{"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/multi-head-attention/papers/153","list_of":"/method/multi-head-attention","method":"Multi-Head Attention","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":153,"pages_in_order":249,"rows_per_page":100,"rows":[15201,15300],"of":24855,"counts":{"archive_papers_tagged":24855,"with_a_code_link":11214,"where_syntology_ran_a_sample":3454,"not_listed_spam_title":0,"listed":24855,"listed_where_code_ran":3454,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":2916,"every_run_a_failure_of_syntologys_instrument":538,"listed_with_a_run_with_no_instrument_failure":2916,"listed_every_run_a_failure_of_syntologys_instrument":538,"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/multi-head-attention","prev":"/method/multi-head-attention/papers/152","next":"/method/multi-head-attention/papers/154","papers":[{"paper":"/paper/semantic-conditional-diffusion-networks-for","slug":"semantic-conditional-diffusion-networks-for","title":"Semantic-Conditional Diffusion Networks for Image Captioning","date":"2022-12-06","arxiv_id":"2212.03099","n_code_links":2,"syntology":null},{"paper":"/paper/simple-baseline-for-weather-forecasting-using","slug":"simple-baseline-for-weather-forecasting-using","title":"Simple Baseline for Weather Forecasting Using Spatiotemporal Context Aggregation Network","date":"2022-12-06","arxiv_id":"2212.02952","n_code_links":1,"syntology":{"ran":5,"of":10,"n_ran_checked":5,"n_instrument":0,"unverified":5,"pointer_only":10,"phrase":"5 ran (of which 4 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 5 unverified","official":{"repos":["seominseok0429/w4c22-simple-baseline-for-weather-forecasting-using-spatiotemporal-context-aggregation-network"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":5,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"style-transfer-and-classification-in-hebrew","title":"Style transfer and classification in hebrew news items","date":"2022-12-06","arxiv_id":"2212.03019","n_code_links":0,"syntology":null},{"paper":"/paper/unigeo-unifying-geometry-logical-reasoning","slug":"unigeo-unifying-geometry-logical-reasoning","title":"UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression","date":"2022-12-06","arxiv_id":"2212.02746","n_code_links":2,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":4,"phrase":"2 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; 0 where Syntology's instrument failed) · 2 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["chen-judge/unigeo"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"video-object-of-interest-segmentation","title":"Video Object of Interest Segmentation","date":"2022-12-06","arxiv_id":"2212.02871","n_code_links":0,"syntology":null},{"paper":null,"slug":"3d-latentmapper-view-agnostic-single-view","title":"3D-LatentMapper: View Agnostic Single-View Reconstruction of 3D Shapes","date":"2022-12-05","arxiv_id":"2212.02184","n_code_links":0,"syntology":null},{"paper":null,"slug":"audio-driven-co-speech-gesture-video","title":"Audio-Driven Co-Speech Gesture Video Generation","date":"2022-12-05","arxiv_id":"2212.02350","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-generation-of-factual-news","title":"Automatic Generation of Factual News Headlines in Finnish","date":"2022-12-05","arxiv_id":"2212.02170","n_code_links":0,"syntology":null},{"paper":null,"slug":"inspired-by-norbert-wiener-feedback-loop","title":"FBLNet: FeedBack Loop Network for Driver Attention Prediction","date":"2022-12-05","arxiv_id":"2212.02096","n_code_links":0,"syntology":null},{"paper":"/paper/mask-matching-transformer-for-few-shot","slug":"mask-matching-transformer-for-few-shot","title":"Mask Matching Transformer for Few-Shot Segmentation","date":"2022-12-05","arxiv_id":"2301.01208","n_code_links":1,"syntology":null},{"paper":"/paper/retrieval-as-attention-end-to-end-learning-of","slug":"retrieval-as-attention-end-to-end-learning-of","title":"Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer","date":"2022-12-05","arxiv_id":"2212.02027","n_code_links":1,"syntology":null},{"paper":"/paper/unifying-vision-text-and-layout-for-universal","slug":"unifying-vision-text-and-layout-for-universal","title":"Unifying Vision, Text, and Layout for Universal Document Processing","date":"2022-12-05","arxiv_id":"2212.02623","n_code_links":5,"syntology":{"ran":15,"of":17,"n_ran_checked":14,"n_instrument":1,"unverified":2,"pointer_only":4,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 14 with no instrument failure: 0 honoured, 2 violated, 12 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["microsoft/i-code","microsoft/udop"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","unlocated"]}}},{"paper":"/paper/video-games-as-a-corpus-sentiment-analysis","slug":"video-games-as-a-corpus-sentiment-analysis","title":"Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog","date":"2022-12-05","arxiv_id":"2212.02168","n_code_links":0,"syntology":null},{"paper":null,"slug":"joint-self-supervised-image-volume","title":"Joint Self-Supervised Image-Volume Representation Learning with Intra-Inter Contrastive Clustering","date":"2022-12-04","arxiv_id":"2212.01893","n_code_links":0,"syntology":null},{"paper":null,"slug":"languages-you-know-influence-those-you-learn","title":"Languages You Know Influence Those You Learn: Impact of Language Characteristics on Multi-Lingual Text-to-Text Transfer","date":"2022-12-04","arxiv_id":"2212.01757","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-stochastic-autoregressive-image","slug":"exploring-stochastic-autoregressive-image","title":"Exploring Stochastic Autoregressive Image Modeling for Visual Representation","date":"2022-12-03","arxiv_id":"2212.01610","n_code_links":1,"syntology":null},{"paper":null,"slug":"exploring-the-limits-of-differentially","title":"Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping","date":"2022-12-03","arxiv_id":"2212.01539","n_code_links":0,"syntology":null},{"paper":null,"slug":"global-memory-transformer-for-processing-long","title":"Global memory transformer for processing long documents","date":"2022-12-03","arxiv_id":"2212.01650","n_code_links":0,"syntology":null},{"paper":null,"slug":"recognition-and-prediction-of-surgical","title":"Recognition and Prediction of Surgical Gestures and Trajectories Using Transformer Models in Robot-Assisted Surgery","date":"2022-12-03","arxiv_id":"2212.01683","n_code_links":0,"syntology":null},{"paper":null,"slug":"cold-fusion-collaborative-descent-for","title":"ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning","date":"2022-12-02","arxiv_id":"2212.01378","n_code_links":0,"syntology":null},{"paper":"/paper/event-knowledge-in-large-language-models-the","slug":"event-knowledge-in-large-language-models-the","title":"Event knowledge in large language models: the gap between the impossible and the unlikely","date":"2022-12-02","arxiv_id":"2212.01488","n_code_links":1,"syntology":null},{"paper":"/paper/fecam-frequency-enhanced-channel-attention","slug":"fecam-frequency-enhanced-channel-attention","title":"FECAM: Frequency Enhanced Channel Attention Mechanism for Time Series Forecasting","date":"2022-12-02","arxiv_id":"2212.01209","n_code_links":1,"syntology":null},{"paper":"/paper/relation-aware-language-graph-transformer-for","slug":"relation-aware-language-graph-transformer-for","title":"Relation-Aware Language-Graph Transformer for Question Answering","date":"2022-12-02","arxiv_id":"2212.00975","n_code_links":1,"syntology":null},{"paper":"/paper/slmt-net-a-self-supervised-learning-based","slug":"slmt-net-a-self-supervised-learning-based","title":"Multi-scale Transformer Network with Edge-aware Pre-training for Cross-Modality MR Image Synthesis","date":"2022-12-02","arxiv_id":"2212.01108","n_code_links":2,"syntology":null},{"paper":"/paper/sumren-summarizing-reported-speech-about","slug":"sumren-summarizing-reported-speech-about","title":"SumREN: Summarizing Reported Speech about Events in News","date":"2022-12-02","arxiv_id":"2212.01146","n_code_links":1,"syntology":null},{"paper":"/paper/tackling-low-resourced-sign-language","slug":"tackling-low-resourced-sign-language","title":"Tackling Low-Resourced Sign Language Translation: UPC at WMT-SLT 22","date":"2022-12-02","arxiv_id":"2212.01140","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-diverse-relevant-and-coherent-open","title":"Towards Diverse, Relevant and Coherent Open-Domain Dialogue Generation via Hybrid Latent Variables","date":"2022-12-02","arxiv_id":"2212.01145","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-survey-on-gpt-3","title":"a survey on GPT-3","date":"2022-12-01","arxiv_id":"2212.00857","n_code_links":0,"syntology":null},{"paper":null,"slug":"adapted-multimodal-bert-with-layer-wise","title":"Adapted Multimodal BERT with Layer-wise Fusion for Sentiment Analysis","date":"2022-12-01","arxiv_id":"2212.00678","n_code_links":0,"syntology":null},{"paper":null,"slug":"chapter-exploiting-convolutional-neural","title":"CHAPTER: Exploiting Convolutional Neural Network Adapters for Self-supervised Speech Models","date":"2022-12-01","arxiv_id":"2212.01282","n_code_links":0,"syntology":null},{"paper":null,"slug":"concealed-object-detection-for-passive","title":"Concealed Object Detection for Passive Millimeter-Wave Security Imaging Based on Task-Aligned Detection Transformer","date":"2022-12-01","arxiv_id":"2212.00313","n_code_links":0,"syntology":null},{"paper":null,"slug":"cuni-non-autoregressive-system-for-the-wmt-22","title":"CUNI Non-Autoregressive System for the WMT 22 Efficient Translation Shared Task","date":"2022-12-01","arxiv_id":"2212.00477","n_code_links":0,"syntology":null},{"paper":"/paper/data-efficient-finetuning-using-cross-task","slug":"data-efficient-finetuning-using-cross-task","title":"Data-Efficient Finetuning Using Cross-Task Nearest Neighbors","date":"2022-12-01","arxiv_id":"2212.00196","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":["allenai/data-efficient-finetuning"],"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/distilling-multi-step-reasoning-capabilities","slug":"distilling-multi-step-reasoning-capabilities","title":"Distilling Reasoning Capabilities into Smaller Language Models","date":"2022-12-01","arxiv_id":"2212.00193","n_code_links":1,"syntology":null},{"paper":"/paper/explainable-artificial-intelligence-for-8","slug":"explainable-artificial-intelligence-for-8","title":"Explainable Artificial Intelligence for Improved Modeling of Processes","date":"2022-12-01","arxiv_id":"2212.00695","n_code_links":1,"syntology":null},{"paper":"/paper/ghost-free-high-dynamic-range-imaging-via","slug":"ghost-free-high-dynamic-range-imaging-via","title":"Ghost-free High Dynamic Range Imaging via Hybrid CNN-Transformer and Structure Tensor","date":"2022-12-01","arxiv_id":"2212.00595","n_code_links":1,"syntology":null},{"paper":"/paper/learning-progressive-modality-shared","slug":"learning-progressive-modality-shared","title":"Learning Progressive Modality-shared Transformers for Effective Visible-Infrared Person Re-identification","date":"2022-12-01","arxiv_id":"2212.00226","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-novel-framework-for-decentralized-dynamic","title":"A Novel Framework for Decentralized Dynamic Resource Allocation Using Voronoi Tessellations","date":"2022-11-30","arxiv_id":"2212.00140","n_code_links":0,"syntology":null},{"paper":null,"slug":"budgetlongformer-can-we-cheaply-pretrain-a","title":"BudgetLongformer: Can we Cheaply Pretrain a SotA Legal Language Model From Scratch?","date":"2022-11-30","arxiv_id":"2211.17135","n_code_links":0,"syntology":null},{"paper":null,"slug":"dsnet-a-simple-yet-efficient-network-with","title":"DSNet: a simple yet efficient network with dual-stream attention for lesion segmentation","date":"2022-11-30","arxiv_id":"2211.16950","n_code_links":0,"syntology":null},{"paper":"/paper/extremebert-a-toolkit-for-accelerating","slug":"extremebert-a-toolkit-for-accelerating","title":"ExtremeBERT: A Toolkit for Accelerating Pretraining of Customized BERT","date":"2022-11-30","arxiv_id":"2211.17201","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["extreme-bert/extreme-bert"],"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":null,"slug":"heat-hardware-efficient-automatic-tensor","title":"HEAT: Hardware-Efficient Automatic Tensor Decomposition for Transformer Compression","date":"2022-11-30","arxiv_id":"2211.16749","n_code_links":0,"syntology":null},{"paper":"/paper/part-based-face-recognition-with-vision","slug":"part-based-face-recognition-with-vision","title":"Part-based Face Recognition with Vision Transformers","date":"2022-11-30","arxiv_id":"2212.00057","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"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) · 0 unverified","official":{"repos":["szlbiubiubiu/Part_fViT"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/pattern-attention-transformer-with-doughnut","slug":"pattern-attention-transformer-with-doughnut","title":"Pattern Attention Transformer with Doughnut Kernel","date":"2022-11-30","arxiv_id":"2211.16961","n_code_links":0,"syntology":null},{"paper":null,"slug":"quadapter-adapter-for-gpt-2-quantization","title":"Quadapter: Adapter for GPT-2 Quantization","date":"2022-11-30","arxiv_id":"2211.16912","n_code_links":0,"syntology":null},{"paper":null,"slug":"rephrasing-the-reference-for-non","title":"Rephrasing the Reference for Non-Autoregressive Machine Translation","date":"2022-11-30","arxiv_id":"2211.16863","n_code_links":0,"syntology":null},{"paper":"/paper/t2g-former-organizing-tabular-features-into","slug":"t2g-former-organizing-tabular-features-into","title":"T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interaction","date":"2022-11-30","arxiv_id":"2211.16887","n_code_links":1,"syntology":{"ran":13,"of":13,"n_ran_checked":10,"n_instrument":3,"unverified":0,"pointer_only":1,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 1 violated, 9 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["jyansir/t2g-former"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"task-specific-embeddings-for-ante-hoc","title":"Task-Specific Embeddings for Ante-Hoc Explainable Text Classification","date":"2022-11-30","arxiv_id":"2212.00086","n_code_links":0,"syntology":null},{"paper":null,"slug":"topological-data-analysis-for-speech","title":"Topological Data Analysis for Speech Processing","date":"2022-11-30","arxiv_id":"2211.17223","n_code_links":0,"syntology":null},{"paper":"/paper/airformer-predicting-nationwide-air-quality","slug":"airformer-predicting-nationwide-air-quality","title":"AirFormer: Predicting Nationwide Air Quality in China with Transformers","date":"2022-11-29","arxiv_id":"2211.15979","n_code_links":1,"syntology":null},{"paper":"/paper/attribute-de-biased-vision-transformer-ad-vit","slug":"attribute-de-biased-vision-transformer-ad-vit","title":"Attribute De-biased Vision Transformer (AD-ViT) for Long-Term Person Re-identification","date":"2022-11-29","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/bartsmiles-generative-masked-language-models","slug":"bartsmiles-generative-masked-language-models","title":"BARTSmiles: Generative Masked Language Models for Molecular Representations","date":"2022-11-29","arxiv_id":"2211.16349","n_code_links":1,"syntology":{"ran":6,"of":6,"n_ran_checked":6,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"6 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; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yerevann/bartsmiles"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/composition-based-oxidation-state-prediction","slug":"composition-based-oxidation-state-prediction","title":"Composition based oxidation state prediction of materials using deep learning","date":"2022-11-29","arxiv_id":"2211.15895","n_code_links":1,"syntology":null},{"paper":null,"slug":"diverse-multi-answer-retrieval-with-1","title":"Diverse Multi-Answer Retrieval with Determinantal Point Processes","date":"2022-11-29","arxiv_id":"2211.16029","n_code_links":0,"syntology":null},{"paper":"/paper/hierarchical-transformer-for-survival","slug":"hierarchical-transformer-for-survival","title":"Hierarchical Transformer for Survival Prediction Using Multimodality Whole Slide Images and Genomics","date":"2022-11-29","arxiv_id":"2211.16632","n_code_links":1,"syntology":null},{"paper":null,"slug":"metal-conscious-embedding-for-cbct-projection","title":"Metal-conscious Embedding for CBCT Projection Inpainting","date":"2022-11-29","arxiv_id":"2211.16219","n_code_links":0,"syntology":null},{"paper":"/paper/noisyquant-noisy-bias-enhanced-post-training","slug":"noisyquant-noisy-bias-enhanced-post-training","title":"NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers","date":"2022-11-29","arxiv_id":"2211.16056","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["kriskrisliu/NoisyQuant"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"outfit-generation-and-recommendation-an","title":"Outfit Generation and Recommendation -- An Experimental Study","date":"2022-11-29","arxiv_id":"2211.16353","n_code_links":0,"syntology":null},{"paper":"/paper/phrasetransformer-an-incorporation-of-local","slug":"phrasetransformer-an-incorporation-of-local","title":"PhraseTransformer: An Incorporation of Local Context Information into Sequence-to-sequence Semantic Parsing","date":"2022-11-29","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/spartan-sparse-hierarchical-memory-for","slug":"spartan-sparse-hierarchical-memory-for","title":"SPARTAN: Sparse Hierarchical Memory for Parameter-Efficient Transformers","date":"2022-11-29","arxiv_id":"2211.16634","n_code_links":1,"syntology":null},{"paper":"/paper/transformer-based-hand-gesture-recognition","slug":"transformer-based-hand-gesture-recognition","title":"Transformer-based Hand Gesture Recognition via High-Density EMG Signals: From Instantaneous Recognition to Fusion of Motor Unit Spike Trains","date":"2022-11-29","arxiv_id":"2212.00743","n_code_links":1,"syntology":null},{"paper":"/paper/zero-shot-opinion-summarization-with-gpt-3","slug":"zero-shot-opinion-summarization-with-gpt-3","title":"Prompted Opinion Summarization with GPT-3.5","date":"2022-11-29","arxiv_id":"2211.15914","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-light-touch-approach-to-teaching","title":"A Light Touch Approach to Teaching Transformers Multi-view Geometry","date":"2022-11-28","arxiv_id":"2211.15107","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatically-extracting-information-in","title":"Automatically Extracting Information in Medical Dialogue: Expert System And Attention for Labelling","date":"2022-11-28","arxiv_id":"2211.15544","n_code_links":0,"syntology":null},{"paper":null,"slug":"bjtu-wechat-s-systems-for-the-wmt22-chat","title":"BJTU-WeChat's Systems for the WMT22 Chat Translation Task","date":"2022-11-28","arxiv_id":"2211.15009","n_code_links":0,"syntology":null},{"paper":"/paper/connecting-the-dots-floorplan-reconstruction","slug":"connecting-the-dots-floorplan-reconstruction","title":"Connecting the Dots: Floorplan Reconstruction Using Two-Level Queries","date":"2022-11-28","arxiv_id":"2211.15658","n_code_links":1,"syntology":null},{"paper":"/paper/diffusionbert-improving-generative-masked","slug":"diffusionbert-improving-generative-masked","title":"DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models","date":"2022-11-28","arxiv_id":"2211.15029","n_code_links":1,"syntology":{"ran":9,"of":11,"n_ran_checked":9,"n_instrument":0,"unverified":2,"pointer_only":2,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["hzfinfdu/diffusion-bert"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/dq-detr-dual-query-detection-transformer-for","slug":"dq-detr-dual-query-detection-transformer-for","title":"DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding","date":"2022-11-28","arxiv_id":"2211.15516","n_code_links":1,"syntology":null},{"paper":"/paper/gpt-neo-for-commonsense-reasoning-a","slug":"gpt-neo-for-commonsense-reasoning-a","title":"GPT-Neo for commonsense reasoning -- a theoretical and practical lens","date":"2022-11-28","arxiv_id":"2211.15593","n_code_links":1,"syntology":null},{"paper":null,"slug":"handling-and-extracting-key-entities-from","title":"Handling and extracting key entities from customer conversations using Speech recognition and Named Entity recognition","date":"2022-11-28","arxiv_id":"2211.17107","n_code_links":0,"syntology":null},{"paper":null,"slug":"is-it-required-ranking-the-skills-required","title":"Is it Required? Ranking the Skills Required for a Job-Title","date":"2022-11-28","arxiv_id":"2212.08553","n_code_links":0,"syntology":null},{"paper":null,"slug":"revisiting-distance-metric-learning-for-few","title":"Revisiting Distance Metric Learning for Few-Shot Natural Language Classification","date":"2022-11-28","arxiv_id":"2211.15202","n_code_links":0,"syntology":null},{"paper":"/paper/scientific-and-creative-analogies-in","slug":"scientific-and-creative-analogies-in","title":"Scientific and Creative Analogies in Pretrained Language Models","date":"2022-11-28","arxiv_id":"2211.15268","n_code_links":2,"syntology":null},{"paper":null,"slug":"summer-wechat-neural-machine-translation","title":"Summer: WeChat Neural Machine Translation Systems for the WMT22 Biomedical Translation Task","date":"2022-11-28","arxiv_id":"2211.15022","n_code_links":0,"syntology":null},{"paper":"/paper/superpoint-transformer-for-3d-scene-instance","slug":"superpoint-transformer-for-3d-scene-instance","title":"Superpoint Transformer for 3D Scene Instance Segmentation","date":"2022-11-28","arxiv_id":"2211.15766","n_code_links":1,"syntology":null},{"paper":"/paper/3d-point-positional-encoding-for-multi-camera","slug":"3d-point-positional-encoding-for-multi-camera","title":"3DPPE: 3D Point Positional Encoding for Multi-Camera 3D Object Detection Transformers","date":"2022-11-27","arxiv_id":"2211.14710","n_code_links":1,"syntology":null},{"paper":"/paper/a-time-series-is-worth-64-words-long-term","slug":"a-time-series-is-worth-64-words-long-term","title":"A Time Series is Worth 64 Words: Long-term Forecasting with Transformers","date":"2022-11-27","arxiv_id":"2211.14730","n_code_links":8,"syntology":{"ran":17,"of":30,"n_ran_checked":16,"n_instrument":1,"unverified":13,"pointer_only":0,"phrase":"17 ran (of which 2 constructed an object rather than computing a result; 16 with no instrument failure: 0 honoured, 0 violated, 16 with no contract checked; 1 where Syntology's instrument failed) · 13 unverified","official":{"repos":["yuqinie98/patchtst"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":6,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"awte-bert-attending-to-wordpiece-tokenization","title":"ESIE-BERT: Enriching Sub-words Information Explicitly with BERT for Joint Intent Classification and SlotFilling","date":"2022-11-27","arxiv_id":"2211.14829","n_code_links":0,"syntology":null},{"paper":null,"slug":"detect-localize-repair-a-unified-framework","title":"Detect-Localize-Repair: A Unified Framework for Learning to Debug with CodeT5","date":"2022-11-27","arxiv_id":"2211.14875","n_code_links":0,"syntology":null},{"paper":"/paper/prototype-as-query-for-few-shot-semantic","slug":"prototype-as-query-for-few-shot-semantic","title":"Prototype as Query for Few Shot Semantic Segmentation","date":"2022-11-27","arxiv_id":"2211.14764","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"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) · 0 unverified","official":{"repos":["leileicao/protoformer"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["unlocated"]}}},{"paper":"/paper/semantic-aware-local-global-vision","slug":"semantic-aware-local-global-vision","title":"Semantic-Aware Local-Global Vision Transformer","date":"2022-11-27","arxiv_id":"2211.14705","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-bloom-an-empirical-study-on","title":"Understanding BLOOM: An empirical study on diverse NLP tasks","date":"2022-11-27","arxiv_id":"2211.14865","n_code_links":0,"syntology":null},{"paper":"/paper/cddfuse-correlation-driven-dual-branch","slug":"cddfuse-correlation-driven-dual-branch","title":"CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion","date":"2022-11-26","arxiv_id":"2211.14461","n_code_links":3,"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":["zhaozixiang1228/mmif-cddfuse"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/cross-field-transformer-for-diabetic","slug":"cross-field-transformer-for-diabetic","title":"Cross-Field Transformer for Diabetic Retinopathy Grading on Two-field Fundus Images","date":"2022-11-26","arxiv_id":"2211.14552","n_code_links":1,"syntology":null},{"paper":"/paper/how-crucial-is-transformer-in-decision","slug":"how-crucial-is-transformer-in-decision","title":"How Crucial is Transformer in Decision Transformer?","date":"2022-11-26","arxiv_id":"2211.14655","n_code_links":1,"syntology":{"ran":2,"of":5,"n_ran_checked":1,"n_instrument":1,"unverified":3,"pointer_only":2,"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) · 3 unverified","official":{"repos":["max7born/decision-lstm"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/patchgt-transformer-over-non-trainable","slug":"patchgt-transformer-over-non-trainable","title":"PatchGT: Transformer over Non-trainable Clusters for Learning Graph Representations","date":"2022-11-26","arxiv_id":"2211.14425","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformer-based-model-for-word-level","title":"Transformer-based Model for Word Level Language Identification in Code-mixed Kannada-English Texts","date":"2022-11-26","arxiv_id":"2211.14459","n_code_links":0,"syntology":null},{"paper":"/paper/a-system-for-morphology-task-generalization","slug":"a-system-for-morphology-task-generalization","title":"A System for Morphology-Task Generalization via Unified Representation and Behavior Distillation","date":"2022-11-25","arxiv_id":"2211.14296","n_code_links":1,"syntology":null},{"paper":null,"slug":"aggregated-text-transformer-for-scene-text","title":"Aggregated Text Transformer for Scene Text Detection","date":"2022-11-25","arxiv_id":"2211.13984","n_code_links":0,"syntology":null},{"paper":"/paper/an-analysis-of-social-biases-present-in-bert","slug":"an-analysis-of-social-biases-present-in-bert","title":"An Analysis of Social Biases Present in BERT Variants Across Multiple Languages","date":"2022-11-25","arxiv_id":"2211.14402","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":["parishadbehnam/social-biases-in-bert-variants-across-multiple-languages"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"asynchronous-event-triggered-control-for-non","title":"Asynchronous Event-Triggered Control for Non-Linear Systems","date":"2022-11-25","arxiv_id":"2211.13846","n_code_links":0,"syntology":null},{"paper":"/paper/batmannet-bi-branch-masked-graph-transformer","slug":"batmannet-bi-branch-masked-graph-transformer","title":"BatmanNet: Bi-branch Masked Graph Transformer Autoencoder for Molecular Representation","date":"2022-11-25","arxiv_id":"2211.13979","n_code_links":1,"syntology":null},{"paper":null,"slug":"degenerate-swin-to-win-plain-window-based","title":"Degenerate Swin to Win: Plain Window-based Transformer without Sophisticated Operations","date":"2022-11-25","arxiv_id":"2211.14255","n_code_links":0,"syntology":null},{"paper":"/paper/finetuning-bert-on-partially-annotated-ner","slug":"finetuning-bert-on-partially-annotated-ner","title":"Finetuning BERT on Partially Annotated NER Corpora","date":"2022-11-25","arxiv_id":"2211.14360","n_code_links":1,"syntology":null},{"paper":"/paper/galvatron-efficient-transformer-training-over","slug":"galvatron-efficient-transformer-training-over","title":"Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism","date":"2022-11-25","arxiv_id":"2211.13878","n_code_links":3,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["pku-dair/hetu"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"gpt-3-driven-pedagogical-agents-for-training","title":"GPT-3-driven pedagogical agents for training children's curious question-asking skills","date":"2022-11-25","arxiv_id":"2211.14228","n_code_links":0,"syntology":null},{"paper":"/paper/interaction-visual-transformer-for-egocentric","slug":"interaction-visual-transformer-for-egocentric","title":"Interaction Region Visual Transformer for Egocentric Action Anticipation","date":"2022-11-25","arxiv_id":"2211.14154","n_code_links":1,"syntology":null},{"paper":null,"slug":"molecular-joint-representation-learning-via","title":"Molecular Joint Representation Learning via Multi-modal Information","date":"2022-11-25","arxiv_id":"2211.14042","n_code_links":0,"syntology":null},{"paper":null,"slug":"rust-latent-neural-scene-representations-from","title":"RUST: Latent Neural Scene Representations from Unposed Imagery","date":"2022-11-25","arxiv_id":"2211.14306","n_code_links":0,"syntology":null},{"paper":"/paper/spatial-spectral-transformer-for","slug":"spatial-spectral-transformer-for","title":"Spatial-Spectral Transformer for Hyperspectral Image Denoising","date":"2022-11-25","arxiv_id":"2211.14090","n_code_links":3,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":2,"phrase":"0 ran · 2 unverified","official":{"repos":["myuli/sst"],"state":"official: not harvested","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":[]}}}],"record_sha256":"6b6bde27d450c78c4712d24cbf80928f11286dc31b0116b8edde51c9a45af118","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}