Analysis for the Sentiment Prediction on Financial Data","date":"2021-12-27","arxiv_id":"2112.13790","n_code_links":0,"syntology":null},{"paper":null,"slug":"estimating-parameters-of-the-tree-root-in","title":"Estimating Parameters of the Tree Root in Heterogeneous Soil Environments via Mask-Guided Multi-Polarimetric Integration Neural Network","date":"2021-12-27","arxiv_id":"2112.13494","n_code_links":0,"syntology":null},{"paper":"/paper/event-based-clinical-findings-extraction-from","slug":"event-based-clinical-findings-extraction-from","title":"Event-based clinical findings extraction from radiology reports with pre-trained language model","date":"2021-12-27","arxiv_id":"2112.13512","n_code_links":1,"syntology":null},{"paper":"/paper/heteroqa-learning-towards-question-and","slug":"heteroqa-learning-towards-question-and","title":"HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling","date":"2021-12-27","arxiv_id":"2112.13597","n_code_links":1,"syntology":null},{"paper":"/paper/intelligent-traffic-light-via-policy-based","slug":"intelligent-traffic-light-via-policy-based","title":"Intelligent Traffic Light via Policy-based Deep Reinforcement Learning","date":"2021-12-27","arxiv_id":"2112.13817","n_code_links":1,"syntology":null},{"paper":"/paper/learning-generative-vision-transformer-with-1","slug":"learning-generative-vision-transformer-with-1","title":"Learning Generative Vision Transformer with Energy-Based Latent Space for Saliency Prediction","date":"2021-12-27","arxiv_id":"2112.13528","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-robust-and-lightweight-model-through","title":"Learning Robust and Lightweight Model through Separable Structured Transformations","date":"2021-12-27","arxiv_id":"2112.13551","n_code_links":0,"syntology":null},{"paper":null,"slug":"mind-the-gap-cross-lingual-information","title":"Mind the Gap: Cross-Lingual Information Retrieval with Hierarchical Knowledge Enhancement","date":"2021-12-27","arxiv_id":"2112.13510","n_code_links":0,"syntology":null},{"paper":"/paper/msht-multi-stage-hybrid-transformer-for-the","slug":"msht-multi-stage-hybrid-transformer-for-the","title":"MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer","date":"2021-12-27","arxiv_id":"2112.13513","n_code_links":1,"syntology":null},{"paper":"/paper/multi-image-visual-question-answering","slug":"multi-image-visual-question-answering","title":"Multi-Image Visual Question Answering","date":"2021-12-27","arxiv_id":"2112.13706","n_code_links":1,"syntology":null},{"paper":null,"slug":"secondary-use-of-clinical-problem-list","title":"Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment","date":"2021-12-27","arxiv_id":"2112.13756","n_code_links":0,"syntology":null},{"paper":"/paper/spvit-enabling-faster-vision-transformers-via","slug":"spvit-enabling-faster-vision-transformers-via","title":"SPViT: Enabling Faster Vision Transformers via Soft Token Pruning","date":"2021-12-27","arxiv_id":"2112.13890","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":0,"n_instrument":3,"unverified":0,"pointer_only":3,"phrase":"3 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; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["peiyanflying/spvit"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}}],"record_sha256":"4cef64828514afd279f814cc647f62e61b3be1167e06ffae5154ed2168c611b5","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}