{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/dense-connections/papers/156","list_of":"/method/dense-connections","method":"Dense Connections","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":156,"pages_in_order":293,"rows_per_page":100,"rows":[15501,15600],"of":29230,"counts":{"archive_papers_tagged":29230,"with_a_code_link":12972,"where_syntology_ran_a_sample":3929,"not_listed_spam_title":0,"listed":29230,"listed_where_code_ran":3929,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3303,"every_run_a_failure_of_syntologys_instrument":626,"listed_with_a_run_with_no_instrument_failure":3303,"listed_every_run_a_failure_of_syntologys_instrument":626,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/dense-connections","prev":"/method/dense-connections/papers/155","next":"/method/dense-connections/papers/157","papers":[{"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":"mt-snn-enhance-spiking-neural-network-with","title":"MT-SNN: Enhance Spiking Neural Network with Multiple Thresholds","date":"2023-03-20","arxiv_id":"2303.11127","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":null,"slug":"picture-that-sketch-photorealistic-image","title":"Picture that Sketch: Photorealistic Image Generation from Abstract Sketches","date":"2023-03-20","arxiv_id":"2303.11162","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":"/paper/transfer-learning-method-in-the-problem-of","slug":"transfer-learning-method-in-the-problem-of","title":"Transfer learning method in the problem of binary classification of chest X-rays","date":"2023-03-19","arxiv_id":"2303.10601","n_code_links":1,"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":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":"conditional-synthetic-food-image-generation","title":"Conditional Synthetic Food Image Generation","date":"2023-03-16","arxiv_id":"2303.09005","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":"end-to-end-learning-based-wireless-image","title":"End-to-End Learning-Based Wireless Image Recognition Using the PyramidNet in Edge Intelligence","date":"2023-03-16","arxiv_id":"2303.09188","n_code_links":0,"syntology":null},{"paper":null,"slug":"energy-management-of-multi-mode-plug-in","title":"Energy Management of Multi-mode Plug-in Hybrid Electric Vehicle using Multi-agent Deep Reinforcement Learning","date":"2023-03-16","arxiv_id":"2303.09658","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":"/paper/ldmvfi-video-frame-interpolation-with-latent","slug":"ldmvfi-video-frame-interpolation-with-latent","title":"LDMVFI: Video Frame Interpolation with Latent Diffusion Models","date":"2023-03-16","arxiv_id":"2303.09508","n_code_links":2,"syntology":{"ran":8,"of":11,"n_ran_checked":7,"n_instrument":1,"unverified":3,"pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 2 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["danielism97/ldmvfi","danier97/ldmvfi"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"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":null,"slug":"self-inspection-method-of-unmanned-aerial","title":"Self-Inspection Method of Unmanned Aerial Vehicles in Power Plants Using Deep Q-Network Reinforcement Learning","date":"2023-03-16","arxiv_id":"2303.09013","n_code_links":0,"syntology":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"]}}},{"paper":null,"slug":"gcre-gpt-a-generative-model-for-comparative","title":"GCRE-GPT: A Generative Model for Comparative Relation Extraction","date":"2023-03-15","arxiv_id":"2303.08601","n_code_links":0,"syntology":null},{"paper":"/paper/gpt-4-technical-report-1","slug":"gpt-4-technical-report-1","title":"GPT-4 Technical Report","date":"2023-03-15","arxiv_id":"2303.08774","n_code_links":11,"syntology":{"ran":5,"of":5,"n_ran_checked":5,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 2 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["openai/evals"],"state":"community repositories only","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed"]}}},{"paper":null,"slug":"implicit-ray-transformers-for-multi-view","title":"Implicit Ray-Transformers for Multi-view Remote Sensing Image Segmentation","date":"2023-03-15","arxiv_id":"2303.08401","n_code_links":0,"syntology":null},{"paper":"/paper/lep-ad-language-embedding-of-proteins-and","slug":"lep-ad-language-embedding-of-proteins-and","title":"LEP-AD: Language Embedding of Proteins and Attention to Drugs predicts drug target interactions","date":"2023-03-15","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-exposure-hdr-composition-by-gated-swin","title":"Multi-Exposure HDR Composition by Gated Swin Transformer","date":"2023-03-15","arxiv_id":"2303.08704","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-modal-facial-expression-recognition","title":"Multi Modal Facial Expression Recognition with Transformer-Based Fusion Networks and Dynamic Sampling","date":"2023-03-15","arxiv_id":"2303.08419","n_code_links":0,"syntology":null},{"paper":"/paper/presto-a-multilingual-dataset-for-parsing","slug":"presto-a-multilingual-dataset-for-parsing","title":"PRESTO: A Multilingual Dataset for Parsing Realistic Task-Oriented Dialogs","date":"2023-03-15","arxiv_id":"2303.08954","n_code_links":1,"syntology":null},{"paper":null,"slug":"query-guided-attention-in-vision-transformers","title":"Query-guided Attention in Vision Transformers for Localizing Objects Using a Single Sketch","date":"2023-03-15","arxiv_id":"2303.08784","n_code_links":0,"syntology":null},{"paper":"/paper/reinforce-data-multiply-impact-improved-model","slug":"reinforce-data-multiply-impact-improved-model","title":"Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement","date":"2023-03-15","arxiv_id":"2303.08983","n_code_links":1,"syntology":null},{"paper":"/paper/selfcheckgpt-zero-resource-black-box","slug":"selfcheckgpt-zero-resource-black-box","title":"SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Models","date":"2023-03-15","arxiv_id":"2303.08896","n_code_links":1,"syntology":{"ran":6,"of":11,"n_ran_checked":3,"n_instrument":3,"unverified":5,"pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 5 unverified","official":{"repos":["potsawee/selfcheckgpt"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":"/paper/spatialformer-semantic-and-target-aware","slug":"spatialformer-semantic-and-target-aware","title":"SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning","date":"2023-03-15","arxiv_id":"2303.09281","n_code_links":1,"syntology":null},{"paper":"/paper/vddt-improving-vessel-detection-with","slug":"vddt-improving-vessel-detection-with","title":"VDDT: Improving Vessel Detection with Deformable Transfomer","date":"2023-03-15","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"do-transformers-parse-while-predicting-the","title":"Do Transformers Parse while Predicting the Masked Word?","date":"2023-03-14","arxiv_id":"2303.08117","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficiently-training-vision-transformers-on","title":"Efficiently Training Vision Transformers on Structural MRI Scans for Alzheimer's Disease Detection","date":"2023-03-14","arxiv_id":"2303.08216","n_code_links":0,"syntology":null},{"paper":"/paper/evaluation-of-chatgpt-as-a-question-answering","slug":"evaluation-of-chatgpt-as-a-question-answering","title":"Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM Family","date":"2023-03-14","arxiv_id":"2303.07992","n_code_links":2,"syntology":null},{"paper":null,"slug":"features-matching-using-natural-language","title":"Features matching using natural language processing","date":"2023-03-14","arxiv_id":"2303.12804","n_code_links":0,"syntology":null},{"paper":null,"slug":"finding-the-needle-in-a-haystack-unsupervised","title":"Finding the Needle in a Haystack: Unsupervised Rationale Extraction from Long Text Classifiers","date":"2023-03-14","arxiv_id":"2303.07991","n_code_links":0,"syntology":null},{"paper":null,"slug":"fptn-fast-pure-transformer-network-for","title":"FPTN: Fast Pure Transformer Network for Traffic Flow Forecasting","date":"2023-03-14","arxiv_id":"2303.07685","n_code_links":0,"syntology":null},{"paper":null,"slug":"geospark-sparking-up-point-cloud-segmentation","title":"GeoSpark: Sparking up Point Cloud Segmentation with Geometry Clue","date":"2023-03-14","arxiv_id":"2303.08274","n_code_links":0,"syntology":null},{"paper":null,"slug":"graph-transformer-gans-for-graph-constrained","title":"Graph Transformer GANs for Graph-Constrained House Generation","date":"2023-03-14","arxiv_id":"2303.08225","n_code_links":0,"syntology":null},{"paper":"/paper/i3d-transformer-architectures-with-input","slug":"i3d-transformer-architectures-with-input","title":"I3D: Transformer architectures with input-dependent dynamic depth for speech recognition","date":"2023-03-14","arxiv_id":"2303.07624","n_code_links":1,"syntology":null},{"paper":"/paper/implant-global-and-local-hierarchy","slug":"implant-global-and-local-hierarchy","title":"Implant Global and Local Hierarchy Information to Sequence based Code Representation Models","date":"2023-03-14","arxiv_id":"2303.07826","n_code_links":1,"syntology":null},{"paper":null,"slug":"medbert-de-a-comprehensive-german-bert-model","title":"MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain","date":"2023-03-14","arxiv_id":"2303.08179","n_code_links":0,"syntology":null},{"paper":"/paper/neuro-symbolic-commonsense-social-reasoning","slug":"neuro-symbolic-commonsense-social-reasoning","title":"Neuro-symbolic Commonsense Social Reasoning","date":"2023-03-14","arxiv_id":"2303.08264","n_code_links":3,"syntology":null},{"paper":null,"slug":"precise-facial-landmark-detection-by","title":"Precise Facial Landmark Detection by Reference Heatmap Transformer","date":"2023-03-14","arxiv_id":"2303.07840","n_code_links":0,"syntology":null},{"paper":"/paper/quaternion-orthogonal-transformer-for-facial","slug":"quaternion-orthogonal-transformer-for-facial","title":"Quaternion Orthogonal Transformer for Facial Expression Recognition in the Wild","date":"2023-03-14","arxiv_id":"2303.07831","n_code_links":1,"syntology":null},{"paper":"/paper/r-2-range-regularization-for-model","slug":"r-2-range-regularization-for-model","title":"R2 Loss: Range Restriction Loss for Model Compression and Quantization","date":"2023-03-14","arxiv_id":"2303.08253","n_code_links":0,"syntology":null},{"paper":null,"slug":"re-move-an-adaptive-policy-design-approach","title":"RE-MOVE: An Adaptive Policy Design for Robotic Navigation Tasks in Dynamic Environments via Language-Based Feedback","date":"2023-03-14","arxiv_id":"2303.07622","n_code_links":0,"syntology":null},{"paper":null,"slug":"recovering-arrhythmic-eeg-transients-from","title":"Recovering Arrhythmic EEG Transients from Their Stochastic Interference","date":"2023-03-14","arxiv_id":"2303.07683","n_code_links":0,"syntology":null},{"paper":"/paper/rotation-invariant-transformer-for-point","slug":"rotation-invariant-transformer-for-point","title":"Rotation-Invariant Transformer for Point Cloud Matching","date":"2023-03-14","arxiv_id":"2303.08231","n_code_links":1,"syntology":{"ran":9,"of":10,"n_ran_checked":8,"n_instrument":1,"unverified":1,"pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["haoyu94/roitr"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"towards-real-time-single-channel-speech","title":"Towards Real-Time Single-Channel Speech Separation in Noisy and Reverberant Environments","date":"2023-03-14","arxiv_id":"2303.07569","n_code_links":0,"syntology":null},{"paper":"/paper/amom-adaptive-masking-over-masking-for","slug":"amom-adaptive-masking-over-masking-for","title":"AMOM: Adaptive Masking over Masking for Conditional Masked Language Model","date":"2023-03-13","arxiv_id":"2303.07457","n_code_links":1,"syntology":null}],"record_sha256":"c541cbe72c5b99323aacac196aa0c6562b6ce5a8cfc0f635f8f8e38576a3f69d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}