{"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/focus/papers/138","list_of":"/method/focus","method":"Focus","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":138,"pages_in_order":154,"rows_per_page":100,"rows":[13701,13800],"of":15340,"counts":{"archive_papers_tagged":15340,"with_a_code_link":5193,"where_syntology_ran_a_sample":1419,"not_listed_spam_title":0,"listed":15340,"listed_where_code_ran":1419,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1210,"every_run_a_failure_of_syntologys_instrument":209,"listed_with_a_run_with_no_instrument_failure":1210,"listed_every_run_a_failure_of_syntologys_instrument":209,"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/focus","prev":"/method/focus/papers/137","next":"/method/focus/papers/139","papers":[{"paper":null,"slug":"real-time-non-invasive-imaging-and-detection","title":"Real-Time Non-Invasive Imaging and Detection of Spreading Depolarizations through EEG: An Ultra-Light Explainable Deep Learning Approach","date":"2023-09-06","arxiv_id":"2309.03147","n_code_links":0,"syntology":null},{"paper":null,"slug":"risk-reducing-design-and-operations-toolkit","title":"On strategies for risk management and decision making under uncertainty shared across multiple fields","date":"2023-09-06","arxiv_id":"2309.03133","n_code_links":0,"syntology":null},{"paper":"/paper/seal-a-framework-for-systematic-evaluation-of","slug":"seal-a-framework-for-systematic-evaluation-of","title":"SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution","date":"2023-09-06","arxiv_id":"2309.03020","n_code_links":1,"syntology":{"ran":20,"of":23,"n_ran_checked":18,"n_instrument":2,"unverified":3,"pointer_only":23,"phrase":"20 ran (of which 0 constructed an object rather than computing a result; 18 with no instrument failure: 0 honoured, 1 violated, 17 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["xpixelgroup/seal"],"state":"official (archive's flag): 20 ran","n_ran":20,"n_constructed":0,"n_ran_no_instrument_failure":18,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"viewmix-augmentation-for-robust","title":"ViewMix: Augmentation for Robust Representation in Self-Supervised Learning","date":"2023-09-06","arxiv_id":"2309.03360","n_code_links":0,"syntology":null},{"paper":null,"slug":"advanced-underwater-image-restoration-in","title":"Advanced Underwater Image Restoration in Complex Illumination Conditions","date":"2023-09-05","arxiv_id":"2309.02217","n_code_links":0,"syntology":null},{"paper":"/paper/an-efficient-approach-to-unsupervised-out-of","slug":"an-efficient-approach-to-unsupervised-out-of","title":"Unsupervised Out-of-Distribution Detection by Restoring Lossy Inputs with Variational Autoencoder","date":"2023-09-05","arxiv_id":"2309.02084","n_code_links":1,"syntology":null},{"paper":null,"slug":"bigfuse-global-context-aware-image-fusion-in","title":"BigFUSE: Global Context-Aware Image Fusion in Dual-View Light-Sheet Fluorescence Microscopy with Image Formation Prior","date":"2023-09-05","arxiv_id":"2309.01865","n_code_links":0,"syntology":null},{"paper":null,"slug":"dual-relation-alignment-for-composed-image","title":"Dual Relation Alignment for Composed Image Retrieval","date":"2023-09-05","arxiv_id":"2309.02169","n_code_links":0,"syntology":null},{"paper":"/paper/granger-causal-inference-in-multivariate","slug":"granger-causal-inference-in-multivariate","title":"Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length","date":"2023-09-05","arxiv_id":"2309.02027","n_code_links":1,"syntology":null},{"paper":null,"slug":"neurosymbolic-meta-reinforcement-lookahead","title":"Neurosymbolic Meta-Reinforcement Lookahead Learning Achieves Safe Self-Driving in Non-Stationary Environments","date":"2023-09-05","arxiv_id":"2309.02328","n_code_links":0,"syntology":null},{"paper":null,"slug":"projections-of-economic-impacts-of-climate","title":"Projections of Economic Impacts of Climate Change on Marine Protected Areas: Palau, the Great Barrier Reef, and the Bering Sea","date":"2023-09-05","arxiv_id":"2309.02323","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-communications-based-on-adaptive","title":"Semantic Communications Based on Adaptive Generative Models and Information Bottleneck","date":"2023-09-05","arxiv_id":"2309.02387","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-impact-of-artificial-intelligence-on-the","title":"The Impact of Artificial Intelligence on the Evolution of Digital Education: A Comparative Study of OpenAI Text Generation Tools including ChatGPT, Bing Chat, Bard, and Ernie","date":"2023-09-05","arxiv_id":"2309.02029","n_code_links":0,"syntology":null},{"paper":null,"slug":"traffic-light-recognition-using-convolutional","title":"Traffic Light Recognition using Convolutional Neural Networks: A Survey","date":"2023-09-05","arxiv_id":"2309.02158","n_code_links":0,"syntology":null},{"paper":"/paper/adapting-segment-anything-model-for-change","slug":"adapting-segment-anything-model-for-change","title":"Adapting Segment Anything Model for Change Detection in HR Remote Sensing Images","date":"2023-09-04","arxiv_id":"2309.01429","n_code_links":1,"syntology":{"ran":14,"of":15,"n_ran_checked":12,"n_instrument":2,"unverified":1,"pointer_only":15,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ggsding/sam-cd"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"badsqa-stealthy-backdoor-attacks-using","title":"EventTrojan: Manipulating Non-Intrusive Speech Quality Assessment via Imperceptible Events","date":"2023-09-04","arxiv_id":"2309.01480","n_code_links":0,"syntology":null},{"paper":"/paper/dat-spatially-dynamic-vision-transformer-with","slug":"dat-spatially-dynamic-vision-transformer-with","title":"DAT++: Spatially Dynamic Vision Transformer with Deformable Attention","date":"2023-09-04","arxiv_id":"2309.01430","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":8,"n_instrument":0,"unverified":2,"pointer_only":6,"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) · 2 unverified","official":{"repos":["leaplabthu/dat"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/efficient-computation-of-predictive","slug":"efficient-computation-of-predictive","title":"Efficient computation of predictive probabilities in probit models via expectation propagation","date":"2023-09-04","arxiv_id":"2309.01630","n_code_links":1,"syntology":null},{"paper":"/paper/efficient-expectation-propagation-for","slug":"efficient-expectation-propagation-for","title":"Efficient expectation propagation for posterior approximation in high-dimensional probit models","date":"2023-09-04","arxiv_id":"2309.01619","n_code_links":1,"syntology":null},{"paper":"/paper/evolving-linguistic-divergence-on-polarizing","slug":"evolving-linguistic-divergence-on-polarizing","title":"Evolving linguistic divergence on polarizing social media","date":"2023-09-04","arxiv_id":"2309.01659","n_code_links":1,"syntology":null},{"paper":null,"slug":"interdisciplinary-fairness-in-imbalanced","title":"Interdisciplinary Fairness in Imbalanced Research Proposal Topic Inference: A Hierarchical Transformer-based Method with Selective Interpolation","date":"2023-09-04","arxiv_id":"2309.01717","n_code_links":0,"syntology":null},{"paper":null,"slug":"les-houches-lectures-on-deep-learning-at","title":"Les Houches Lectures on Deep Learning at Large & Infinite Width","date":"2023-09-04","arxiv_id":"2309.01592","n_code_links":0,"syntology":null},{"paper":null,"slug":"leveraging-self-supervised-vision","title":"Leveraging Self-Supervised Vision Transformers for Segmentation-based Transfer Function Design","date":"2023-09-04","arxiv_id":"2309.01408","n_code_links":0,"syntology":null},{"paper":null,"slug":"lora-like-calibration-for-multimodal","title":"LoRA-like Calibration for Multimodal Deception Detection using ATSFace Data","date":"2023-09-04","arxiv_id":"2309.01383","n_code_links":0,"syntology":null},{"paper":null,"slug":"metric-learning-for-projections-bias-of","title":"Bridging the Projection Gap: Overcoming Projection Bias Through Parameterized Distance Learning","date":"2023-09-04","arxiv_id":"2309.01390","n_code_links":0,"syntology":null},{"paper":null,"slug":"mitigation-of-stop-and-go-traffic-waves-with","title":"Mitigation of stop-and-go traffic waves with intelligent vehicles at low market penetration rates","date":"2023-09-04","arxiv_id":"2309.01834","n_code_links":0,"syntology":null},{"paper":"/paper/parameter-and-computation-efficient-transfer-1","slug":"parameter-and-computation-efficient-transfer-1","title":"Parameter and Computation Efficient Transfer Learning for Vision-Language Pre-trained Models","date":"2023-09-04","arxiv_id":"2309.01479","n_code_links":1,"syntology":null},{"paper":null,"slug":"segmentation-of-3d-pore-space-from-ct-images","title":"Segmentation of 3D pore space from CT images using curvilinear skeleton: application to numerical simulation of microbial decomposition","date":"2023-09-04","arxiv_id":"2309.01611","n_code_links":0,"syntology":null},{"paper":null,"slug":"skope3d-a-synthetic-dataset-for-vehicle","title":"SKoPe3D: A Synthetic Dataset for Vehicle Keypoint Perception in 3D from Traffic Monitoring Cameras","date":"2023-09-04","arxiv_id":"2309.01324","n_code_links":0,"syntology":null},{"paper":null,"slug":"mapping-ai-arguments-in-journalism-studies","title":"Mapping AI Arguments in Journalism Studies","date":"2023-09-03","arxiv_id":"2309.12357","n_code_links":0,"syntology":null},{"paper":"/paper/mila-memory-based-instance-level-adaptation-1","slug":"mila-memory-based-instance-level-adaptation-1","title":"MILA: Memory-Based Instance-Level Adaptation for Cross-Domain Object Detection","date":"2023-09-03","arxiv_id":"2309.01086","n_code_links":1,"syntology":null},{"paper":"/paper/tropical-geometric-tools-for-machine-learning","slug":"tropical-geometric-tools-for-machine-learning","title":"Tropical Geometric Tools for Machine Learning: the TML package","date":"2023-09-03","arxiv_id":"2309.01082","n_code_links":1,"syntology":null},{"paper":"/paper/a-3d-explainability-framework-to-uncover","slug":"a-3d-explainability-framework-to-uncover","title":"An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognition","date":"2023-09-02","arxiv_id":"2309.00903","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":5,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["ece7048/3dsulci"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/attt2m-text-driven-human-motion-generation-1","slug":"attt2m-text-driven-human-motion-generation-1","title":"AttT2M: Text-Driven Human Motion Generation with Multi-Perspective Attention Mechanism","date":"2023-09-02","arxiv_id":"2309.00796","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["zcymonkey/attt2m"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/fastposegait-a-toolbox-and-benchmark-for","slug":"fastposegait-a-toolbox-and-benchmark-for","title":"FastPoseGait: A Toolbox and Benchmark for Efficient Pose-based Gait Recognition","date":"2023-09-02","arxiv_id":"2309.00794","n_code_links":1,"syntology":null},{"paper":"/paper/from-specific-to-generic-learned-sorted-set","slug":"from-specific-to-generic-learned-sorted-set","title":"From Specific to Generic Learned Sorted Set Dictionaries: A Theoretically Sound Paradigm Yelding Competitive Data Structural Boosters in Practice","date":"2023-09-02","arxiv_id":"2309.00946","n_code_links":1,"syntology":null},{"paper":"/paper/multi-scale-data-driven-and-anatomically","slug":"multi-scale-data-driven-and-anatomically","title":"Multi-scale, Data-driven and Anatomically Constrained Deep Learning Image Registration for Adult and Fetal Echocardiography","date":"2023-09-02","arxiv_id":"2309.00831","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-scoping-review-of-mathematical-models-of","title":"Mathematical models of Plasmodium vivax transmission: a scoping review","date":"2023-09-01","arxiv_id":"2309.00274","n_code_links":0,"syntology":null},{"paper":null,"slug":"asymmetric-double-winged-multi-view","title":"Asymmetric double-winged multi-view clustering network for exploring Diverse and Consistent Information","date":"2023-09-01","arxiv_id":"2309.00474","n_code_links":0,"syntology":null},{"paper":"/paper/copiloting-the-copilots-fusing-large-language","slug":"copiloting-the-copilots-fusing-large-language","title":"Copiloting the Copilots: Fusing Large Language Models with Completion Engines for Automated Program Repair","date":"2023-09-01","arxiv_id":"2309.00608","n_code_links":1,"syntology":{"ran":7,"of":7,"n_ran_checked":7,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"7 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; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ise-uiuc/Repilot"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"cpsp-learning-speech-concepts-from-phoneme","title":"Learning Speech Representation From Contrastive Token-Acoustic Pretraining","date":"2023-09-01","arxiv_id":"2309.00424","n_code_links":0,"syntology":null},{"paper":"/paper/explainable-active-learning-for-preference","slug":"explainable-active-learning-for-preference","title":"Explainable Active Learning for Preference Elicitation","date":"2023-09-01","arxiv_id":"2309.00356","n_code_links":1,"syntology":null},{"paper":null,"slug":"human-trajectory-prediction-using-lstm-with","title":"Human trajectory prediction using LSTM with Attention mechanism","date":"2023-09-01","arxiv_id":"2309.00331","n_code_links":0,"syntology":null},{"paper":"/paper/image-hijacking-adversarial-images-can","slug":"image-hijacking-adversarial-images-can","title":"Image Hijacks: Adversarial Images can Control Generative Models at Runtime","date":"2023-09-01","arxiv_id":"2309.00236","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":5,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["euanong/image-hijacks"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"rignet-efficient-repetitive-image-guided","title":"RigNet++: Semantic Assisted Repetitive Image Guided Network for Depth Completion","date":"2023-09-01","arxiv_id":"2309.00655","n_code_links":0,"syntology":null},{"paper":null,"slug":"videogen-a-reference-guided-latent-diffusion","title":"VideoGen: A Reference-Guided Latent Diffusion Approach for High Definition Text-to-Video Generation","date":"2023-09-01","arxiv_id":"2309.00398","n_code_links":0,"syntology":null},{"paper":null,"slug":"what-makes-good-open-vocabulary-detector-a","title":"What Makes Good Open-Vocabulary Detector: A Disassembling Perspective","date":"2023-09-01","arxiv_id":"2309.00227","n_code_links":0,"syntology":null},{"paper":null,"slug":"when-do-discourse-markers-affect","title":"When Do Discourse Markers Affect Computational Sentence Understanding?","date":"2023-09-01","arxiv_id":"2309.00368","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-stochastic-block-model-for-community","title":"A stochastic block model for community detection in attributed networks","date":"2023-08-31","arxiv_id":"2308.16382","n_code_links":0,"syntology":null},{"paper":null,"slug":"boosting-and-or-based-computational-protein","title":"Boosting AND/OR-Based Computational Protein Design: Dynamic Heuristics and Generalizable UFO","date":"2023-08-31","arxiv_id":"2309.00408","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-programming-languages-boost-each-other","title":"Can Programming Languages Boost Each Other via Instruction Tuning?","date":"2023-08-31","arxiv_id":"2308.16824","n_code_links":0,"syntology":null},{"paper":null,"slug":"distraction-free-embeddings-for-robust-vqa","title":"Distraction-free Embeddings for Robust VQA","date":"2023-08-31","arxiv_id":"2309.00133","n_code_links":0,"syntology":null},{"paper":null,"slug":"ethical-framework-for-harnessing-the-power-of","title":"Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond","date":"2023-08-31","arxiv_id":"2309.00064","n_code_links":0,"syntology":null},{"paper":null,"slug":"fault-injection-and-safe-error-attack-for","title":"Fault Injection and Safe-Error Attack for Extraction of Embedded Neural Network Models","date":"2023-08-31","arxiv_id":"2308.16703","n_code_links":0,"syntology":null},{"paper":null,"slug":"fuzzy-approach-for-audio-video-emotion","title":"Fuzzy Approach for Audio-Video Emotion Recognition in Computer Games for Children","date":"2023-08-31","arxiv_id":"2309.00138","n_code_links":0,"syntology":null},{"paper":null,"slug":"generalised-winograd-schema-and-its","title":"Generalised Winograd Schema and its Contextuality","date":"2023-08-31","arxiv_id":"2308.16498","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-mandarin-prosodic-structure","title":"Improving Mandarin Prosodic Structure Prediction with Multi-level Contextual Information","date":"2023-08-31","arxiv_id":"2308.16577","n_code_links":0,"syntology":null},{"paper":"/paper/language-conditioned-path-planning","slug":"language-conditioned-path-planning","title":"Language-Conditioned Path Planning","date":"2023-08-31","arxiv_id":"2308.16893","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-with-multi-modal-gradient-attention","title":"Learning with Multi-modal Gradient Attention for Explainable Composed Image Retrieval","date":"2023-08-31","arxiv_id":"2308.16649","n_code_links":0,"syntology":null},{"paper":null,"slug":"mfr-net-multi-faceted-responsive-listening","title":"MFR-Net: Multi-faceted Responsive Listening Head Generation via Denoising Diffusion Model","date":"2023-08-31","arxiv_id":"2308.16635","n_code_links":0,"syntology":null},{"paper":null,"slug":"precision-enhancement-of-distribution-system","title":"Precision Enhancement of Distribution System State Estimation via Tri-Objective Micro Phasor Measurement Unit Deployment","date":"2023-08-31","arxiv_id":"2309.00055","n_code_links":0,"syntology":null},{"paper":null,"slug":"privacy-preserving-machine-learning-for-4","title":"Privacy Preserving Machine Learning for Behavioral Authentication Systems","date":"2023-08-31","arxiv_id":"2309.13046","n_code_links":0,"syntology":null},{"paper":"/paper/ref-diff-zero-shot-referring-image","slug":"ref-diff-zero-shot-referring-image","title":"Ref-Diff: Zero-shot Referring Image Segmentation with Generative Models","date":"2023-08-31","arxiv_id":"2308.16777","n_code_links":1,"syntology":null},{"paper":"/paper/separate-and-locate-rethink-the-text-in-text","slug":"separate-and-locate-rethink-the-text-in-text","title":"Separate and Locate: Rethink the Text in Text-based Visual Question Answering","date":"2023-08-31","arxiv_id":"2308.16383","n_code_links":1,"syntology":null},{"paper":"/paper/touchstone-evaluating-vision-language-models","slug":"touchstone-evaluating-vision-language-models","title":"TouchStone: Evaluating Vision-Language Models by Language Models","date":"2023-08-31","arxiv_id":"2308.16890","n_code_links":1,"syntology":null},{"paper":"/paper/unsupervised-recognition-of-unknown-objects","slug":"unsupervised-recognition-of-unknown-objects","title":"Unsupervised Recognition of Unknown Objects for Open-World Object Detection","date":"2023-08-31","arxiv_id":"2308.16527","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":["frh23333/mepu-owod"],"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":"using-large-language-models-to-automate","title":"Using Large Language Models to Automate Category and Trend Analysis of Scientific Articles: An Application in Ophthalmology","date":"2023-08-31","arxiv_id":"2308.16688","n_code_links":0,"syntology":null},{"paper":null,"slug":"vilta-enhancing-vision-language-pre-training","title":"ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation","date":"2023-08-31","arxiv_id":"2308.16689","n_code_links":0,"syntology":null},{"paper":"/paper/a-recycling-training-strategy-for-medical","slug":"a-recycling-training-strategy-for-medical","title":"A Recycling Training Strategy for Medical Image Segmentation with Diffusion Denoising Models","date":"2023-08-30","arxiv_id":"2308.16355","n_code_links":1,"syntology":null},{"paper":null,"slug":"analyzing-character-and-consciousness-in-ai","title":"Analyzing Character and Consciousness in AI-Generated Social Content: A Case Study of Chirper, the AI Social Network","date":"2023-08-30","arxiv_id":"2309.08614","n_code_links":0,"syntology":null},{"paper":null,"slug":"assessing-drivers-situation-awareness-in-semi","title":"Assessing Drivers' Situation Awareness in Semi-Autonomous Vehicles: ASP based Characterisations of Driving Dynamics for Modelling Scene Interpretation and Projection","date":"2023-08-30","arxiv_id":"2308.15895","n_code_links":0,"syntology":null},{"paper":"/paper/b2c-afm-bi-directional-co-temporal-and-cross","slug":"b2c-afm-bi-directional-co-temporal-and-cross","title":"B2C-AFM: Bi-Directional Co-Temporal and Cross-Spatial Attention Fusion Model for Human Action Recognition","date":"2023-08-30","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"cyberbullying-detection-for-low-resource","title":"Cyberbullying Detection for Low-resource Languages and Dialects: Review of the State of the Art","date":"2023-08-30","arxiv_id":"2308.15745","n_code_links":0,"syntology":null},{"paper":null,"slug":"denoising-attention-for-query-aware-user","title":"Denoising Attention for Query-aware User Modeling in Personalized Search","date":"2023-08-30","arxiv_id":"2308.15968","n_code_links":0,"syntology":null},{"paper":null,"slug":"feature-attention-network-fa-net-a-deep","title":"Feature Attention Network (FA-Net): A Deep-Learning Based Approach for Underwater Single Image Enhancement","date":"2023-08-30","arxiv_id":"2308.15868","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-scale-data-extraction-from-the-unos","title":"Large-scale data extraction from the UNOS organ donor documents","date":"2023-08-30","arxiv_id":"2308.15752","n_code_links":0,"syntology":null},{"paper":"/paper/latency-aware-unified-dynamic-networks-for","slug":"latency-aware-unified-dynamic-networks-for","title":"Latency-aware Unified Dynamic Networks for Efficient Image Recognition","date":"2023-08-30","arxiv_id":"2308.15949","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: 3 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["leaplabthu/laudnet"],"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":"/paper/llasm-large-language-and-speech-model","slug":"llasm-large-language-and-speech-model","title":"LLaSM: Large Language and Speech Model","date":"2023-08-30","arxiv_id":"2308.15930","n_code_links":1,"syntology":{"ran":2,"of":4,"n_ran_checked":2,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["linksoul-ai/llasm"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"minimum-width-for-deep-narrow-mlp-a","title":"Minimum Width for Deep, Narrow MLP: A Diffeomorphism Approach","date":"2023-08-30","arxiv_id":"2308.15873","n_code_links":0,"syntology":null},{"paper":null,"slug":"msgnn-multi-scale-spatio-temporal-graph","title":"MSGNN: Multi-scale Spatio-temporal Graph Neural Network for Epidemic Forecasting","date":"2023-08-30","arxiv_id":"2308.15840","n_code_links":0,"syntology":null},{"paper":"/paper/nemo-first-glimpse-of-a-new-rule-engine","slug":"nemo-first-glimpse-of-a-new-rule-engine","title":"Nemo: First Glimpse of a New Rule Engine","date":"2023-08-30","arxiv_id":"2308.15897","n_code_links":1,"syntology":null},{"paper":null,"slug":"research-on-image-stitching-based-on","title":"Research on Image Stitching Based on Invariant Features of Reconstructed Plane","date":"2023-08-30","arxiv_id":"2308.15860","n_code_links":0,"syntology":null},{"paper":null,"slug":"semi-supervised-domain-adaptation-with-inter","title":"IIDM: Inter and Intra-domain Mixing for Semi-supervised Domain Adaptation in Semantic Segmentation","date":"2023-08-30","arxiv_id":"2308.15855","n_code_links":0,"syntology":null},{"paper":"/paper/stage-by-stage-wavelet-optimization","slug":"stage-by-stage-wavelet-optimization","title":"Stage-by-stage Wavelet Optimization Refinement Diffusion Model for Sparse-View CT Reconstruction","date":"2023-08-30","arxiv_id":"2308.15942","n_code_links":1,"syntology":null},{"paper":"/paper/surrogate-based-autotuning-for-randomized","slug":"surrogate-based-autotuning-for-randomized","title":"Surrogate-based Autotuning for Randomized Sketching Algorithms in Regression Problems","date":"2023-08-30","arxiv_id":"2308.15720","n_code_links":1,"syntology":null},{"paper":null,"slug":"threshold-knn-shapley-a-linear-time-and","title":"Threshold KNN-Shapley: A Linear-Time and Privacy-Friendly Approach to Data Valuation","date":"2023-08-30","arxiv_id":"2308.15709","n_code_links":0,"syntology":null},{"paper":null,"slug":"vision-based-traffic-accident-detection-and","title":"Vision-Based Traffic Accident Detection and Anticipation: A Survey","date":"2023-08-30","arxiv_id":"2308.15985","n_code_links":0,"syntology":null},{"paper":null,"slug":"3d-adversarial-augmentations-for-robust-out","title":"3D Adversarial Augmentations for Robust Out-of-Domain Predictions","date":"2023-08-29","arxiv_id":"2308.15479","n_code_links":0,"syntology":null},{"paper":null,"slug":"another-look-at-the-linear-probability-model","title":"Another Look at the Linear Probability Model and Nonlinear Index Models","date":"2023-08-29","arxiv_id":"2308.15338","n_code_links":0,"syntology":null},{"paper":"/paper/benchmarking-the-generation-of-fact-checking","slug":"benchmarking-the-generation-of-fact-checking","title":"Benchmarking the Generation of Fact Checking Explanations","date":"2023-08-29","arxiv_id":"2308.15202","n_code_links":1,"syntology":null},{"paper":null,"slug":"bridging-distribution-learning-and-image","title":"Bridging Distribution Learning and Image Clustering in High-dimensional Space","date":"2023-08-29","arxiv_id":"2308.15667","n_code_links":0,"syntology":null},{"paper":null,"slug":"caps-a-practical-partition-index-for-filtered","title":"CAPS: A Practical Partition Index for Filtered Similarity Search","date":"2023-08-29","arxiv_id":"2308.15014","n_code_links":0,"syntology":null},{"paper":null,"slug":"classification-aware-neural-topic-model","title":"Classification-Aware Neural Topic Model Combined With Interpretable Analysis -- For Conflict Classification","date":"2023-08-29","arxiv_id":"2308.15232","n_code_links":0,"syntology":null},{"paper":"/paper/document-ai-a-comparative-study-of","slug":"document-ai-a-comparative-study-of","title":"Document AI: A Comparative Study of Transformer-Based, Graph-Based Models, and Convolutional Neural Networks For Document Layout Analysis","date":"2023-08-29","arxiv_id":"2308.15517","n_code_links":1,"syntology":null},{"paper":"/paper/enhancing-robot-learning-through-learned","slug":"enhancing-robot-learning-through-learned","title":"Enhancing Robot Learning through Learned Human-Attention Feature Maps","date":"2023-08-29","arxiv_id":"2308.15327","n_code_links":1,"syntology":null},{"paper":"/paper/evaluating-explanation-methods-for","slug":"evaluating-explanation-methods-for","title":"Evaluating Explanation Methods for Multivariate Time Series Classification","date":"2023-08-29","arxiv_id":"2308.15223","n_code_links":1,"syntology":null},{"paper":null,"slug":"fedlogic-interpretable-federated-multi-domain","title":"Federated Neuro-Symbolic Learning","date":"2023-08-29","arxiv_id":"2308.15324","n_code_links":0,"syntology":null},{"paper":"/paper/few-shot-object-detection-via-synthetic","slug":"few-shot-object-detection-via-synthetic","title":"Few-Shot Object Detection via Synthetic Features with Optimal Transport","date":"2023-08-29","arxiv_id":"2308.15005","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":null,"slug":"from-ddms-to-dnns-using-process-data-and","title":"From DDMs to DNNs: Using process data and models of decision-making to improve human-AI interactions","date":"2023-08-29","arxiv_id":"2308.15225","n_code_links":0,"syntology":null},{"paper":null,"slug":"group-conditional-conformal-prediction-via","title":"Group-Conditional Conformal Prediction via Quantile Regression Calibration for Crop and Weed Classification","date":"2023-08-29","arxiv_id":"2308.15094","n_code_links":0,"syntology":null}],"record_sha256":"213377a74619917a3ddde9da6d7fa3b071bde5dc582e4d7b194bea4e920c5b82","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}