{"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/138","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":138,"pages_in_order":293,"rows_per_page":100,"rows":[13701,13800],"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/137","next":"/method/dense-connections/papers/139","papers":[{"paper":null,"slug":"harnessing-the-power-of-hugging-face","title":"Harnessing the Power of Hugging Face Transformers for Predicting Mental Health Disorders in Social Networks","date":"2023-06-29","arxiv_id":"2306.16891","n_code_links":0,"syntology":null},{"paper":null,"slug":"icdaelst-intensity-controllable-detail","title":"Lightweight texture transfer based on texture feature preset","date":"2023-06-29","arxiv_id":"2306.16846","n_code_links":0,"syntology":null},{"paper":"/paper/llavar-enhanced-visual-instruction-tuning-for","slug":"llavar-enhanced-visual-instruction-tuning-for","title":"LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding","date":"2023-06-29","arxiv_id":"2306.17107","n_code_links":2,"syntology":{"ran":6,"of":6,"n_ran_checked":0,"n_instrument":6,"unverified":0,"pointer_only":2,"phrase":"6 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; 6 where Syntology's instrument failed) · 0 unverified","official":{"repos":["SALT-NLP/LLaVAR"],"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":["listed","official","unlocated"]}}},{"paper":"/paper/lyricwhiz-robust-multilingual-zero-shot","slug":"lyricwhiz-robust-multilingual-zero-shot","title":"LyricWhiz: Robust Multilingual Zero-shot Lyrics Transcription by Whispering to ChatGPT","date":"2023-06-29","arxiv_id":"2306.17103","n_code_links":1,"syntology":null},{"paper":"/paper/mnisq-a-large-scale-quantum-circuit-dataset","slug":"mnisq-a-large-scale-quantum-circuit-dataset","title":"MNISQ: A Large-Scale Quantum Circuit Dataset for Machine Learning on/for Quantum Computers in the NISQ era","date":"2023-06-29","arxiv_id":"2306.16627","n_code_links":1,"syntology":null},{"paper":"/paper/multi-source-semantic-graph-based-multimodal","slug":"multi-source-semantic-graph-based-multimodal","title":"Multi-source Semantic Graph-based Multimodal Sarcasm Explanation Generation","date":"2023-06-29","arxiv_id":"2306.16650","n_code_links":1,"syntology":null},{"paper":null,"slug":"pvp-personalized-video-prior-for-editable","title":"PVP: Personalized Video Prior for Editable Dynamic Portraits using StyleGAN","date":"2023-06-29","arxiv_id":"2306.17123","n_code_links":0,"syntology":null},{"paper":null,"slug":"safety-aware-task-composition-for-discrete","title":"Safety-Aware Task Composition for Discrete and Continuous Reinforcement Learning","date":"2023-06-29","arxiv_id":"2306.17033","n_code_links":0,"syntology":null},{"paper":"/paper/umass-bionlp-at-mediqa-chat-2023-can-llms","slug":"umass-bionlp-at-mediqa-chat-2023-can-llms","title":"UMASS_BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?","date":"2023-06-29","arxiv_id":"2306.16931","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["believewhat/dr.noteaid"],"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":"action-and-trajectory-planning-for-urban","title":"Action and Trajectory Planning for Urban Autonomous Driving with Hierarchical Reinforcement Learning","date":"2023-06-28","arxiv_id":"2306.15968","n_code_links":0,"syntology":null},{"paper":"/paper/an-efficient-sparse-inference-software","slug":"an-efficient-sparse-inference-software","title":"An Efficient Sparse Inference Software Accelerator for Transformer-based Language Models on CPUs","date":"2023-06-28","arxiv_id":"2306.16601","n_code_links":1,"syntology":null},{"paper":null,"slug":"automatic-calibration-and-error-correction","title":"Pareto Optimal Learning for Estimating Large Language Model Errors","date":"2023-06-28","arxiv_id":"2306.16564","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-the-hype-assessing-the-performance","title":"Beyond the Hype: Assessing the Performance, Trustworthiness, and Clinical Suitability of GPT3.5","date":"2023-06-28","arxiv_id":"2306.15887","n_code_links":0,"syntology":null},{"paper":"/paper/chatlaw-open-source-legal-large-language","slug":"chatlaw-open-source-legal-large-language","title":"Chatlaw: A Multi-Agent Collaborative Legal Assistant with Knowledge Graph Enhanced Mixture-of-Experts Large Language Model","date":"2023-06-28","arxiv_id":"2306.16092","n_code_links":1,"syntology":null},{"paper":null,"slug":"diversity-is-strength-mastering-football-full","title":"Diversity is Strength: Mastering Football Full Game with Interactive Reinforcement Learning of Multiple AIs","date":"2023-06-28","arxiv_id":"2306.15903","n_code_links":0,"syntology":null},{"paper":"/paper/duet-2d-structured-and-approximately","slug":"duet-2d-structured-and-approximately","title":"DUET: 2D Structured and Approximately Equivariant Representations","date":"2023-06-28","arxiv_id":"2306.16058","n_code_links":1,"syntology":{"ran":9,"of":15,"n_ran_checked":8,"n_instrument":1,"unverified":6,"pointer_only":15,"phrase":"9 ran (of which 5 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 6 unverified","official":{"repos":["apple/ml-duet"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":5,"n_ran_no_instrument_failure":8,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"fast-recognition-of-birds-in-offshore-wind","title":"Fast Recognition of birds in offshore wind farms based on an improved deep learning model","date":"2023-06-28","arxiv_id":"2306.16019","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-grained-3d-object-recognition-an","title":"Fine-grained 3D object recognition: an approach and experiments","date":"2023-06-28","arxiv_id":"2306.15919","n_code_links":0,"syntology":null},{"paper":null,"slug":"inferring-the-goals-of-communicating-agents","title":"Inferring the Goals of Communicating Agents from Actions and Instructions","date":"2023-06-28","arxiv_id":"2306.16207","n_code_links":0,"syntology":null},{"paper":"/paper/is-chatgpt-a-biomedical-expert-exploring-the","slug":"is-chatgpt-a-biomedical-expert-exploring-the","title":"Is ChatGPT a Biomedical Expert? -- Exploring the Zero-Shot Performance of Current GPT Models in Biomedical Tasks","date":"2023-06-28","arxiv_id":"2306.16108","n_code_links":1,"syntology":null},{"paper":null,"slug":"leveraging-gpt-4-for-food-effect","title":"Leveraging GPT-4 for Food Effect Summarization to Enhance Product-Specific Guidance Development via Iterative Prompting","date":"2023-06-28","arxiv_id":"2306.16275","n_code_links":0,"syntology":null},{"paper":null,"slug":"mass-spectra-prediction-with-structural-motif","title":"Mass Spectra Prediction with Structural Motif-based Graph Neural Networks","date":"2023-06-28","arxiv_id":"2306.16085","n_code_links":0,"syntology":null},{"paper":"/paper/mathbf-c-2-former-calibrated-and","slug":"mathbf-c-2-former-calibrated-and","title":"$\\mathbf{C}^2$Former: Calibrated and Complementary Transformer for RGB-Infrared Object Detection","date":"2023-06-28","arxiv_id":"2306.16175","n_code_links":2,"syntology":null},{"paper":null,"slug":"multi-site-clinical-federated-learning-using","title":"Multi-Site Clinical Federated Learning using Recursive and Attentive Models and NVFlare","date":"2023-06-28","arxiv_id":"2306.16367","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-positive-pairs-for-enhancing","title":"Semantic Positive Pairs for Enhancing Visual Representation Learning of Instance Discrimination methods","date":"2023-06-28","arxiv_id":"2306.16122","n_code_links":0,"syntology":null},{"paper":null,"slug":"skillnet-x-a-multilingual-multitask-model","title":"SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills","date":"2023-06-28","arxiv_id":"2306.16176","n_code_links":0,"syntology":null},{"paper":"/paper/taqyim-evaluating-arabic-nlp-tasks-using","slug":"taqyim-evaluating-arabic-nlp-tasks-using","title":"Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models","date":"2023-06-28","arxiv_id":"2306.16322","n_code_links":1,"syntology":null},{"paper":null,"slug":"the-2nd-place-solution-for-2023-waymo-open","title":"The 2nd Place Solution for 2023 Waymo Open Sim Agents Challenge","date":"2023-06-28","arxiv_id":"2306.15914","n_code_links":0,"syntology":null},{"paper":"/paper/cellvit-vision-transformers-for-precise-cell","slug":"cellvit-vision-transformers-for-precise-cell","title":"CellViT: Vision Transformers for Precise Cell Segmentation and Classification","date":"2023-06-27","arxiv_id":"2306.15350","n_code_links":3,"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":["tio-ikim/cellvit"],"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":"cutting-edge-techniques-for-depth-map-super","title":"Cutting-Edge Techniques for Depth Map Super-Resolution","date":"2023-06-27","arxiv_id":"2306.15244","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-gpt-3-5-and-gpt-4-on-grammatical","title":"Evaluating GPT-3.5 and GPT-4 on Grammatical Error Correction for Brazilian Portuguese","date":"2023-06-27","arxiv_id":"2306.15788","n_code_links":0,"syntology":null},{"paper":null,"slug":"fedet-a-communication-efficient-federated","title":"FedET: A Communication-Efficient Federated Class-Incremental Learning Framework Based on Enhanced Transformer","date":"2023-06-27","arxiv_id":"2306.15347","n_code_links":0,"syntology":null},{"paper":null,"slug":"gender-bias-in-bert-measuring-and-analysing-1","title":"Gender Bias in BERT -- Measuring and Analysing Biases through Sentiment Rating in a Realistic Downstream Classification Task","date":"2023-06-27","arxiv_id":"2306.15298","n_code_links":0,"syntology":null},{"paper":"/paper/hyenadna-long-range-genomic-sequence-modeling","slug":"hyenadna-long-range-genomic-sequence-modeling","title":"HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution","date":"2023-06-27","arxiv_id":"2306.15794","n_code_links":4,"syntology":{"ran":17,"of":28,"n_ran_checked":13,"n_instrument":4,"unverified":11,"pointer_only":1,"phrase":"17 ran (of which 11 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 4 where Syntology's instrument failed) · 11 unverified","official":{"repos":["HazyResearch/hyena-dna"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":2,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"investigating-cross-domain-behaviors-of-bert","title":"Investigating Cross-Domain Behaviors of BERT in Review Understanding","date":"2023-06-27","arxiv_id":"2306.15123","n_code_links":0,"syntology":null},{"paper":"/paper/leandojo-theorem-proving-with-retrieval-1","slug":"leandojo-theorem-proving-with-retrieval-1","title":"LeanDojo: Theorem Proving with Retrieval-Augmented Language Models","date":"2023-06-27","arxiv_id":"2306.15626","n_code_links":3,"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: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["lean-dojo/leandojo","lean-dojo/leandojochatgpt","lean-dojo/reprover"],"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":"mat-mixed-strategy-game-of-adversarial","title":"MAT: Mixed-Strategy Game of Adversarial Training in Fine-tuning","date":"2023-06-27","arxiv_id":"2306.15826","n_code_links":0,"syntology":null},{"paper":null,"slug":"ncis-deep-color-gradient-maps-regression-and","title":"NCIS: Deep Color Gradient Maps Regression and Three-Class Pixel Classification for Enhanced Neuronal Cell Instance Segmentation in Nissl-Stained Histological Images","date":"2023-06-27","arxiv_id":"2306.15784","n_code_links":0,"syntology":null},{"paper":"/paper/no-service-rail-surface-defect-segmentation","slug":"no-service-rail-surface-defect-segmentation","title":"No-Service Rail Surface Defect Segmentation via Normalized Attention and Dual-scale Interaction","date":"2023-06-27","arxiv_id":"2306.15442","n_code_links":1,"syntology":null},{"paper":"/paper/novel-hybrid-learning-algorithms-for-improved","slug":"novel-hybrid-learning-algorithms-for-improved","title":"Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging Systems","date":"2023-06-27","arxiv_id":"2306.15341","n_code_links":1,"syntology":null},{"paper":"/paper/panet-lidar-panoptic-segmentation-with-sparse","slug":"panet-lidar-panoptic-segmentation-with-sparse","title":"PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation","date":"2023-06-27","arxiv_id":"2306.15348","n_code_links":1,"syntology":null},{"paper":"/paper/sar-atr-under-limited-training-data-via","slug":"sar-atr-under-limited-training-data-via","title":"SAR ATR under Limited Training Data Via MobileNetV3","date":"2023-06-27","arxiv_id":"2306.15287","n_code_links":1,"syntology":null},{"paper":null,"slug":"sparseoptimizer-sparsify-language-models","title":"SparseOptimizer: Sparsify Language Models through Moreau-Yosida Regularization and Accelerate via Compiler Co-design","date":"2023-06-27","arxiv_id":"2306.15656","n_code_links":0,"syntology":null},{"paper":null,"slug":"style-transfer-based-speech-and-audio-visual","title":"Style-transfer based Speech and Audio-visual Scene Understanding for Robot Action Sequence Acquisition from Videos","date":"2023-06-27","arxiv_id":"2306.15644","n_code_links":0,"syntology":null},{"paper":null,"slug":"taming-detection-transformers-for-medical","title":"Taming Detection Transformers for Medical Object Detection","date":"2023-06-27","arxiv_id":"2306.15472","n_code_links":0,"syntology":null},{"paper":"/paper/towards-predicting-pedestrian-evacuation-time","slug":"towards-predicting-pedestrian-evacuation-time","title":"Towards predicting Pedestrian Evacuation Time and Density from Floorplans using a Vision Transformer","date":"2023-06-27","arxiv_id":"2306.15318","n_code_links":1,"syntology":null},{"paper":null,"slug":"unleashing-the-power-of-user-reviews","title":"Unleashing the Power of User Reviews: Exploring Airline Choices at Catania Airport, Italy","date":"2023-06-27","arxiv_id":"2306.15541","n_code_links":0,"syntology":null},{"paper":null,"slug":"variational-latent-discrete-representation","title":"Variational latent discrete representation for time series modelling","date":"2023-06-27","arxiv_id":"2306.15282","n_code_links":0,"syntology":null},{"paper":"/paper/a-denoised-mean-teacher-for-domain-adaptive","slug":"a-denoised-mean-teacher-for-domain-adaptive","title":"A denoised Mean Teacher for domain adaptive point cloud registration","date":"2023-06-26","arxiv_id":"2306.14749","n_code_links":1,"syntology":null},{"paper":"/paper/constraint-aware-and-ranking-distilled-token","slug":"constraint-aware-and-ranking-distilled-token","title":"Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference","date":"2023-06-26","arxiv_id":"2306.14393","n_code_links":1,"syntology":null},{"paper":"/paper/cst-yolo-a-novel-method-for-blood-cell","slug":"cst-yolo-a-novel-method-for-blood-cell","title":"CST-YOLO: A Novel Method for Blood Cell Detection Based on Improved YOLOv7 and CNN-Swin Transformer","date":"2023-06-26","arxiv_id":"2306.14590","n_code_links":1,"syntology":null},{"paper":"/paper/dnabert-2-efficient-foundation-model-and","slug":"dnabert-2-efficient-foundation-model-and","title":"DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species Genome","date":"2023-06-26","arxiv_id":"2306.15006","n_code_links":6,"syntology":{"ran":13,"of":23,"n_ran_checked":9,"n_instrument":4,"unverified":10,"pointer_only":1,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 4 where Syntology's instrument failed) · 10 unverified","official":{"repos":["magics-lab/dnabert_2","zhihan1996/dnabert_2"],"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":"exploring-the-robustness-of-large-language","title":"Exploring the Robustness of Large Language Models for Solving Programming Problems","date":"2023-06-26","arxiv_id":"2306.14583","n_code_links":0,"syntology":null},{"paper":"/paper/fesvibs-federated-split-learning-of-vision","slug":"fesvibs-federated-split-learning-of-vision","title":"FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling","date":"2023-06-26","arxiv_id":"2306.14638","n_code_links":1,"syntology":null},{"paper":null,"slug":"large-multimodal-models-notes-on-cvpr-2023","title":"Large Multimodal Models: Notes on CVPR 2023 Tutorial","date":"2023-06-26","arxiv_id":"2306.14895","n_code_links":0,"syntology":null},{"paper":null,"slug":"lm4hpc-towards-effective-language-model","title":"LM4HPC: Towards Effective Language Model Application in High-Performance Computing","date":"2023-06-26","arxiv_id":"2306.14979","n_code_links":0,"syntology":null},{"paper":"/paper/longcoder-a-long-range-pre-trained-language","slug":"longcoder-a-long-range-pre-trained-language","title":"LongCoder: A Long-Range Pre-trained Language Model for Code Completion","date":"2023-06-26","arxiv_id":"2306.14893","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"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":["microsoft/CodeBERT"],"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":"parameternet-parameters-are-all-you-need-for","title":"ParameterNet: Parameters Are All You Need","date":"2023-06-26","arxiv_id":"2306.14525","n_code_links":0,"syntology":null},{"paper":null,"slug":"supervised-pretraining-can-learn-in-context","title":"Supervised Pretraining Can Learn In-Context Reinforcement Learning","date":"2023-06-26","arxiv_id":"2306.14892","n_code_links":0,"syntology":null},{"paper":"/paper/vint-a-foundation-model-for-visual-navigation","slug":"vint-a-foundation-model-for-visual-navigation","title":"ViNT: A Foundation Model for Visual Navigation","date":"2023-06-26","arxiv_id":"2306.14846","n_code_links":1,"syntology":null},{"paper":"/paper/a-web-based-mpox-skin-lesion-detection-system","slug":"a-web-based-mpox-skin-lesion-detection-system","title":"A Web-based Mpox Skin Lesion Detection System Using State-of-the-art Deep Learning Models Considering Racial Diversity","date":"2023-06-25","arxiv_id":"2306.14169","n_code_links":1,"syntology":null},{"paper":null,"slug":"adaptive-window-pruning-for-efficient-local","title":"Adaptive Window Pruning for Efficient Local Motion Deblurring","date":"2023-06-25","arxiv_id":"2306.14268","n_code_links":0,"syntology":null},{"paper":null,"slug":"addressing-cold-start-problem-for-end-to-end","title":"Addressing Cold Start Problem for End-to-end Automatic Speech Scoring","date":"2023-06-25","arxiv_id":"2306.14310","n_code_links":0,"syntology":null},{"paper":null,"slug":"g-sto-sequential-main-shopping-intention","title":"G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer","date":"2023-06-25","arxiv_id":"2306.14314","n_code_links":0,"syntology":null},{"paper":null,"slug":"gpatcher-a-simple-and-adaptive-mlp-model-for","title":"GPatcher: A Simple and Adaptive MLP Model for Alleviating Graph Heterophily","date":"2023-06-25","arxiv_id":"2306.14340","n_code_links":0,"syntology":null},{"paper":null,"slug":"interactive-design-by-integrating-a-large-pre","title":"Interactive Design by Integrating a Large Pre-Trained Language Model and Building Information Modeling","date":"2023-06-25","arxiv_id":"2306.14165","n_code_links":0,"syntology":null},{"paper":null,"slug":"let-s-do-a-thought-experiment-using","title":"Let's Do a Thought Experiment: Using Counterfactuals to Improve Moral Reasoning","date":"2023-06-25","arxiv_id":"2306.14308","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-scale-cross-contrastive-learning-for","title":"Multi-Scale Cross Contrastive Learning for Semi-Supervised Medical Image Segmentation","date":"2023-06-25","arxiv_id":"2306.14293","n_code_links":0,"syntology":null},{"paper":null,"slug":"revolutionizing-cyber-threat-detection-with","title":"Revolutionizing Cyber Threat Detection with Large Language Models: A privacy-preserving BERT-based Lightweight Model for IoT/IIoT Devices","date":"2023-06-25","arxiv_id":"2306.14263","n_code_links":0,"syntology":null},{"paper":null,"slug":"steganographic-capacity-of-deep-learning","title":"Steganographic Capacity of Deep Learning Models","date":"2023-06-25","arxiv_id":"2306.17189","n_code_links":0,"syntology":null},{"paper":null,"slug":"switch-bert-learning-to-model-multimodal","title":"Switch-BERT: Learning to Model Multimodal Interactions by Switching Attention and Input","date":"2023-06-25","arxiv_id":"2306.14182","n_code_links":0,"syntology":null},{"paper":null,"slug":"action-q-transformer-visual-explanation-in","title":"Action Q-Transformer: Visual Explanation in Deep Reinforcement Learning with Encoder-Decoder Model using Action Query","date":"2023-06-24","arxiv_id":"2306.13879","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-gpt-4-support-analysis-of-textual-data-in","title":"Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise?","date":"2023-06-24","arxiv_id":"2306.13906","n_code_links":0,"syntology":null},{"paper":null,"slug":"comparison-of-pre-trained-language-models-for","title":"Comparison of Pre-trained Language Models for Turkish Address Parsing","date":"2023-06-24","arxiv_id":"2306.13947","n_code_links":0,"syntology":null},{"paper":null,"slug":"emotion-flip-reasoning-in-multiparty-1","title":"Emotion Flip Reasoning in Multiparty Conversations","date":"2023-06-24","arxiv_id":"2306.13959","n_code_links":0,"syntology":null},{"paper":"/paper/fusing-multimodal-signals-on-hyper-complex","slug":"fusing-multimodal-signals-on-hyper-complex","title":"Fusing Multimodal Signals on Hyper-complex Space for Extreme Abstractive Text Summarization (TL;DR) of Scientific Contents","date":"2023-06-24","arxiv_id":"2306.13968","n_code_links":1,"syntology":null},{"paper":null,"slug":"ierl-interpretable-ensemble-representation","title":"IERL: Interpretable Ensemble Representation Learning -- Combining CrowdSourced Knowledge and Distributed Semantic Representations","date":"2023-06-24","arxiv_id":"2306.13865","n_code_links":0,"syntology":null},{"paper":null,"slug":"is-pre-training-truly-better-than-meta","title":"Is Pre-training Truly Better Than Meta-Learning?","date":"2023-06-24","arxiv_id":"2306.13841","n_code_links":0,"syntology":null},{"paper":"/paper/l3cube-mahasent-md-a-multi-domain-marathi","slug":"l3cube-mahasent-md-a-multi-domain-marathi","title":"L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Models","date":"2023-06-24","arxiv_id":"2306.13888","n_code_links":1,"syntology":null},{"paper":"/paper/large-language-models-as-sous-chefs-revising","slug":"large-language-models-as-sous-chefs-revising","title":"Large Language Models as Sous Chefs: Revising Recipes with GPT-3","date":"2023-06-24","arxiv_id":"2306.13986","n_code_links":1,"syntology":null},{"paper":null,"slug":"large-sequence-models-for-sequential-decision","title":"Large Sequence Models for Sequential Decision-Making: A Survey","date":"2023-06-24","arxiv_id":"2306.13945","n_code_links":0,"syntology":null},{"paper":"/paper/math-word-problem-solving-by-generating","slug":"math-word-problem-solving-by-generating","title":"Math Word Problem Solving by Generating Linguistic Variants of Problem Statements","date":"2023-06-24","arxiv_id":"2306.13899","n_code_links":1,"syntology":null},{"paper":"/paper/my-boli-code-mixed-marathi-english-corpora","slug":"my-boli-code-mixed-marathi-english-corpora","title":"My Boli: Code-mixed Marathi-English Corpora, Pretrained Language Models and Evaluation Benchmarks","date":"2023-06-24","arxiv_id":"2306.14030","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-uses-of-large-language-models-to","title":"On the Uses of Large Language Models to Interpret Ambiguous Cyberattack Descriptions","date":"2023-06-24","arxiv_id":"2306.14062","n_code_links":0,"syntology":null},{"paper":null,"slug":"partitioning-guided-k-means-extreme-empty","title":"Partitioning-Guided K-Means: Extreme Empty Cluster Resolution for Extreme Model Compression","date":"2023-06-24","arxiv_id":"2306.14031","n_code_links":0,"syntology":null},{"paper":null,"slug":"waypoint-transformer-reinforcement-learning","title":"Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets","date":"2023-06-24","arxiv_id":"2306.14069","n_code_links":0,"syntology":null},{"paper":null,"slug":"abstractive-text-summarization-for-resumes","title":"Abstractive Text Summarization for Resumes With Cutting Edge NLP Transformers and LSTM","date":"2023-06-23","arxiv_id":"2306.13315","n_code_links":0,"syntology":null},{"paper":"/paper/bridging-the-performance-gap-between-detr-and","slug":"bridging-the-performance-gap-between-detr-and","title":"Bridging the Performance Gap between DETR and R-CNN for Graphical Object Detection in Document Images","date":"2023-06-23","arxiv_id":"2306.13526","n_code_links":0,"syntology":null},{"paper":null,"slug":"cross-language-speech-emotion-recognition","title":"Cross-Language Speech Emotion Recognition Using Multimodal Dual Attention Transformers","date":"2023-06-23","arxiv_id":"2306.13804","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-online-processing-with-deep-neural","slug":"efficient-online-processing-with-deep-neural","title":"Efficient Online Processing with Deep Neural Networks","date":"2023-06-23","arxiv_id":"2306.13474","n_code_links":1,"syntology":null},{"paper":null,"slug":"gkd-generalized-knowledge-distillation-for","title":"On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes","date":"2023-06-23","arxiv_id":"2306.13649","n_code_links":0,"syntology":null},{"paper":"/paper/incorporating-graph-information-in","slug":"incorporating-graph-information-in","title":"Incorporating Graph Information in Transformer-based AMR Parsing","date":"2023-06-23","arxiv_id":"2306.13467","n_code_links":1,"syntology":null},{"paper":null,"slug":"llm-assisted-content-analysis-using-large","title":"LLM-Assisted Content Analysis: Using Large Language Models to Support Deductive Coding","date":"2023-06-23","arxiv_id":"2306.14924","n_code_links":0,"syntology":null},{"paper":"/paper/long-range-language-modeling-with-self","slug":"long-range-language-modeling-with-self","title":"Retrieval-Pretrained Transformer: Long-range Language Modeling with Self-retrieval","date":"2023-06-23","arxiv_id":"2306.13421","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":0,"n_instrument":4,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ohadrubin/rpt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/prores-exploring-degradation-aware-visual","slug":"prores-exploring-degradation-aware-visual","title":"ProRes: Exploring Degradation-aware Visual Prompt for Universal Image Restoration","date":"2023-06-23","arxiv_id":"2306.13653","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["leonmakise/prores"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"resume-information-extraction-via-post-ocr","title":"Resume Information Extraction via Post-OCR Text Processing","date":"2023-06-23","arxiv_id":"2306.13775","n_code_links":0,"syntology":null},{"paper":null,"slug":"swin-free-achieving-better-cross-window","title":"Swin-Free: Achieving Better Cross-Window Attention and Efficiency with Size-varying Window","date":"2023-06-23","arxiv_id":"2306.13776","n_code_links":0,"syntology":null},{"paper":"/paper/system-level-natural-language-feedback","slug":"system-level-natural-language-feedback","title":"System-Level Natural Language Feedback","date":"2023-06-23","arxiv_id":"2306.13588","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["yyy-apple/sys-nl-feedback"],"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":"the-double-helix-inside-the-nlp-transformer","title":"The Double Helix inside the NLP Transformer","date":"2023-06-23","arxiv_id":"2306.13817","n_code_links":0,"syntology":null},{"paper":null,"slug":"upscaling-global-hourly-gpp-with-temporal","title":"Upscaling Global Hourly GPP with Temporal Fusion Transformer (TFT)","date":"2023-06-23","arxiv_id":"2306.13815","n_code_links":0,"syntology":null}],"record_sha256":"4f1bd23c978dd515a1fef06927fa778b52c74f9bbb7c39e0a5daedf7275e0067","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}