{"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/linear-layer/papers/185","list_of":"/method/linear-layer","method":"Linear Layer","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":185,"pages_in_order":255,"rows_per_page":100,"rows":[18401,18500],"of":25421,"counts":{"archive_papers_tagged":25421,"with_a_code_link":11479,"where_syntology_ran_a_sample":3523,"not_listed_spam_title":0,"listed":25421,"listed_where_code_ran":3523,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":2976,"every_run_a_failure_of_syntologys_instrument":547,"listed_with_a_run_with_no_instrument_failure":2976,"listed_every_run_a_failure_of_syntologys_instrument":547,"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/linear-layer","prev":"/method/linear-layer/papers/184","next":"/method/linear-layer/papers/186","papers":[{"paper":"/paper/vrt-a-video-restoration-transformer","slug":"vrt-a-video-restoration-transformer","title":"VRT: A Video Restoration Transformer","date":"2022-01-28","arxiv_id":"2201.12288","n_code_links":1,"syntology":{"ran":4,"of":5,"n_ran_checked":0,"n_instrument":4,"unverified":1,"pointer_only":5,"phrase":"4 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; 4 where Syntology's instrument failed) · 1 unverified","official":{"repos":["jingyunliang/vrt"],"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","unlocated"]}}},{"paper":"/paper/clinical-longformer-and-clinical-bigbird","slug":"clinical-longformer-and-clinical-bigbird","title":"Clinical-Longformer and Clinical-BigBird: Transformers for long clinical sequences","date":"2022-01-27","arxiv_id":"2201.11838","n_code_links":1,"syntology":null},{"paper":"/paper/generalised-image-outpainting-with-u","slug":"generalised-image-outpainting-with-u","title":"Generalised Image Outpainting with U-Transformer","date":"2022-01-27","arxiv_id":"2201.11403","n_code_links":1,"syntology":null},{"paper":"/paper/going-extreme-comparative-analysis-of-hate","slug":"going-extreme-comparative-analysis-of-hate","title":"Going Extreme: Comparative Analysis of Hate Speech in Parler and Gab","date":"2022-01-27","arxiv_id":"2201.11770","n_code_links":1,"syntology":null},{"paper":"/paper/grad2task-improved-few-shot-text-1","slug":"grad2task-improved-few-shot-text-1","title":"Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation","date":"2022-01-27","arxiv_id":"2201.11576","n_code_links":1,"syntology":null},{"paper":"/paper/reasoning-like-program-executors-1","slug":"reasoning-like-program-executors-1","title":"Reasoning Like Program Executors","date":"2022-01-27","arxiv_id":"2201.11473","n_code_links":1,"syntology":null},{"paper":"/paper/transformer-module-networks-for-systematic","slug":"transformer-module-networks-for-systematic","title":"Transformer Module Networks for Systematic Generalization in Visual Question Answering","date":"2022-01-27","arxiv_id":"2201.11316","n_code_links":1,"syntology":null},{"paper":"/paper/a-comprehensive-study-of-image-classification","slug":"a-comprehensive-study-of-image-classification","title":"A Comprehensive Study of Image Classification Model Sensitivity to Foregrounds, Backgrounds, and Visual Attributes","date":"2022-01-26","arxiv_id":"2201.10766","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":["mmoayeri/rival10"],"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/discoscore-evaluating-text-generation-with","slug":"discoscore-evaluating-text-generation-with","title":"DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence","date":"2022-01-26","arxiv_id":"2201.11176","n_code_links":1,"syntology":null},{"paper":null,"slug":"dnnfuser-generative-pre-trained-transformer","title":"DNNFuser: Generative Pre-Trained Transformer as a Generalized Mapper for Layer Fusion in DNN Accelerators","date":"2022-01-26","arxiv_id":"2201.11218","n_code_links":0,"syntology":null},{"paper":null,"slug":"dsformer-a-dual-domain-self-supervised","title":"DSFormer: A Dual-domain Self-supervised Transformer for Accelerated Multi-contrast MRI Reconstruction","date":"2022-01-26","arxiv_id":"2201.10776","n_code_links":0,"syntology":null},{"paper":null,"slug":"dual-decoder-transformer-for-end-to-end","title":"On the Effectiveness of Pinyin-Character Dual-Decoding for End-to-End Mandarin Chinese ASR","date":"2022-01-26","arxiv_id":"2201.10792","n_code_links":0,"syntology":null},{"paper":"/paper/dual-tasks-siamese-transformer-framework-for","slug":"dual-tasks-siamese-transformer-framework-for","title":"Dual-Tasks Siamese Transformer Framework for Building Damage Assessment","date":"2022-01-26","arxiv_id":"2201.10953","n_code_links":0,"syntology":null},{"paper":"/paper/fincat-financial-numeral-claim-analysis-tool","slug":"fincat-financial-numeral-claim-analysis-tool","title":"FiNCAT: Financial Numeral Claim Analysis Tool","date":"2022-01-26","arxiv_id":"2202.00631","n_code_links":1,"syntology":null},{"paper":"/paper/neural-grapheme-to-phoneme-conversion-with","slug":"neural-grapheme-to-phoneme-conversion-with","title":"Neural Grapheme-to-Phoneme Conversion with Pre-trained Grapheme Models","date":"2022-01-26","arxiv_id":"2201.10716","n_code_links":1,"syntology":null},{"paper":"/paper/predicting-knee-osteoarthritis-progression","slug":"predicting-knee-osteoarthritis-progression","title":"Predicting Knee Osteoarthritis Progression from Structural MRI using Deep Learning","date":"2022-01-26","arxiv_id":"2201.10849","n_code_links":1,"syntology":null},{"paper":null,"slug":"self-supervised-3d-semantic-representation","title":"Self-supervised 3D Semantic Representation Learning for Vision-and-Language Navigation","date":"2022-01-26","arxiv_id":"2201.10788","n_code_links":0,"syntology":null},{"paper":"/paper/synchromesh-reliable-code-generation-from-pre-1","slug":"synchromesh-reliable-code-generation-from-pre-1","title":"Synchromesh: Reliable code generation from pre-trained language models","date":"2022-01-26","arxiv_id":"2201.11227","n_code_links":2,"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":null}},{"paper":null,"slug":"transppg-two-stream-transformer-for-remote","title":"TransPPG: Two-stream Transformer for Remote Heart Rate Estimate","date":"2022-01-26","arxiv_id":"2201.10873","n_code_links":0,"syntology":null},{"paper":"/paper/when-shift-operation-meets-vision-transformer","slug":"when-shift-operation-meets-vision-transformer","title":"When Shift Operation Meets Vision Transformer: An Extremely Simple Alternative to Attention Mechanism","date":"2022-01-26","arxiv_id":"2201.10801","n_code_links":2,"syntology":{"ran":6,"of":7,"n_ran_checked":6,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"6 ran (of which 6 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) · 1 unverified; every one of the 6 samples that ran constructed an object rather than computing a result","official":{"repos":["microsoft/SPACH"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":6,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"attention-based-vandalism-detection-in","title":"Attention-Based Vandalism Detection in OpenStreetMap","date":"2022-01-25","arxiv_id":"2201.10406","n_code_links":0,"syntology":null},{"paper":"/paper/bertha-video-captioning-evaluation-via","slug":"bertha-video-captioning-evaluation-via","title":"BERTHA: Video Captioning Evaluation Via Transfer-Learned Human Assessment","date":"2022-01-25","arxiv_id":"2201.10243","n_code_links":1,"syntology":null},{"paper":"/paper/convolutional-xformers-for-vision","slug":"convolutional-xformers-for-vision","title":"Convolutional Xformers for Vision","date":"2022-01-25","arxiv_id":"2201.10271","n_code_links":1,"syntology":null},{"paper":"/paper/explore-and-match-end-to-end-video-grounding","slug":"explore-and-match-end-to-end-video-grounding","title":"Explore-And-Match: Bridging Proposal-Based and Proposal-Free With Transformer for Sentence Grounding in Videos","date":"2022-01-25","arxiv_id":"2201.10168","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-non-autoregressive-end-to-end","title":"Improving non-autoregressive end-to-end speech recognition with pre-trained acoustic and language models","date":"2022-01-25","arxiv_id":"2201.10103","n_code_links":0,"syntology":null},{"paper":null,"slug":"masked-transformer-for-neighhourhood-aware","title":"Neighbour Interaction based Click-Through Rate Prediction via Graph-masked Transformer","date":"2022-01-25","arxiv_id":"2201.13311","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimal-transport-based-data-augmentation-for","title":"Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation","date":"2022-01-25","arxiv_id":"2202.00567","n_code_links":0,"syntology":null},{"paper":null,"slug":"pre-trained-language-transformers-are","title":"Pre-Trained Language Transformers are Universal Image Classifiers","date":"2022-01-25","arxiv_id":"2201.10182","n_code_links":0,"syntology":null},{"paper":"/paper/vit-hgr-vision-transformer-based-hand-gesture","slug":"vit-hgr-vision-transformer-based-hand-gesture","title":"ViT-HGR: Vision Transformer-based Hand Gesture Recognition from High Density Surface EMG Signals","date":"2022-01-25","arxiv_id":"2201.10060","n_code_links":1,"syntology":null},{"paper":null,"slug":"whose-language-counts-as-high-quality","title":"Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection","date":"2022-01-25","arxiv_id":"2201.10474","n_code_links":0,"syntology":null},{"paper":null,"slug":"zero-shot-long-form-voice-cloning-with","title":"Zero-Shot Long-Form Voice Cloning with Dynamic Convolution Attention","date":"2022-01-25","arxiv_id":"2201.10375","n_code_links":0,"syntology":null},{"paper":null,"slug":"zero-shot-sketch-based-image-retrieval-using","title":"Zero-Shot Sketch Based Image Retrieval using Graph Transformer","date":"2022-01-25","arxiv_id":"2201.10185","n_code_links":0,"syntology":null},{"paper":null,"slug":"emotion-based-modeling-of-mental-disorders-on","title":"Emotion-based Modeling of Mental Disorders on Social Media","date":"2022-01-24","arxiv_id":"2201.09451","n_code_links":0,"syntology":null},{"paper":"/paper/improving-chest-x-ray-report-generation-by","slug":"improving-chest-x-ray-report-generation-by","title":"Improving Chest X-Ray Report Generation by Leveraging Warm Starting","date":"2022-01-24","arxiv_id":"2201.09405","n_code_links":1,"syntology":null},{"paper":"/paper/patches-are-all-you-need-1","slug":"patches-are-all-you-need-1","title":"Patches Are All You Need?","date":"2022-01-24","arxiv_id":"2201.09792","n_code_links":12,"syntology":{"ran":8,"of":8,"n_ran_checked":7,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 5 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["locuslab/convmixer","tmp-iclr/convmixer"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"polyphone-disambiguation-and-accent","title":"Polyphone disambiguation and accent prediction using pre-trained language models in Japanese TTS front-end","date":"2022-01-24","arxiv_id":"2201.09427","n_code_links":0,"syntology":null},{"paper":null,"slug":"synthetic-books","title":"Synthetic Books","date":"2022-01-24","arxiv_id":"2201.09518","n_code_links":0,"syntology":null},{"paper":"/paper/transformers-in-medical-imaging-a-survey","slug":"transformers-in-medical-imaging-a-survey","title":"Transformers in Medical Imaging: A Survey","date":"2022-01-24","arxiv_id":"2201.09873","n_code_links":1,"syntology":null},{"paper":"/paper/unified-multimodal-punctuation-restoration","slug":"unified-multimodal-punctuation-restoration","title":"Unified Multimodal Punctuation Restoration Framework for Mixed-Modality Corpus","date":"2022-01-24","arxiv_id":"2202.00468","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-large-and-diverse-arabic-corpus-for","title":"A Large and Diverse Arabic Corpus for Language Modeling","date":"2022-01-23","arxiv_id":"2201.09227","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-pre-trained-audio-visual-transformer-for","title":"A Pre-trained Audio-Visual Transformer for Emotion Recognition","date":"2022-01-23","arxiv_id":"2201.09165","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-survey-for-deep-rgbt-tracking","title":"A Survey for Deep RGBT Tracking","date":"2022-01-23","arxiv_id":"2201.09296","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-application-of-pseudo-log-likelihoods-to","title":"An Application of Pseudo-Log-Likelihoods to Natural Language Scoring","date":"2022-01-23","arxiv_id":"2201.09377","n_code_links":0,"syntology":null},{"paper":"/paper/fast-mri-reconstruction-how-powerful","slug":"fast-mri-reconstruction-how-powerful","title":"Fast MRI Reconstruction: How Powerful Transformers Are?","date":"2022-01-23","arxiv_id":"2201.09400","n_code_links":1,"syntology":null},{"paper":"/paper/investigating-expressiveness-of-transformer","slug":"investigating-expressiveness-of-transformer","title":"How Expressive are Transformers in Spectral Domain for Graphs?","date":"2022-01-23","arxiv_id":"2201.09332","n_code_links":1,"syntology":{"ran":4,"of":6,"n_ran_checked":4,"n_instrument":0,"unverified":2,"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) · 2 unverified","official":{"repos":["ansonb/FeTA_TMLR"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/reconformer-accelerated-mri-reconstruction","slug":"reconformer-accelerated-mri-reconstruction","title":"ReconFormer: Accelerated MRI Reconstruction Using Recurrent Transformer","date":"2022-01-23","arxiv_id":"2201.09376","n_code_links":1,"syntology":null},{"paper":null,"slug":"dual-flattening-transformers-through","title":"Dual-Flattening Transformers through Decomposed Row and Column Queries for Semantic Segmentation","date":"2022-01-22","arxiv_id":"2201.09139","n_code_links":0,"syntology":null},{"paper":"/paper/a-comparative-study-on-language-models-for-1","slug":"a-comparative-study-on-language-models-for-1","title":"A Comparative Study on Language Models for Task-Oriented Dialogue Systems","date":"2022-01-21","arxiv_id":"2201.08687","n_code_links":1,"syntology":null},{"paper":null,"slug":"autodistill-an-end-to-end-framework-to","title":"AutoDistill: an End-to-End Framework to Explore and Distill Hardware-Efficient Language Models","date":"2022-01-21","arxiv_id":"2201.08539","n_code_links":0,"syntology":null},{"paper":"/paper/black-box-prompt-learning-for-pre-trained","slug":"black-box-prompt-learning-for-pre-trained","title":"Black-box Prompt Learning for Pre-trained Language Models","date":"2022-01-21","arxiv_id":"2201.08531","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"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) · 1 unverified","official":{"repos":["shizhediao/black-box-prompt-learning"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/dual-contrastive-learning-text-classification","slug":"dual-contrastive-learning-text-classification","title":"Dual Contrastive Learning: Text Classification via Label-Aware Data Augmentation","date":"2022-01-21","arxiv_id":"2201.08702","n_code_links":2,"syntology":null},{"paper":"/paper/fast-differentiable-matrix-square-root-1","slug":"fast-differentiable-matrix-square-root-1","title":"Fast Differentiable Matrix Square Root","date":"2022-01-21","arxiv_id":"2201.08663","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":["KingJamesSong/DifferentiableSVD"],"state":"official: harvested for another paper","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":[]}}},{"paper":null,"slug":"less-is-less-when-are-snippets-insufficient","title":"Less is Less: When Are Snippets Insufficient for Human vs Machine Relevance Estimation?","date":"2022-01-21","arxiv_id":"2201.08721","n_code_links":0,"syntology":null},{"paper":"/paper/representing-long-range-context-for-graph-1","slug":"representing-long-range-context-for-graph-1","title":"Representing Long-Range Context for Graph Neural Networks with Global Attention","date":"2022-01-21","arxiv_id":"2201.08821","n_code_links":1,"syntology":{"ran":7,"of":14,"n_ran_checked":6,"n_instrument":1,"unverified":7,"pointer_only":0,"phrase":"7 ran (of which 5 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 7 unverified","official":{"repos":["ucbrise/graphtrans"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":5,"n_ran_no_instrument_failure":6,"n_unverified":7,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"uncertainty-cognizant-model-predictive","title":"Uncertainty-Cognizant Model Predictive Control for Energy Management of Residential Buildings with PVT and Thermal Energy Storage","date":"2022-01-21","arxiv_id":"2201.08909","n_code_links":0,"syntology":null},{"paper":"/paper/cheating-automatic-short-answer-grading-on","slug":"cheating-automatic-short-answer-grading-on","title":"Cheating Automatic Short Answer Grading: On the Adversarial Usage of Adjectives and Adverbs","date":"2022-01-20","arxiv_id":"2201.08318","n_code_links":1,"syntology":null},{"paper":"/paper/memvit-memory-augmented-multiscale-vision","slug":"memvit-memory-augmented-multiscale-vision","title":"MeMViT: Memory-Augmented Multiscale Vision Transformer for Efficient Long-Term Video Recognition","date":"2022-01-20","arxiv_id":"2201.08383","n_code_links":1,"syntology":null},{"paper":null,"slug":"meta-learning-for-code-summarization-1","title":"Meta Learning for Code Summarization","date":"2022-01-20","arxiv_id":"2201.08310","n_code_links":0,"syntology":null},{"paper":null,"slug":"sentiment-analysis-predicting-yelp-scores","title":"Sentiment Analysis: Predicting Yelp Scores","date":"2022-01-20","arxiv_id":"2201.07999","n_code_links":0,"syntology":null},{"paper":null,"slug":"tervit-an-efficient-ternary-vision","title":"TerViT: An Efficient Ternary Vision Transformer","date":"2022-01-20","arxiv_id":"2201.08050","n_code_links":0,"syntology":null},{"paper":"/paper/transfer-learning-approaches-for-building","slug":"transfer-learning-approaches-for-building","title":"Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models","date":"2022-01-20","arxiv_id":"2201.08471","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":["hltcoe/colbert-x"],"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/gap-gen-guided-automatic-python-code","slug":"gap-gen-guided-automatic-python-code","title":"GAP-Gen: Guided Automatic Python Code Generation","date":"2022-01-19","arxiv_id":"2201.08810","n_code_links":1,"syntology":null},{"paper":"/paper/near-optimal-sparse-allreduce-for-distributed","slug":"near-optimal-sparse-allreduce-for-distributed","title":"Near-Optimal Sparse Allreduce for Distributed Deep Learning","date":"2022-01-19","arxiv_id":"2201.07598","n_code_links":1,"syntology":null},{"paper":"/paper/poseur-direct-human-pose-regression-with","slug":"poseur-direct-human-pose-regression-with","title":"Poseur: Direct Human Pose Regression with Transformers","date":"2022-01-19","arxiv_id":"2201.07412","n_code_links":1,"syntology":null},{"paper":"/paper/q-vit-fully-differentiable-quantization-for","slug":"q-vit-fully-differentiable-quantization-for","title":"Q-ViT: Fully Differentiable Quantization for Vision Transformer","date":"2022-01-19","arxiv_id":"2201.07703","n_code_links":1,"syntology":{"ran":7,"of":9,"n_ran_checked":5,"n_instrument":2,"unverified":2,"pointer_only":9,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 2 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["zhexinli/Q-ViT-DeiT"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"swin-pose-swin-transformer-based-human-pose","title":"Swin-Pose: Swin Transformer Based Human Pose Estimation","date":"2022-01-19","arxiv_id":"2201.07384","n_code_links":0,"syntology":null},{"paper":null,"slug":"tourbert-a-pretrained-language-model-for-the","title":"TourBERT: A pretrained language model for the tourism industry","date":"2022-01-19","arxiv_id":"2201.07449","n_code_links":0,"syntology":null},{"paper":null,"slug":"transfuse-a-unified-transformer-based-image","title":"TransFuse: A Unified Transformer-based Image Fusion Framework using Self-supervised Learning","date":"2022-01-19","arxiv_id":"2201.07451","n_code_links":0,"syntology":null},{"paper":"/paper/coauthor-designing-a-human-ai-collaborative","slug":"coauthor-designing-a-human-ai-collaborative","title":"CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities","date":"2022-01-18","arxiv_id":"2201.06796","n_code_links":1,"syntology":null},{"paper":null,"slug":"gtrans-spatiotemporal-autoregressive","title":"GTrans: Spatiotemporal Autoregressive Transformer with Graph Embeddings for Nowcasting Extreme Events","date":"2022-01-18","arxiv_id":"2201.06717","n_code_links":0,"syntology":null},{"paper":null,"slug":"hierarchical-neural-network-approaches-for","title":"Hierarchical Neural Network Approaches for Long Document Classification","date":"2022-01-18","arxiv_id":"2201.06774","n_code_links":0,"syntology":null},{"paper":"/paper/motion-inbetweening-via-deep-d-interpolator","slug":"motion-inbetweening-via-deep-d-interpolator","title":"Motion Inbetweening via Deep $Δ$-Interpolator","date":"2022-01-18","arxiv_id":"2201.06701","n_code_links":1,"syntology":null},{"paper":null,"slug":"repre-improving-self-supervised-vision","title":"RePre: Improving Self-Supervised Vision Transformer with Reconstructive Pre-training","date":"2022-01-18","arxiv_id":"2201.06857","n_code_links":0,"syntology":null},{"paper":"/paper/resistance-training-using-prior-bias-toward","slug":"resistance-training-using-prior-bias-toward","title":"Resistance Training using Prior Bias: toward Unbiased Scene Graph Generation","date":"2022-01-18","arxiv_id":"2201.06794","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":3,"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":["chch1999/rtpb"],"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":"towards-controllable-protein-design-with","title":"Controllable Protein Design with Language Models","date":"2022-01-18","arxiv_id":"2201.07338","n_code_links":0,"syntology":null},{"paper":null,"slug":"bert-vs-albert-explained","title":"BERT vs ALBERT explained","date":"2022-01-17","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/continual-transformers-redundancy-free","slug":"continual-transformers-redundancy-free","title":"Continual Transformers: Redundancy-Free Attention for Online Inference","date":"2022-01-17","arxiv_id":"2201.06268","n_code_links":1,"syntology":null},{"paper":null,"slug":"disentangled-latent-transformer-for","title":"Disentangled Latent Transformer for Interpretable Monocular Height Estimation","date":"2022-01-17","arxiv_id":"2201.06357","n_code_links":0,"syntology":null},{"paper":"/paper/korean-specific-dataset-for-table-question","slug":"korean-specific-dataset-for-table-question","title":"Korean-Specific Dataset for Table Question Answering","date":"2022-01-17","arxiv_id":"2201.06223","n_code_links":1,"syntology":null},{"paper":null,"slug":"looking-at-the-performer-from-a-hopfield","title":"Looking at the Performer from a Hopfield Point of View","date":"2022-01-17","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/mulve-a-multi-language-vocabulary-evaluation","slug":"mulve-a-multi-language-vocabulary-evaluation","title":"MuLVE, A Multi-Language Vocabulary Evaluation Data Set","date":"2022-01-17","arxiv_id":"2201.06286","n_code_links":0,"syntology":null},{"paper":"/paper/squire-a-sequence-to-sequence-framework-for","slug":"squire-a-sequence-to-sequence-framework-for","title":"SQUIRE: A Sequence-to-sequence Framework for Multi-hop Knowledge Graph Reasoning","date":"2022-01-17","arxiv_id":"2201.06206","n_code_links":1,"syntology":null},{"paper":"/paper/swinunet3d-a-hierarchical-architecture-for","slug":"swinunet3d-a-hierarchical-architecture-for","title":"SwinUNet3D -- A Hierarchical Architecture for Deep Traffic Prediction using Shifted Window Transformers","date":"2022-01-17","arxiv_id":"2201.06390","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"2 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["bojesomo/Traffic4Cast2021-SwinUNet3D"],"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"]}}},{"paper":null,"slug":"unintended-bias-in-language-model","title":"Unintended Bias in Language Model-driven Conversational Recommendation","date":"2022-01-17","arxiv_id":"2201.06224","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-balanced-data-approach-for-evaluating-cross","title":"A Balanced Data Approach for Evaluating Cross-Lingual Transfer: Mapping the Linguistic Blood Bank","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"a-multi-granularity-opinion-summarization","title":"A Multi-Granularity Opinion Summarization Method","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"a-study-of-pre-trained-language-models-for","title":"A Study of Pre-trained Language Models for Analogy Generation","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"a-study-of-the-attention-abnormality-in","title":"A Study of the Attention Abnormality in Trojaned BERTs","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"allwoz-towards-multilingual-task-oriented-1","title":"AllWOZ: Towards Multilingual Task-Oriented Dialog Systems for All","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"an-exploitation-of-heterogeneous-graph-neural","title":"An Exploitation of Heterogeneous Graph Neural Network for Extractive Long Document Summarization","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"applying-softtriple-loss-for-supervised-1","title":"Applying SoftTriple Loss for Supervised Language Model Fine Tuning","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"arabart-a-pretrained-arabic-sequence-to","title":"AraBART: a Pretrained Arabic Sequence-to-Sequence Model for Abstractive Summarization","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"are-pretrained-multilingual-models-equally","title":"Are Pretrained Multilingual Models Equally Fair Across Languages?","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"auto-regressive-text-generation-with-pre","title":"Auto-regressive Text Generation with Pre-Trained Language Models: An Empirical Study on Question-type Short Text Generation","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"autoattention-automatic-attention-head","title":"AutoAttention: Automatic Attention Head Selection Through Differentiable Pruning","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"bridge-the-gap-between-cv-and-nlp-a-gradient-1","title":"Bridge the Gap Between CV and NLP! A Gradient-based Textual Adversarial Attack Framework","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"can-bert-conduct-logical-reasoning-on-the","title":"Can BERT Conduct Logical Reasoning? On the Difficulty of Learning to Reason from Data","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"challenge-for-open-domain-targeted-sentiment","title":"Challenge for open-domain targeted sentiment analysis","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"context-aware-prompt-customize-a-unique","title":"Context-Aware Prompt: Customize A Unique Prompt For Each Input","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"conventional-clustering-based-method-for","title":"Conventional clustering-based method for event detection on social networks","date":"2022-01-16","arxiv_id":null,"n_code_links":0,"syntology":null}],"record_sha256":"c25c6d9caf18748c60702641b4746e32f4df1abf0ddb4abb09b4f0211f256570","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}