{"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/diffusion/papers/119","list_of":"/method/diffusion","method":"Diffusion","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":119,"pages_in_order":139,"rows_per_page":100,"rows":[11801,11900],"of":13848,"counts":{"archive_papers_tagged":13848,"with_a_code_link":5365,"where_syntology_ran_a_sample":2249,"not_listed_spam_title":0,"listed":13848,"listed_where_code_ran":2249,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1969,"every_run_a_failure_of_syntologys_instrument":280,"listed_with_a_run_with_no_instrument_failure":1969,"listed_every_run_a_failure_of_syntologys_instrument":280,"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/diffusion","prev":"/method/diffusion/papers/118","next":"/method/diffusion/papers/120","papers":[{"paper":null,"slug":"compressed-regression-over-adaptive-networks","title":"Compressed Regression over Adaptive Networks","date":"2023-04-07","arxiv_id":"2304.03638","n_code_links":0,"syntology":null},{"paper":"/paper/harnessing-the-spatial-temporal-attention-of","slug":"harnessing-the-spatial-temporal-attention-of","title":"Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image Synthesis","date":"2023-04-07","arxiv_id":"2304.03869","n_code_links":1,"syntology":{"ran":1,"of":3,"n_ran_checked":1,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"1 ran (of which 1 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) · 2 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["ucsb-nlp-chang/diffusion-spacetime-attn"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"zero-shot-ct-field-of-view-completion-with","title":"Zero-shot CT Field-of-view Completion with Unconditional Generative Diffusion Prior","date":"2023-04-07","arxiv_id":"2304.03760","n_code_links":0,"syntology":null},{"paper":"/paper/benchmarking-robustness-to-text-guided","slug":"benchmarking-robustness-to-text-guided","title":"Benchmarking Robustness to Text-Guided Corruptions","date":"2023-04-06","arxiv_id":"2304.02963","n_code_links":1,"syntology":null},{"paper":"/paper/diffusion-models-as-masked-autoencoders","slug":"diffusion-models-as-masked-autoencoders","title":"Diffusion Models as Masked Autoencoders","date":"2023-04-06","arxiv_id":"2304.03283","n_code_links":1,"syntology":{"ran":9,"of":12,"n_ran_checked":8,"n_instrument":1,"unverified":3,"pointer_only":12,"phrase":"9 ran (of which 7 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) · 3 unverified","official":null}},{"paper":null,"slug":"ditto-nerf-diffusion-based-iterative-text-to","title":"DITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Model","date":"2023-04-06","arxiv_id":"2304.02827","n_code_links":0,"syntology":null},{"paper":"/paper/face-animation-with-an-attribute-guided","slug":"face-animation-with-an-attribute-guided","title":"Face Animation with an Attribute-Guided Diffusion Model","date":"2023-04-06","arxiv_id":"2304.03199","n_code_links":1,"syntology":{"ran":12,"of":12,"n_ran_checked":10,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["zengbohan0217/fadm"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"improving-the-hole-picture-towards-a","title":"Improving the Hole Picture: Towards a Consensus on the Mechanism of Nuclear Transport","date":"2023-04-06","arxiv_id":"2304.03230","n_code_links":0,"syntology":null},{"paper":"/paper/rosteals-robust-steganography-using","slug":"rosteals-robust-steganography-using","title":"RoSteALS: Robust Steganography using Autoencoder Latent Space","date":"2023-04-06","arxiv_id":"2304.03400","n_code_links":1,"syntology":null},{"paper":null,"slug":"sketchffusion-sketch-guided-image-editing","title":"SketchFFusion: Sketch-guided image editing with diffusion model","date":"2023-04-06","arxiv_id":"2304.03174","n_code_links":0,"syntology":null},{"paper":"/paper/towards-coherent-image-inpainting-using","slug":"towards-coherent-image-inpainting-using","title":"Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models","date":"2023-04-06","arxiv_id":"2304.03322","n_code_links":1,"syntology":null},{"paper":"/paper/zero-shot-generative-model-adaptation-via","slug":"zero-shot-generative-model-adaptation-via","title":"Zero-shot Generative Model Adaptation via Image-specific Prompt Learning","date":"2023-04-06","arxiv_id":"2304.03119","n_code_links":1,"syntology":{"ran":9,"of":10,"n_ran_checked":9,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 1 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["picsart-ai-research/ipl-zero-shot-generative-model-adaptation"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-diffusion-based-method-for-multi-turn","title":"A Diffusion-based Method for Multi-turn Compositional Image Generation","date":"2023-04-05","arxiv_id":"2304.02192","n_code_links":0,"syntology":null},{"paper":"/paper/eigenfold-generative-protein-structure","slug":"eigenfold-generative-protein-structure","title":"EigenFold: Generative Protein Structure Prediction with Diffusion Models","date":"2023-04-05","arxiv_id":"2304.02198","n_code_links":1,"syntology":{"ran":6,"of":8,"n_ran_checked":6,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"6 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; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["bjing2016/eigenfold"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/generative-novel-view-synthesis-with-3d-aware","slug":"generative-novel-view-synthesis-with-3d-aware","title":"Generative Novel View Synthesis with 3D-Aware Diffusion Models","date":"2023-04-05","arxiv_id":"2304.02602","n_code_links":1,"syntology":null},{"paper":null,"slug":"genphys-from-physical-processes-to-generative","title":"GenPhys: From Physical Processes to Generative Models","date":"2023-04-05","arxiv_id":"2304.02637","n_code_links":0,"syntology":null},{"paper":"/paper/goal-conditioned-imitation-learning-using","slug":"goal-conditioned-imitation-learning-using","title":"Goal-Conditioned Imitation Learning using Score-based Diffusion Policies","date":"2023-04-05","arxiv_id":"2304.02532","n_code_links":1,"syntology":null},{"paper":null,"slug":"jpeg-compressed-images-can-bypass-protections","title":"JPEG Compressed Images Can Bypass Protections Against AI Editing","date":"2023-04-05","arxiv_id":"2304.02234","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-expected-sample-allele-frequencies-from","title":"The Expected Sample Allele Frequencies from Populations of Changing Size via Orthogonal Polynomials","date":"2023-04-05","arxiv_id":"2304.02593","n_code_links":0,"syntology":null},{"paper":"/paper/zero-shot-medical-image-translation-via","slug":"zero-shot-medical-image-translation-via","title":"Zero-shot Medical Image Translation via Frequency-Guided Diffusion Models","date":"2023-04-05","arxiv_id":"2304.02742","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-survey-on-graph-diffusion-models-generative","title":"A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material","date":"2023-04-04","arxiv_id":"2304.01565","n_code_links":0,"syntology":null},{"paper":"/paper/corediff-contextual-error-modulated","slug":"corediff-contextual-error-modulated","title":"CoreDiff: Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization","date":"2023-04-04","arxiv_id":"2304.01814","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-learning-for-diffusion-in-porous-media","title":"Deep learning for diffusion in porous media","date":"2023-04-04","arxiv_id":"2304.02104","n_code_links":0,"syntology":null},{"paper":"/paper/denoising-diffusion-probabilistic-models-to","slug":"denoising-diffusion-probabilistic-models-to","title":"Denoising Diffusion Probabilistic Models to Predict the Density of Molecular Clouds","date":"2023-04-04","arxiv_id":"2304.01670","n_code_links":1,"syntology":null},{"paper":"/paper/dwa-differential-wavelet-amplifier-for-image","slug":"dwa-differential-wavelet-amplifier-for-image","title":"Waving Goodbye to Low-Res: A Diffusion-Wavelet Approach for Image Super-Resolution","date":"2023-04-04","arxiv_id":"2304.01994","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":6,"n_instrument":2,"unverified":2,"pointer_only":5,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 2 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["brian-moser/diwa"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/multimodal-garment-designer-human-centric","slug":"multimodal-garment-designer-human-centric","title":"Multimodal Garment Designer: Human-Centric Latent Diffusion Models for Fashion Image Editing","date":"2023-04-04","arxiv_id":"2304.02051","n_code_links":1,"syntology":null},{"paper":null,"slug":"podia-3d-domain-adaptation-of-3d-generative","title":"PODIA-3D: Domain Adaptation of 3D Generative Model Across Large Domain Gap Using Pose-Preserved Text-to-Image Diffusion","date":"2023-04-04","arxiv_id":"2304.01900","n_code_links":0,"syntology":null},{"paper":null,"slug":"trace-and-pace-controllable-pedestrian","title":"Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion","date":"2023-04-04","arxiv_id":"2304.01893","n_code_links":0,"syntology":null},{"paper":null,"slug":"audit-audio-editing-by-following-instructions","title":"AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models","date":"2023-04-03","arxiv_id":"2304.00830","n_code_links":0,"syntology":null},{"paper":null,"slug":"controllable-motion-synthesis-and","title":"Controllable Motion Synthesis and Reconstruction with Autoregressive Diffusion Models","date":"2023-04-03","arxiv_id":"2304.04681","n_code_links":0,"syntology":null},{"paper":"/paper/diffurec-a-diffusion-model-for-sequential","slug":"diffurec-a-diffusion-model-for-sequential","title":"DiffuRec: A Diffusion Model for Sequential Recommendation","date":"2023-04-03","arxiv_id":"2304.00686","n_code_links":1,"syntology":{"ran":4,"of":7,"n_ran_checked":4,"n_instrument":0,"unverified":3,"pointer_only":1,"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":["whuir/diffurec"],"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":"/paper/diffusion-bridge-mixture-transports","slug":"diffusion-bridge-mixture-transports","title":"Diffusion Bridge Mixture Transports, Schrödinger Bridge Problems and Generative Modeling","date":"2023-04-03","arxiv_id":"2304.00917","n_code_links":2,"syntology":{"ran":6,"of":6,"n_ran_checked":4,"n_instrument":2,"unverified":0,"pointer_only":1,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 3 honoured, 1 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["stepelu/idbm-pytorch"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official","unlocated"]}}},{"paper":"/paper/dreamavatar-text-and-shape-guided-3d-human","slug":"dreamavatar-text-and-shape-guided-3d-human","title":"DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Models","date":"2023-04-03","arxiv_id":"2304.00916","n_code_links":1,"syntology":null},{"paper":null,"slug":"generative-diffusion-prior-for-unified-image","title":"Generative Diffusion Prior for Unified Image Restoration and Enhancement","date":"2023-04-03","arxiv_id":"2304.01247","n_code_links":0,"syntology":null},{"paper":null,"slug":"laplace-fpinns-laplace-based-fractional","title":"Laplace-fPINNs: Laplace-based fractional physics-informed neural networks for solving forward and inverse problems of subdiffusion","date":"2023-04-03","arxiv_id":"2304.00909","n_code_links":0,"syntology":null},{"paper":null,"slug":"vit-dae-transformer-driven-diffusion","title":"ViT-DAE: Transformer-driven Diffusion Autoencoder for Histopathology Image Analysis","date":"2023-04-03","arxiv_id":"2304.01053","n_code_links":0,"syntology":null},{"paper":"/paper/parents-and-children-distinguishing","slug":"parents-and-children-distinguishing","title":"Parents and Children: Distinguishing Multimodal DeepFakes from Natural Images","date":"2023-04-02","arxiv_id":"2304.00500","n_code_links":2,"syntology":null},{"paper":null,"slug":"textile-pattern-generation-using-diffusion","title":"Textile Pattern Generation Using Diffusion Models","date":"2023-04-02","arxiv_id":"2304.00520","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffusion-map-particle-systems-for-generative","title":"Diffusion map particle systems for generative modeling","date":"2023-04-01","arxiv_id":"2304.00200","n_code_links":0,"syntology":null},{"paper":null,"slug":"doubly-stochastic-models-learning-with","title":"Doubly Stochastic Models: Learning with Unbiased Label Noises and Inference Stability","date":"2023-04-01","arxiv_id":"2304.00320","n_code_links":0,"syntology":null},{"paper":null,"slug":"drdisco-deep-registration-for-distortion","title":"DrDisco: Deep Registration for Distortion Correction of Diffusion MRI with single phase-encoding","date":"2023-04-01","arxiv_id":"2304.00217","n_code_links":0,"syntology":null},{"paper":null,"slug":"3d-aware-image-generation-using-2d-diffusion","title":"3D-aware Image Generation using 2D Diffusion Models","date":"2023-03-31","arxiv_id":"2303.17905","n_code_links":0,"syntology":null},{"paper":"/paper/a-closer-look-at-parameter-efficient-tuning","slug":"a-closer-look-at-parameter-efficient-tuning","title":"A Closer Look at Parameter-Efficient Tuning in Diffusion Models","date":"2023-03-31","arxiv_id":"2303.18181","n_code_links":1,"syntology":{"ran":13,"of":14,"n_ran_checked":8,"n_instrument":5,"unverified":1,"pointer_only":5,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 2 honoured, 3 violated, 3 with no contract checked; 5 where Syntology's instrument failed) · 1 unverified","official":{"repos":["Xiang-cd/unet-finetune"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"can-ai-put-gamma-ray-astrophysicists-out-of-a","title":"Can AI Put Gamma-Ray Astrophysicists Out of a Job?","date":"2023-03-31","arxiv_id":"2303.17853","n_code_links":0,"syntology":null},{"paper":"/paper/crossloc3d-aerial-ground-cross-source-3d","slug":"crossloc3d-aerial-ground-cross-source-3d","title":"CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition","date":"2023-03-31","arxiv_id":"2303.17778","n_code_links":1,"syntology":{"ran":11,"of":15,"n_ran_checked":10,"n_instrument":1,"unverified":4,"pointer_only":0,"phrase":"11 ran (of which 9 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 1 where Syntology's instrument failed) · 4 unverified","official":{"repos":["rayguan97/crossloc3d"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":9,"n_ran_no_instrument_failure":10,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"deep-learning-based-diffusion-tensor-cardiac","title":"Deep Learning-based Diffusion Tensor Cardiac Magnetic Resonance Reconstruction: A Comparison Study","date":"2023-03-31","arxiv_id":"2304.00996","n_code_links":0,"syntology":null},{"paper":"/paper/diffusion-action-segmentation","slug":"diffusion-action-segmentation","title":"Diffusion Action Segmentation","date":"2023-03-31","arxiv_id":"2303.17959","n_code_links":1,"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: 2 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":null}},{"paper":null,"slug":"hd-gcn-a-hybrid-diffusion-graph-convolutional","title":"HD-GCN:A Hybrid Diffusion Graph Convolutional Network","date":"2023-03-31","arxiv_id":"2303.17966","n_code_links":0,"syntology":null},{"paper":null,"slug":"ic-fps-instance-centroid-faster-point","title":"IC-FPS: Instance-Centroid Faster Point Sampling Module for 3D Point-base Object Detection","date":"2023-03-31","arxiv_id":"2303.17921","n_code_links":0,"syntology":null},{"paper":"/paper/infty-diff-infinite-resolution-diffusion-with","slug":"infty-diff-infinite-resolution-diffusion-with","title":"$\\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States","date":"2023-03-31","arxiv_id":"2303.18242","n_code_links":1,"syntology":{"ran":8,"of":8,"n_ran_checked":7,"n_instrument":1,"unverified":0,"pointer_only":1,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["samb-t/infty-diff"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/microcanonical-langevin-monte-carlo","slug":"microcanonical-langevin-monte-carlo","title":"Fluctuation without dissipation: Microcanonical Langevin Monte Carlo","date":"2023-03-31","arxiv_id":"2303.18221","n_code_links":1,"syntology":null},{"paper":"/paper/one-shot-unsupervised-domain-adaptation-with","slug":"one-shot-unsupervised-domain-adaptation-with","title":"One-shot Unsupervised Domain Adaptation with Personalized Diffusion Models","date":"2023-03-31","arxiv_id":"2303.18080","n_code_links":1,"syntology":null},{"paper":"/paper/pay-attention-accuracy-versus","slug":"pay-attention-accuracy-versus","title":"Trade-offs in Fine-tuned Diffusion Models Between Accuracy and Interpretability","date":"2023-03-31","arxiv_id":"2303.17908","n_code_links":1,"syntology":null},{"paper":"/paper/reference-based-image-composition-with-sketch","slug":"reference-based-image-composition-with-sketch","title":"Reference-based Image Composition with Sketch via Structure-aware Diffusion Model","date":"2023-03-31","arxiv_id":"2304.09748","n_code_links":1,"syntology":null},{"paper":null,"slug":"textit-e-uber-a-crowdsourcing-platform-for","title":"$\\textit{e-Uber}$: A Crowdsourcing Platform for Electric Vehicle-based Ride- and Energy-sharing","date":"2023-03-31","arxiv_id":"2304.04753","n_code_links":0,"syntology":null},{"paper":"/paper/avatarcraft-transforming-text-into-neural","slug":"avatarcraft-transforming-text-into-neural","title":"AvatarCraft: Transforming Text into Neural Human Avatars with Parameterized Shape and Pose Control","date":"2023-03-30","arxiv_id":"2303.17606","n_code_links":1,"syntology":null},{"paper":null,"slug":"consistent-view-synthesis-with-pose-guided","title":"Consistent View Synthesis with Pose-Guided Diffusion Models","date":"2023-03-30","arxiv_id":"2303.17598","n_code_links":0,"syntology":null},{"paper":null,"slug":"dae-talker-high-fidelity-speech-driven","title":"DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder","date":"2023-03-30","arxiv_id":"2303.17550","n_code_links":0,"syntology":null},{"paper":"/paper/ddp-diffusion-model-for-dense-visual","slug":"ddp-diffusion-model-for-dense-visual","title":"DDP: Diffusion Model for Dense Visual Prediction","date":"2023-03-30","arxiv_id":"2303.17559","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-generative-model-and-its-applications-in","title":"Deep Generative Model and Its Applications in Efficient Wireless Network Management: A Tutorial and Case Study","date":"2023-03-30","arxiv_id":"2303.17114","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffcollage-parallel-generation-of-large","title":"DiffCollage: Parallel Generation of Large Content with Diffusion Models","date":"2023-03-30","arxiv_id":"2303.17076","n_code_links":0,"syntology":null},{"paper":"/paper/discriminative-class-tokens-for-text-to-image","slug":"discriminative-class-tokens-for-text-to-image","title":"Discriminative Class Tokens for Text-to-Image Diffusion Models","date":"2023-03-30","arxiv_id":"2303.17155","n_code_links":1,"syntology":null},{"paper":null,"slug":"efficient-sampling-of-stochastic-differential","title":"Efficient Sampling of Stochastic Differential Equations with Positive Semi-Definite Models","date":"2023-03-30","arxiv_id":"2303.17109","n_code_links":0,"syntology":null},{"paper":"/paper/forget-me-not-learning-to-forget-in-text-to","slug":"forget-me-not-learning-to-forget-in-text-to","title":"Forget-Me-Not: Learning to Forget in Text-to-Image Diffusion Models","date":"2023-03-30","arxiv_id":"2303.17591","n_code_links":1,"syntology":null},{"paper":"/paper/layoutdiffusion-controllable-diffusion-model","slug":"layoutdiffusion-controllable-diffusion-model","title":"LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation","date":"2023-03-30","arxiv_id":"2303.17189","n_code_links":2,"syntology":{"ran":11,"of":19,"n_ran_checked":10,"n_instrument":1,"unverified":8,"pointer_only":3,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 2 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 8 unverified","official":{"repos":["dcdcvgroup/layout-diffusion-mindspore"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["named_in_paper","official"]}}},{"paper":"/paper/pair-diffusion-object-level-image-editing","slug":"pair-diffusion-object-level-image-editing","title":"PAIR-Diffusion: A Comprehensive Multimodal Object-Level Image Editor","date":"2023-03-30","arxiv_id":"2303.17546","n_code_links":1,"syntology":null},{"paper":null,"slug":"social-biases-through-the-text-to-image","title":"Social Biases through the Text-to-Image Generation Lens","date":"2023-03-30","arxiv_id":"2304.06034","n_code_links":0,"syntology":null},{"paper":"/paper/token-merging-for-fast-stable-diffusion","slug":"token-merging-for-fast-stable-diffusion","title":"Token Merging for Fast Stable Diffusion","date":"2023-03-30","arxiv_id":"2303.17604","n_code_links":4,"syntology":{"ran":7,"of":7,"n_ran_checked":3,"n_instrument":4,"unverified":0,"pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 1 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","official":{"repos":["dbolya/tomesd"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/zero-shot-video-editing-using-off-the-shelf","slug":"zero-shot-video-editing-using-off-the-shelf","title":"Zero-Shot Video Editing Using Off-The-Shelf Image Diffusion Models","date":"2023-03-30","arxiv_id":"2303.17599","n_code_links":1,"syntology":null},{"paper":"/paper/4d-facial-expression-diffusion-model","slug":"4d-facial-expression-diffusion-model","title":"4D Facial Expression Diffusion Model","date":"2023-03-29","arxiv_id":"2303.16611","n_code_links":1,"syntology":null},{"paper":"/paper/a-pilot-study-of-query-free-adversarial","slug":"a-pilot-study-of-query-free-adversarial","title":"A Pilot Study of Query-Free Adversarial Attack against Stable Diffusion","date":"2023-03-29","arxiv_id":"2303.16378","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":3,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["optml-group/qf-attack"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-unified-single-stage-learning-model-for","title":"A Unified Learning Model for Estimating Fiber Orientation Distribution Functions on Heterogeneous Multi-shell Diffusion-weighted MRI","date":"2023-03-29","arxiv_id":"2303.16376","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffusion-schrodinger-bridge-matching-1","title":"Diffusion Schrödinger Bridge Matching","date":"2023-03-29","arxiv_id":"2303.16852","n_code_links":0,"syntology":null},{"paper":null,"slug":"holodiffusion-training-a-3d-diffusion-model","title":"HoloDiffusion: Training a 3D Diffusion Model using 2D Images","date":"2023-03-29","arxiv_id":"2303.16509","n_code_links":0,"syntology":null},{"paper":"/paper/hyperdiffusion-generating-implicit-neural","slug":"hyperdiffusion-generating-implicit-neural","title":"HyperDiffusion: Generating Implicit Neural Fields with Weight-Space Diffusion","date":"2023-03-29","arxiv_id":"2303.17015","n_code_links":1,"syntology":null},{"paper":"/paper/implicit-diffusion-models-for-continuous","slug":"implicit-diffusion-models-for-continuous","title":"Implicit Diffusion Models for Continuous Super-Resolution","date":"2023-03-29","arxiv_id":"2303.16491","n_code_links":1,"syntology":{"ran":5,"of":10,"n_ran_checked":3,"n_instrument":2,"unverified":5,"pointer_only":10,"phrase":"5 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; 2 where Syntology's instrument failed) · 5 unverified","official":{"repos":["ree1s/idm"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":"/paper/mdp-a-generalized-framework-for-text-guided","slug":"mdp-a-generalized-framework-for-text-guided","title":"MDP: A Generalized Framework for Text-Guided Image Editing by Manipulating the Diffusion Path","date":"2023-03-29","arxiv_id":"2303.16765","n_code_links":2,"syntology":{"ran":6,"of":6,"n_ran_checked":3,"n_instrument":3,"unverified":0,"pointer_only":0,"phrase":"6 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; 3 where Syntology's instrument failed) · 0 unverified","official":{"repos":["qianwangx/mdp-diffusion"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["listed","official"]}}},{"paper":null,"slug":"physics-driven-diffusion-models-for-impact","title":"Physics-Driven Diffusion Models for Impact Sound Synthesis from Videos","date":"2023-03-29","arxiv_id":"2303.16897","n_code_links":0,"syntology":null},{"paper":"/paper/wordstylist-styled-verbatim-handwritten-text","slug":"wordstylist-styled-verbatim-handwritten-text","title":"WordStylist: Styled Verbatim Handwritten Text Generation with Latent Diffusion Models","date":"2023-03-29","arxiv_id":"2303.16576","n_code_links":1,"syntology":null},{"paper":null,"slug":"cellular-exchange-imaging-cexi-evaluation-of","title":"Cellular EXchange Imaging (CEXI): Evaluation of a diffusion model including water exchange in cells using numerical phantoms of permeable spheres","date":"2023-03-28","arxiv_id":"2303.16112","n_code_links":0,"syntology":null},{"paper":null,"slug":"ddmm-synth-a-denoising-diffusion-model-for","title":"DDMM-Synth: A Denoising Diffusion Model for Cross-modal Medical Image Synthesis with Sparse-view Measurement Embedding","date":"2023-03-28","arxiv_id":"2303.15770","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffuld-diffusive-universal-lesion-detection","title":"DiffULD: Diffusive Universal Lesion Detection","date":"2023-03-28","arxiv_id":"2303.15728","n_code_links":0,"syntology":null},{"paper":null,"slug":"instruct-3d-to-3d-text-instruction-guided-3d","title":"Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversion","date":"2023-03-28","arxiv_id":"2303.15780","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-cyclegan-improving-quality-of-gans","slug":"rethinking-cyclegan-improving-quality-of-gans","title":"UVCGAN v2: An Improved Cycle-Consistent GAN for Unpaired Image-to-Image Translation","date":"2023-03-28","arxiv_id":"2303.16280","n_code_links":2,"syntology":null},{"paper":"/paper/stylediffusion-prompt-embedding-inversion-for","slug":"stylediffusion-prompt-embedding-inversion-for","title":"StyleDiffusion: Prompt-Embedding Inversion for Text-Based Editing","date":"2023-03-28","arxiv_id":"2303.15649","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["sen-mao/StyleDiffusion"],"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/visual-chain-of-thought-diffusion-models","slug":"visual-chain-of-thought-diffusion-models","title":"Visual Chain-of-Thought Diffusion Models","date":"2023-03-28","arxiv_id":"2303.16187","n_code_links":1,"syntology":null},{"paper":"/paper/your-diffusion-model-is-secretly-a-zero-shot","slug":"your-diffusion-model-is-secretly-a-zero-shot","title":"Your Diffusion Model is Secretly a Zero-Shot Classifier","date":"2023-03-28","arxiv_id":"2303.16203","n_code_links":4,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":1,"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":{"repos":["diffusion-classifier/diffusion-classifier"],"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":["listed","official"]}}},{"paper":"/paper/anti-dreambooth-protecting-users-from","slug":"anti-dreambooth-protecting-users-from","title":"Anti-DreamBooth: Protecting users from personalized text-to-image synthesis","date":"2023-03-27","arxiv_id":"2303.15433","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":0,"n_instrument":1,"unverified":1,"pointer_only":2,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["vinairesearch/anti-dreambooth"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/debiasing-scores-and-prompts-of-2d-diffusion","slug":"debiasing-scores-and-prompts-of-2d-diffusion","title":"Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation","date":"2023-03-27","arxiv_id":"2303.15413","n_code_links":1,"syntology":null},{"paper":"/paper/diffusion-models-for-memory-efficient","slug":"diffusion-models-for-memory-efficient","title":"Memory-Efficient 3D Denoising Diffusion Models for Medical Image Processing","date":"2023-03-27","arxiv_id":"2303.15288","n_code_links":1,"syntology":null},{"paper":null,"slug":"exploring-continual-learning-of-diffusion","title":"Exploring Continual Learning of Diffusion Models","date":"2023-03-27","arxiv_id":"2303.15342","n_code_links":0,"syntology":null},{"paper":"/paper/seer-language-instructed-video-prediction","slug":"seer-language-instructed-video-prediction","title":"Seer: Language Instructed Video Prediction with Latent Diffusion Models","date":"2023-03-27","arxiv_id":"2303.14897","n_code_links":1,"syntology":null},{"paper":"/paper/text-to-image-diffusion-models-are-zero-shot","slug":"text-to-image-diffusion-models-are-zero-shot","title":"Text-to-Image Diffusion Models are Zero-Shot Classifiers","date":"2023-03-27","arxiv_id":"2303.15233","n_code_links":1,"syntology":null},{"paper":"/paper/the-stable-signature-rooting-watermarks-in","slug":"the-stable-signature-rooting-watermarks-in","title":"The Stable Signature: Rooting Watermarks in Latent Diffusion Models","date":"2023-03-27","arxiv_id":"2303.15435","n_code_links":3,"syntology":{"ran":2,"of":2,"n_ran_checked":2,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 2 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) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["facebookresearch/stable_signature"],"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/gesturediffuclip-gesture-diffusion-model-with","slug":"gesturediffuclip-gesture-diffusion-model-with","title":"GestureDiffuCLIP: Gesture Diffusion Model with CLIP Latents","date":"2023-03-26","arxiv_id":"2303.14613","n_code_links":1,"syntology":null},{"paper":"/paper/pdpp-projected-diffusion-for-procedure","slug":"pdpp-projected-diffusion-for-procedure","title":"PDPP: Projected Diffusion for Procedure Planning in Instructional Videos","date":"2023-03-26","arxiv_id":"2303.14676","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 2 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) · 1 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","official":{"repos":["mcg-nju/pdpp"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/a-registration-and-uncertainty-based","slug":"a-registration-and-uncertainty-based","title":"A Registration- and Uncertainty-based Framework for White Matter Tract Segmentation With Only One Annotated Subject","date":"2023-03-25","arxiv_id":"2303.14371","n_code_links":1,"syntology":null},{"paper":"/paper/better-aligning-text-to-image-models-with","slug":"better-aligning-text-to-image-models-with","title":"Human Preference Score: Better Aligning Text-to-Image Models with Human Preference","date":"2023-03-25","arxiv_id":"2303.14420","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":1,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["tgxs002/align_sd"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/freestyle-layout-to-image-synthesis","slug":"freestyle-layout-to-image-synthesis","title":"Freestyle Layout-to-Image Synthesis","date":"2023-03-25","arxiv_id":"2303.14412","n_code_links":1,"syntology":{"ran":3,"of":6,"n_ran_checked":3,"n_instrument":0,"unverified":3,"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) · 3 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":{"repos":["essunny310/freestylenet"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/masked-diffusion-transformer-is-a-strong","slug":"masked-diffusion-transformer-is-a-strong","title":"MDTv2: Masked Diffusion Transformer is a Strong Image Synthesizer","date":"2023-03-25","arxiv_id":"2303.14389","n_code_links":1,"syntology":{"ran":4,"of":6,"n_ran_checked":4,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"4 ran (of which 2 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["sail-sg/mdt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":2,"n_ran_no_instrument_failure":4,"n_unverified":2,"ran_from_kinds":["official"]}}}],"record_sha256":"5bca5b29dea7713fb3ef9f0d12c66451ec3c3a5db212403ac3ae7733c91bf34d","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}