{"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/143","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":143,"pages_in_order":249,"rows_per_page":100,"rows":[14201,14300],"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/142","next":"/method/multi-head-attention/papers/144","papers":[{"paper":null,"slug":"monoatt-online-monocular-3d-object-detection","title":"MonoATT: Online Monocular 3D Object Detection with Adaptive Token Transformer","date":"2023-03-23","arxiv_id":"2303.13018","n_code_links":0,"syntology":null},{"paper":null,"slug":"msfa-frequency-aware-transformer-for","title":"MSFA-Frequency-Aware Transformer for Hyperspectral Images Demosaicing","date":"2023-03-23","arxiv_id":"2303.13404","n_code_links":0,"syntology":null},{"paper":"/paper/patch-mix-transformer-for-unsupervised-domain","slug":"patch-mix-transformer-for-unsupervised-domain","title":"Patch-Mix Transformer for Unsupervised Domain Adaptation: A Game Perspective","date":"2023-03-23","arxiv_id":"2303.13434","n_code_links":0,"syntology":null},{"paper":null,"slug":"pointgame-geometrically-and-adaptively-masked","title":"PointGame: Geometrically and Adaptively Masked Auto-Encoder on Point Clouds","date":"2023-03-23","arxiv_id":"2303.13100","n_code_links":0,"syntology":null},{"paper":"/paper/retrieval-augmented-classification-with","slug":"retrieval-augmented-classification-with","title":"Retrieval-Augmented Classification with Decoupled Representation","date":"2023-03-23","arxiv_id":"2303.13065","n_code_links":1,"syntology":null},{"paper":null,"slug":"scaled-quantization-for-the-vision","title":"Scaled Quantization for the Vision Transformer","date":"2023-03-23","arxiv_id":"2303.13601","n_code_links":0,"syntology":null},{"paper":"/paper/top-down-visual-attention-from-analysis-by","slug":"top-down-visual-attention-from-analysis-by","title":"Top-Down Visual Attention from Analysis by Synthesis","date":"2023-03-23","arxiv_id":"2303.13043","n_code_links":1,"syntology":null},{"paper":null,"slug":"transposer-transformer-as-an-optimizer-for","title":"TransPoser: Transformer as an Optimizer for Joint Object Shape and Pose Estimation","date":"2023-03-23","arxiv_id":"2303.13477","n_code_links":0,"syntology":null},{"paper":"/paper/zero-guidance-segmentation-using-zero-segment","slug":"zero-guidance-segmentation-using-zero-segment","title":"Zero-guidance Segmentation Using Zero Segment Labels","date":"2023-03-23","arxiv_id":"2303.13396","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-small-scale-switch-transformer-and-nlp","title":"Improving Transformer Performance for French Clinical Notes Classification Using Mixture of Experts on a Limited Dataset","date":"2023-03-22","arxiv_id":"2303.12892","n_code_links":0,"syntology":null},{"paper":"/paper/an-extended-study-of-human-like-behavior","slug":"an-extended-study-of-human-like-behavior","title":"An Extended Study of Human-like Behavior under Adversarial Training","date":"2023-03-22","arxiv_id":"2303.12669","n_code_links":1,"syntology":null},{"paper":null,"slug":"analyzing-the-generalizability-of-deep","title":"Analyzing the Generalizability of Deep Contextualized Language Representations For Text Classification","date":"2023-03-22","arxiv_id":"2303.12936","n_code_links":0,"syntology":null},{"paper":null,"slug":"end-to-end-personalized-next-location","title":"End-to-End Personalized Next Location Recommendation via Contrastive User Preference Modeling","date":"2023-03-22","arxiv_id":"2303.12507","n_code_links":0,"syntology":null},{"paper":"/paper/featurenerf-learning-generalizable-nerfs-by","slug":"featurenerf-learning-generalizable-nerfs-by","title":"FeatureNeRF: Learning Generalizable NeRFs by Distilling Foundation Models","date":"2023-03-22","arxiv_id":"2303.12786","n_code_links":1,"syntology":{"ran":5,"of":7,"n_ran_checked":5,"n_instrument":0,"unverified":2,"pointer_only":2,"phrase":"5 ran (of which 0 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) · 2 unverified","official":{"repos":["jianglongye/featurenerf"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"generate-labeled-training-data-using-prompt","title":"Generate labeled training data using Prompt Programming and GPT-3. An example of Big Five Personality Classification","date":"2023-03-22","arxiv_id":"2303.12279","n_code_links":0,"syntology":null},{"paper":"/paper/mega-multilingual-evaluation-of-generative-ai","slug":"mega-multilingual-evaluation-of-generative-ai","title":"MEGA: Multilingual Evaluation of Generative AI","date":"2023-03-22","arxiv_id":"2303.12528","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":7,"n_instrument":1,"unverified":2,"pointer_only":1,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":null}},{"paper":null,"slug":"octr-octree-based-transformer-for-3d-object","title":"OcTr: Octree-based Transformer for 3D Object Detection","date":"2023-03-22","arxiv_id":"2303.12621","n_code_links":0,"syntology":null},{"paper":"/paper/open-source-frame-semantic-parsing","slug":"open-source-frame-semantic-parsing","title":"Open-source Frame Semantic Parsing","date":"2023-03-22","arxiv_id":"2303.12788","n_code_links":1,"syntology":null},{"paper":null,"slug":"semantic-communication-with-memory","title":"Semantic Communication with Memory","date":"2023-03-22","arxiv_id":"2303.12335","n_code_links":0,"syntology":null},{"paper":"/paper/sparks-of-artificial-general-intelligence","slug":"sparks-of-artificial-general-intelligence","title":"Sparks of Artificial General Intelligence: Early experiments with GPT-4","date":"2023-03-22","arxiv_id":"2303.12712","n_code_links":3,"syntology":{"ran":9,"of":10,"n_ran_checked":9,"n_instrument":0,"unverified":1,"pointer_only":0,"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) · 1 unverified","official":null}},{"paper":null,"slug":"tron-transformer-neural-network-acceleration","title":"TRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonics","date":"2023-03-22","arxiv_id":"2303.12914","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-complete-survey-on-generative-ai-aigc-is","title":"A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?","date":"2023-03-21","arxiv_id":"2303.11717","n_code_links":0,"syntology":null},{"paper":null,"slug":"artificial-muses-generative-artificial","title":"Artificial muses: Generative Artificial Intelligence Chatbots Have Risen to Human-Level Creativity","date":"2023-03-21","arxiv_id":"2303.12003","n_code_links":0,"syntology":null},{"paper":null,"slug":"chatgpt-and-a-new-academic-reality-ai-written","title":"ChatGPT and a New Academic Reality: Artificial Intelligence-Written Research Papers and the Ethics of the Large Language Models in Scholarly Publishing","date":"2023-03-21","arxiv_id":"2303.13367","n_code_links":0,"syntology":null},{"paper":"/paper/ctbl-augmenting-large-language-models-for","slug":"ctbl-augmenting-large-language-models-for","title":"cTBLS: Augmenting Large Language Models with Conversational Tables","date":"2023-03-21","arxiv_id":"2303.12024","n_code_links":1,"syntology":null},{"paper":"/paper/debiased-contrastive-learning-for-sequential","slug":"debiased-contrastive-learning-for-sequential","title":"Debiased Contrastive Learning for Sequential Recommendation","date":"2023-03-21","arxiv_id":"2303.11780","n_code_links":1,"syntology":{"ran":3,"of":5,"n_ran_checked":3,"n_instrument":0,"unverified":2,"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) · 2 unverified","official":{"repos":["hkuds/dcrec"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/difficulty-in-learning-chirality-for","slug":"difficulty-in-learning-chirality-for","title":"Difficulty in chirality recognition for Transformer architectures learning chemical structures from string","date":"2023-03-21","arxiv_id":"2303.11593","n_code_links":1,"syntology":null},{"paper":null,"slug":"fine-tuning-climatebert-transformer-with","title":"Fine-tuning ClimateBert transformer with ClimaText for the disclosure analysis of climate-related financial risks","date":"2023-03-21","arxiv_id":"2303.13373","n_code_links":0,"syntology":null},{"paper":"/paper/is-bert-blind-exploring-the-effect-of-vision","slug":"is-bert-blind-exploring-the-effect-of-vision","title":"Is BERT Blind? Exploring the Effect of Vision-and-Language Pretraining on Visual Language Understanding","date":"2023-03-21","arxiv_id":"2303.12513","n_code_links":1,"syntology":null},{"paper":"/paper/learning-a-sparse-transformer-network-for","slug":"learning-a-sparse-transformer-network-for","title":"Learning A Sparse Transformer Network for Effective Image Deraining","date":"2023-03-21","arxiv_id":"2303.11950","n_code_links":1,"syntology":{"ran":8,"of":11,"n_ran_checked":8,"n_instrument":0,"unverified":3,"pointer_only":11,"phrase":"8 ran (of which 8 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified; every one of the 8 samples that ran constructed an object rather than computing a result","official":{"repos":["cschenxiang/drsformer"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":8,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"machine-learning-for-brain-disorders","title":"Machine Learning for Brain Disorders: Transformers and Visual Transformers","date":"2023-03-21","arxiv_id":"2303.12068","n_code_links":0,"syntology":null},{"paper":"/paper/mstformer-motion-inspired-spatial-temporal","slug":"mstformer-motion-inspired-spatial-temporal","title":"MSTFormer: Motion Inspired Spatial-temporal Transformer with Dynamic-aware Attention for long-term Vessel Trajectory Prediction","date":"2023-03-21","arxiv_id":"2303.11540","n_code_links":1,"syntology":null},{"paper":null,"slug":"multimodal-pre-training-framework-for","title":"Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning","date":"2023-03-21","arxiv_id":"2303.11879","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-table-structure-recognition-with","title":"Robust Table Structure Recognition with Dynamic Queries Enhanced Detection Transformer","date":"2023-03-21","arxiv_id":"2303.11615","n_code_links":0,"syntology":null},{"paper":"/paper/sift-sparse-iso-flop-transformations-for","slug":"sift-sparse-iso-flop-transformations-for","title":"Sparse-IFT: Sparse Iso-FLOP Transformations for Maximizing Training Efficiency","date":"2023-03-21","arxiv_id":"2303.11525","n_code_links":2,"syntology":{"ran":21,"of":24,"n_ran_checked":20,"n_instrument":1,"unverified":3,"pointer_only":2,"phrase":"21 ran (of which 0 constructed an object rather than computing a result; 20 with no instrument failure: 0 honoured, 0 violated, 20 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["cerebrasresearch/sift","cerebrasresearch/sparse-ift"],"state":"official (archive's flag): 21 ran","n_ran":21,"n_constructed":0,"n_ran_no_instrument_failure":20,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/the-multiscale-surface-vision-transformer","slug":"the-multiscale-surface-vision-transformer","title":"The Multiscale Surface Vision Transformer","date":"2023-03-21","arxiv_id":"2303.11909","n_code_links":1,"syntology":null},{"paper":"/paper/capabilities-of-gpt-4-on-medical-challenge","slug":"capabilities-of-gpt-4-on-medical-challenge","title":"Capabilities of GPT-4 on Medical Challenge Problems","date":"2023-03-20","arxiv_id":"2303.13375","n_code_links":1,"syntology":null},{"paper":"/paper/character-word-or-both-revisiting-the","slug":"character-word-or-both-revisiting-the","title":"Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models","date":"2023-03-20","arxiv_id":"2303.10893","n_code_links":1,"syntology":null},{"paper":"/paper/deid-gpt-zero-shot-medical-text-de","slug":"deid-gpt-zero-shot-medical-text-de","title":"DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4","date":"2023-03-20","arxiv_id":"2303.11032","n_code_links":1,"syntology":null},{"paper":"/paper/eva-02-a-visual-representation-for-neon","slug":"eva-02-a-visual-representation-for-neon","title":"EVA-02: A Visual Representation for Neon Genesis","date":"2023-03-20","arxiv_id":"2303.11331","n_code_links":6,"syntology":null},{"paper":"/paper/ff-former-swin-fourier-transformer-for","slug":"ff-former-swin-fourier-transformer-for","title":"FF-Former: Swin Fourier Transformer for Nighttime Flare Removal","date":"2023-03-20","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"mind-meets-machine-unravelling-gpt-4-s","title":"Mind meets machine: Unravelling GPT-4's cognitive psychology","date":"2023-03-20","arxiv_id":"2303.11436","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-task-transformer-with-relation","title":"Multi-task Transformer with Relation-attention and Type-attention for Named Entity Recognition","date":"2023-03-20","arxiv_id":"2303.10870","n_code_links":0,"syntology":null},{"paper":null,"slug":"pangu-s-towards-trillion-parameter-language","title":"PanGu-Σ: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing","date":"2023-03-20","arxiv_id":"2303.10845","n_code_links":0,"syntology":null},{"paper":"/paper/reflexion-language-agents-with-verbal","slug":"reflexion-language-agents-with-verbal","title":"Reflexion: Language Agents with Verbal Reinforcement Learning","date":"2023-03-20","arxiv_id":"2303.11366","n_code_links":5,"syntology":{"ran":8,"of":9,"n_ran_checked":6,"n_instrument":2,"unverified":1,"pointer_only":1,"phrase":"8 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; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["noahshinn024/reflexion"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":"/paper/revisiting-transformer-for-point-cloud-based","slug":"revisiting-transformer-for-point-cloud-based","title":"SGFormer: Semantic Graph Transformer for Point Cloud-based 3D Scene Graph Generation","date":"2023-03-20","arxiv_id":"2303.11048","n_code_links":1,"syntology":null},{"paper":"/paper/sparse-distributed-memory-is-a-continual","slug":"sparse-distributed-memory-is-a-continual","title":"Sparse Distributed Memory is a Continual Learner","date":"2023-03-20","arxiv_id":"2303.11934","n_code_links":1,"syntology":null},{"paper":"/paper/towards-better-3d-knowledge-transfer-via","slug":"towards-better-3d-knowledge-transfer-via","title":"GeoMIM: Towards Better 3D Knowledge Transfer via Masked Image Modeling for Multi-view 3D Understanding","date":"2023-03-20","arxiv_id":"2303.11325","n_code_links":1,"syntology":null},{"paper":"/paper/towards-end-to-end-generative-modeling-of","slug":"towards-end-to-end-generative-modeling-of","title":"Towards End-to-End Generative Modeling of Long Videos with Memory-Efficient Bidirectional Transformers","date":"2023-03-20","arxiv_id":"2303.11251","n_code_links":1,"syntology":null},{"paper":"/paper/bangla-grammatical-error-detection-using-t5","slug":"bangla-grammatical-error-detection-using-t5","title":"Bangla Grammatical Error Detection Using T5 Transformer Model","date":"2023-03-19","arxiv_id":"2303.10612","n_code_links":2,"syntology":null},{"paper":"/paper/ctran-cnn-transformer-based-network-for","slug":"ctran-cnn-transformer-based-network-for","title":"CTRAN: CNN-Transformer-based Network for Natural Language Understanding","date":"2023-03-19","arxiv_id":"2303.10606","n_code_links":1,"syntology":null},{"paper":"/paper/multiscale-audio-spectrogram-transformer-for","slug":"multiscale-audio-spectrogram-transformer-for","title":"Multiscale Audio Spectrogram Transformer for Efficient Audio Classification","date":"2023-03-19","arxiv_id":"2303.10757","n_code_links":0,"syntology":null},{"paper":null,"slug":"paco-provocation-involving-action-culture-and","title":"PACO: Provocation Involving Action, Culture, and Oppression","date":"2023-03-19","arxiv_id":"2303.12808","n_code_links":0,"syntology":null},{"paper":null,"slug":"spatial-temporal-transformer-for-affective","title":"Spatial-temporal Transformer for Affective Behavior Analysis","date":"2023-03-19","arxiv_id":"2303.10561","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comprehensive-capability-analysis-of-gpt-3","title":"A Comprehensive Capability Analysis of GPT-3 and GPT-3.5 Series Models","date":"2023-03-18","arxiv_id":"2303.10420","n_code_links":0,"syntology":null},{"paper":"/paper/an-empirical-study-of-pre-trained-language","slug":"an-empirical-study-of-pre-trained-language","title":"An Empirical Study of Pre-trained Language Models in Simple Knowledge Graph Question Answering","date":"2023-03-18","arxiv_id":"2303.10368","n_code_links":1,"syntology":null},{"paper":"/paper/channel-aware-distillation-transformer-for","slug":"channel-aware-distillation-transformer-for","title":"Channel-Aware Distillation Transformer for Depth Estimation on Nano Drones","date":"2023-03-18","arxiv_id":"2303.10386","n_code_links":1,"syntology":null},{"paper":"/paper/discovering-predictable-latent-factors-for","slug":"discovering-predictable-latent-factors-for","title":"Discovering Predictable Latent Factors for Time Series Forecasting","date":"2023-03-18","arxiv_id":"2303.10426","n_code_links":1,"syntology":null},{"paper":null,"slug":"mixing-backward-with-forward-chaining-for","title":"Mixing Backward- with Forward-Chaining for Metacognitive Skill Acquisition and Transfer","date":"2023-03-18","arxiv_id":"2303.12223","n_code_links":0,"syntology":null},{"paper":null,"slug":"noisyhate-benchmarking-content-moderation","title":"NoisyHate: Mining Online Human-Written Perturbations for Realistic Robustness Benchmarking of Content Moderation Models","date":"2023-03-18","arxiv_id":"2303.10430","n_code_links":0,"syntology":null},{"paper":null,"slug":"spdf-sparse-pre-training-and-dense-fine","title":"SPDF: Sparse Pre-training and Dense Fine-tuning for Large Language Models","date":"2023-03-18","arxiv_id":"2303.10464","n_code_links":0,"syntology":null},{"paper":"/paper/vision-transformer-based-model-for-severity","slug":"vision-transformer-based-model-for-severity","title":"Vision Transformer-based Model for Severity Quantification of Lung Pneumonia Using Chest X-ray Images","date":"2023-03-18","arxiv_id":"2303.11935","n_code_links":1,"syntology":null},{"paper":null,"slug":"cerviformer-a-pap-smear-based-cervical-cancer","title":"CerviFormer: A Pap-smear based cervical cancer classification method using cross attention and latent transformer","date":"2023-03-17","arxiv_id":"2303.10222","n_code_links":0,"syntology":null},{"paper":"/paper/colt5-faster-long-range-transformers-with","slug":"colt5-faster-long-range-transformers-with","title":"CoLT5: Faster Long-Range Transformers with Conditional Computation","date":"2023-03-17","arxiv_id":"2303.09752","n_code_links":0,"syntology":{"ran":5,"of":9,"n_ran_checked":5,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"5 ran (of which 0 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) · 4 unverified","official":null}},{"paper":"/paper/gadformer-an-attention-based-model-for-group","slug":"gadformer-an-attention-based-model-for-group","title":"GADformer: A Transparent Transformer Model for Group Anomaly Detection on Trajectories","date":"2023-03-17","arxiv_id":"2303.09841","n_code_links":1,"syntology":null},{"paper":null,"slug":"gnnformer-a-graph-based-framework-for","title":"GNNFormer: A Graph-based Framework for Cytopathology Report Generation","date":"2023-03-17","arxiv_id":"2303.09956","n_code_links":0,"syntology":null},{"paper":null,"slug":"gpts-are-gpts-an-early-look-at-the-labor","title":"GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models","date":"2023-03-17","arxiv_id":"2303.10130","n_code_links":0,"syntology":null},{"paper":null,"slug":"hdformer-a-higher-dimensional-transformer-for","title":"HDformer: A Higher Dimensional Transformer for Diabetes Detection Utilizing Long Range Vascular Signals","date":"2023-03-17","arxiv_id":"2303.11340","n_code_links":0,"syntology":null},{"paper":"/paper/lswinsr-uav-imagery-super-resolution-based-on","slug":"lswinsr-uav-imagery-super-resolution-based-on","title":"LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformer","date":"2023-03-17","arxiv_id":"2303.10232","n_code_links":1,"syntology":null},{"paper":null,"slug":"pedestrain-detection-for-low-light-vision","title":"Pedestrain detection for low-light vision proposal","date":"2023-03-17","arxiv_id":"2303.12725","n_code_links":0,"syntology":null},{"paper":"/paper/refinement-for-absolute-pose-regression-with","slug":"refinement-for-absolute-pose-regression-with","title":"Neural Refinement for Absolute Pose Regression with Feature Synthesis","date":"2023-03-17","arxiv_id":"2303.10087","n_code_links":1,"syntology":{"ran":17,"of":17,"n_ran_checked":17,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"17 ran (of which 0 constructed an object rather than computing a result; 17 with no instrument failure: 0 honoured, 0 violated, 17 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ActiveVisionLab/NeFeS"],"state":"official (archive's flag): 17 ran","n_ran":17,"n_constructed":0,"n_ran_no_instrument_failure":17,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"star-net-improving-single-image-desnowing","title":"Star-Net: Improving Single Image Desnowing Model With More Efficient Connection and Diverse Feature Interaction","date":"2023-03-17","arxiv_id":"2303.09988","n_code_links":0,"syntology":null},{"paper":"/paper/trained-on-100-million-words-and-still-in","slug":"trained-on-100-million-words-and-still-in","title":"Trained on 100 million words and still in shape: BERT meets British National Corpus","date":"2023-03-17","arxiv_id":"2303.09859","n_code_links":2,"syntology":{"ran":3,"of":7,"n_ran_checked":3,"n_instrument":0,"unverified":4,"pointer_only":7,"phrase":"3 ran (of which 3 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) · 4 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":{"repos":["ltgoslo/ltg-bert"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/a-framework-for-real-time-object-detection","slug":"a-framework-for-real-time-object-detection","title":"Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy","date":"2023-03-16","arxiv_id":"2303.09190","n_code_links":2,"syntology":null},{"paper":null,"slug":"block-wise-bit-compression-of-transformer","title":"Block-wise Bit-Compression of Transformer-based Models","date":"2023-03-16","arxiv_id":"2303.09184","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-generative-pre-trained-transformers-gpt","title":"Can Generative Pre-trained Transformers (GPT) Pass Assessments in Higher Education Programming Courses?","date":"2023-03-16","arxiv_id":"2303.09325","n_code_links":0,"syntology":null},{"paper":null,"slug":"emotional-reaction-intensity-estimation-based","title":"Emotional Reaction Intensity Estimation Based on Multimodal Data","date":"2023-03-16","arxiv_id":"2303.09167","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-distributional-shifts-in-large","title":"Exploring Distributional Shifts in Large Language Models for Code Analysis","date":"2023-03-16","arxiv_id":"2303.09128","n_code_links":0,"syntology":null},{"paper":null,"slug":"facial-affect-recognition-based-on","title":"Facial Affect Recognition based on Transformer Encoder and Audiovisual Fusion for the ABAW5 Challenge","date":"2023-03-16","arxiv_id":"2303.09158","n_code_links":0,"syntology":null},{"paper":"/paper/highly-accurate-quantum-chemical-property","slug":"highly-accurate-quantum-chemical-property","title":"Highly Accurate Quantum Chemical Property Prediction with Uni-Mol+","date":"2023-03-16","arxiv_id":"2303.16982","n_code_links":2,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":{"repos":["dptech-corp/Uni-Mol"],"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":"/paper/how-well-do-large-language-models-perform-in","slug":"how-well-do-large-language-models-perform-in","title":"How well do Large Language Models perform in Arithmetic tasks?","date":"2023-03-16","arxiv_id":"2304.02015","n_code_links":1,"syntology":null},{"paper":"/paper/hybrid-spectral-denoising-transformer-with","slug":"hybrid-spectral-denoising-transformer-with","title":"Hybrid Spectral Denoising Transformer with Guided Attention","date":"2023-03-16","arxiv_id":"2303.09040","n_code_links":1,"syntology":{"ran":1,"of":5,"n_ran_checked":1,"n_instrument":0,"unverified":4,"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) · 4 unverified","official":{"repos":["zeqiang-lai/hsdt"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"incrowdformer-on-ground-pedestrian-world","title":"InCrowdFormer: On-Ground Pedestrian World Model From Egocentric Views","date":"2023-03-16","arxiv_id":"2303.09534","n_code_links":0,"syntology":null},{"paper":null,"slug":"instance-conditioned-gan-data-augmentation","title":"Instance-Conditioned GAN Data Augmentation for Representation Learning","date":"2023-03-16","arxiv_id":"2303.09677","n_code_links":0,"syntology":null},{"paper":"/paper/jump-to-conclusions-short-cutting","slug":"jump-to-conclusions-short-cutting","title":"Jump to Conclusions: Short-Cutting Transformers With Linear Transformations","date":"2023-03-16","arxiv_id":"2303.09435","n_code_links":2,"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":["sashayd/mat"],"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":null,"slug":"measuring-improvement-of-f-1-scores-in","title":"Measuring Improvement of F$_1$-Scores in Detection of Self-Admitted Technical Debt","date":"2023-03-16","arxiv_id":"2303.09617","n_code_links":0,"syntology":null},{"paper":"/paper/predicting-human-attention-using","slug":"predicting-human-attention-using","title":"Unifying Top-down and Bottom-up Scanpath Prediction Using Transformers","date":"2023-03-16","arxiv_id":"2303.09383","n_code_links":1,"syntology":null},{"paper":"/paper/psvt-end-to-end-multi-person-3d-pose-and","slug":"psvt-end-to-end-multi-person-3d-pose-and","title":"PSVT: End-to-End Multi-person 3D Pose and Shape Estimation with Progressive Video Transformers","date":"2023-03-16","arxiv_id":"2303.09187","n_code_links":0,"syntology":null},{"paper":"/paper/rehearsal-free-domain-continual-face-anti","slug":"rehearsal-free-domain-continual-face-anti","title":"Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Less","date":"2023-03-16","arxiv_id":"2303.09914","n_code_links":0,"syntology":{"ran":4,"of":5,"n_ran_checked":4,"n_instrument":0,"unverified":1,"pointer_only":5,"phrase":"4 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; 0 where Syntology's instrument failed) · 1 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","official":null}},{"paper":"/paper/smartbert-a-promotion-of-dynamic-early","slug":"smartbert-a-promotion-of-dynamic-early","title":"SmartBERT: A Promotion of Dynamic Early Exiting Mechanism for Accelerating BERT Inference","date":"2023-03-16","arxiv_id":"2303.09266","n_code_links":0,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"3 ran (of which 3 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; every one of the 3 samples that ran constructed an object rather than computing a result","official":null}},{"paper":"/paper/steering-prototype-with-prompt-tuning-for","slug":"steering-prototype-with-prompt-tuning-for","title":"Steering Prototypes with Prompt-tuning for Rehearsal-free Continual Learning","date":"2023-03-16","arxiv_id":"2303.09447","n_code_links":2,"syntology":{"ran":4,"of":4,"n_ran_checked":1,"n_instrument":3,"unverified":0,"pointer_only":1,"phrase":"4 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; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["lzvv123456/contrastive-prototypical-prompt","lzvv123456/steering-prototypes-with-prompt-tuning-for-rehearsal-free-continual-learning"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/taming-diffusion-models-for-audio-driven-co","slug":"taming-diffusion-models-for-audio-driven-co","title":"Taming Diffusion Models for Audio-Driven Co-Speech Gesture Generation","date":"2023-03-16","arxiv_id":"2303.09119","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-the-scalable-evaluation-of","title":"Towards the Scalable Evaluation of Cooperativeness in Language Models","date":"2023-03-16","arxiv_id":"2303.13360","n_code_links":0,"syntology":null},{"paper":null,"slug":"translating-radiology-reports-into-plain","title":"Translating Radiology Reports into Plain Language using ChatGPT and GPT-4 with Prompt Learning: Promising Results, Limitations, and Potential","date":"2023-03-16","arxiv_id":"2303.09038","n_code_links":0,"syntology":null},{"paper":"/paper/typet5-seq2seq-type-inference-using-static","slug":"typet5-seq2seq-type-inference-using-static","title":"TypeT5: Seq2seq Type Inference using Static Analysis","date":"2023-03-16","arxiv_id":"2303.09564","n_code_links":1,"syntology":{"ran":4,"of":7,"n_ran_checked":4,"n_instrument":0,"unverified":3,"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) · 3 unverified","official":{"repos":["utopia-group/typet5"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"automated-interactive-domain-specific","title":"Automated Interactive Domain-Specific Conversational Agents that Understand Human Dialogs","date":"2023-03-15","arxiv_id":"2303.08941","n_code_links":0,"syntology":null},{"paper":"/paper/continuous-emotion-recognition-based-on-tcn","slug":"continuous-emotion-recognition-based-on-tcn","title":"Leveraging TCN and Transformer for effective visual-audio fusion in continuous emotion recognition","date":"2023-03-15","arxiv_id":"2303.08356","n_code_links":1,"syntology":null},{"paper":"/paper/deepmim-deep-supervision-for-masked-image","slug":"deepmim-deep-supervision-for-masked-image","title":"DeepMIM: Deep Supervision for Masked Image Modeling","date":"2023-03-15","arxiv_id":"2303.08817","n_code_links":1,"syntology":null},{"paper":null,"slug":"efficient-uncertainty-estimation-with","title":"Efficient Uncertainty Estimation with Gaussian Process for Reliable Dialog Response Retrieval","date":"2023-03-15","arxiv_id":"2303.08599","n_code_links":0,"syntology":null},{"paper":"/paper/fastinst-a-simple-query-based-model-for-real","slug":"fastinst-a-simple-query-based-model-for-real","title":"FastInst: A Simple Query-Based Model for Real-Time Instance Segmentation","date":"2023-03-15","arxiv_id":"2303.08594","n_code_links":1,"syntology":{"ran":8,"of":9,"n_ran_checked":8,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["junjiehe96/fastinst"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}}],"record_sha256":"6f51f079178b9ee8bce9e9d6ecec77aca0910d511bd509da8f91b00ee2f76da5","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}