{"about":{"site":"https://codewithpapers.app","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.","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"},"url":"/code/apply-mask","entry":"apply_mask","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":25,"n_papers_ran":19,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":16,"n_samples_ran":10,"n_samples_fingerprinted":1,"n_places":25,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":3,"ran":6,"unverified":6},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2609.15687","paper":"/paper/arxiv-2609-15687","title":"EEG-Xplain: Decoding Neural Black-Boxes of EEG Foundation Models","date":null,"month_inferred_from_arxiv_id":"2026-09","title_source":"syntology","repo":"gzhu-hcai/EEG-Xplain","path":"model_list/eegpt.py","file_url":"https://github.com/gzhu-hcai/EEG-Xplain/blob/HEAD/model_list/eegpt.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4265c294be96833d","mcp_get_code":{"code_sha256":"4265c294be96833d"}},{"arxiv_id":"2607.00958","paper":"/paper/arxiv-2607-00958","title":"LeNEPA: No-Augmentation Next-Latent Prediction for Time-Series Representation Learning","date":null,"month_inferred_from_arxiv_id":"2026-07","title_source":"syntology","repo":"langotime/lenepa-milets-2026","path":"models/utils.py","file_url":"https://github.com/langotime/lenepa-milets-2026/blob/HEAD/models/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"d932c3a9443f645b","mcp_get_code":{"code_sha256":"d932c3a9443f645b"}},{"arxiv_id":"2605.20735","paper":"/paper/arxiv-2605-20735","title":"Lowering the Barrier to IREX Participation: Open-Source Algorithms, Toolkit, and Benchmarking for Iris Recognition","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"CVRL/PBM","path":"mrcnn/visualize.py","file_url":"https://github.com/CVRL/PBM/blob/HEAD/mrcnn/visualize.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-2-Clause","inline_ok":true,"code_sha256_prefix":"cdda836085a5b1af","mcp_get_code":{"code_sha256":"cdda836085a5b1af"}},{"arxiv_id":"2601.17883","paper":"/paper/arxiv-2601-17883","title":"EEG-FM-Compass: Progress, Benchmarking, and Future Directions for EEG Foundation Models","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"Dingkun0817/EEG-FM-Benchmark","path":"models/FM/EEGPT/Model_EEGPT.py","file_url":"https://github.com/Dingkun0817/EEG-FM-Benchmark/blob/HEAD/models/FM/EEGPT/Model_EEGPT.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"4265c294be96833d","mcp_get_code":{"code_sha256":"4265c294be96833d"}},{"arxiv_id":"2508.17742","paper":"/paper/arxiv-2508-17742","title":"EEG-FM-Bench: A Comprehensive Benchmark for the Systematic Evaluation and Diagnostic Analyses of EEG Foundation Models","date":"2025-08-25","month_inferred_from_arxiv_id":null,"title_source":"syntology","repo":"xw1216/EEG-FM-Bench","path":"baseline/eegpt/model.py","file_url":"https://github.com/xw1216/EEG-FM-Bench/blob/HEAD/baseline/eegpt/model.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"0a7bd7112008de18","mcp_get_code":{"code_sha256":"0a7bd7112008de18"}},{"arxiv_id":"2410.08589","paper":"/paper/retraining-free-merging-of-sparse-mixture-of","title":"Retraining-Free Merging of Sparse MoE via Hierarchical Clustering","date":"2024-10-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wazenmai/HC-SMoE","path":"hcsmoe/merging/grouping_mixtral.py","file_url":"https://github.com/wazenmai/HC-SMoE/blob/HEAD/hcsmoe/merging/grouping_mixtral.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"2663637656dd4380","mcp_get_code":{"code_sha256":"2663637656dd4380"}},{"arxiv_id":"2406.09627","paper":"/paper/robustsam-segment-anything-robustly-on-1","title":"RobustSAM: Segment Anything Robustly on Degraded Images","date":"2024-06-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"robustsam/RobustSAM","path":"gradio_app.py","file_url":"https://github.com/robustsam/RobustSAM/blob/HEAD/gradio_app.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ddc4752f7f12d6e1","mcp_get_code":{"code_sha256":"ddc4752f7f12d6e1"}},{"arxiv_id":"2403.06674","paper":"/paper/car-damage-detection-and-patch-to-patch-self","title":"Car Damage Detection and Patch-to-Patch Self-supervised Image Alignment","date":"2024-03-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"2000222/car-damage-detectionv0","path":"mrcnn/visualize.py","file_url":"https://github.com/2000222/car-damage-detectionv0/blob/HEAD/mrcnn/visualize.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"cdda836085a5b1af","mcp_get_code":{"code_sha256":"cdda836085a5b1af"}},{"arxiv_id":"2311.15264","paper":"/paper/chada-vit-channel-adaptive-attention-for","title":"ChAda-ViT : Channel Adaptive Attention for Joint Representation Learning of Heterogeneous Microscopy Images","date":"2023-11-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nicoboou/chada_vit","path":"main_attn.py","file_url":"https://github.com/nicoboou/chada_vit/blob/HEAD/main_attn.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"c83fb22106327e13","mcp_get_code":{"code_sha256":"c83fb22106327e13"}},{"arxiv_id":"2310.12404","paper":"/paper/loop-copilot-conducting-ai-ensembles-for","title":"Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing","date":"2023-10-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ldzhangyx/loop-copilot","path":"melodytalk/dependencies/vampnet/mask.py","file_url":"https://github.com/ldzhangyx/loop-copilot/blob/HEAD/melodytalk/dependencies/vampnet/mask.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"7c70f983bb9174e5","mcp_get_code":{"code_sha256":"7c70f983bb9174e5"}},{"arxiv_id":"2307.04686","paper":"/paper/vampnet-music-generation-via-masked-acoustic","title":"VampNet: Music Generation via Masked Acoustic Token Modeling","date":"2023-07-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hugofloresgarcia/vampnet","path":"vampnet/mask.py","file_url":"https://github.com/hugofloresgarcia/vampnet/blob/HEAD/vampnet/mask.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"7c70f983bb9174e5","mcp_get_code":{"code_sha256":"7c70f983bb9174e5"}},{"arxiv_id":"2302.01757","paper":"/paper/rs-del-edit-distance-robustness-certificates-1","title":"RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion","date":"2023-01-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dovermore/randomized-deletion","path":"src/torchmalware/certification/masking_mech.py","file_url":"https://github.com/dovermore/randomized-deletion/blob/HEAD/src/torchmalware/certification/masking_mech.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a89350a23ca96ab6","mcp_get_code":{"code_sha256":"a89350a23ca96ab6"}},{"arxiv_id":"2206.11212","paper":"/paper/visfis-visual-feature-importance-supervision","title":"VisFIS: Visual Feature Importance Supervision with Right-for-the-Right-Reason Objectives","date":"2022-06-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zfying/visfis","path":"components/feature_impt.py","file_url":"https://github.com/zfying/visfis/blob/HEAD/components/feature_impt.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"511904da852d99b3","mcp_get_code":{"code_sha256":"511904da852d99b3"}},{"arxiv_id":"2203.12208","paper":"/paper/self-supervised-learning-of-adversarial","title":"Self-supervised Learning of Adversarial Example: Towards Good Generalizations for Deepfake Detection","date":"2022-03-23","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"liangchen527/SLADD","path":"src/networks/synthesizer.py","file_url":"https://github.com/liangchen527/SLADD/blob/HEAD/src/networks/synthesizer.py","status":"ran_fixture","verification_level":1,"contract_check":"DEP_MISSING","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"9a6c144d88add499","mcp_get_code":{"code_sha256":"9a6c144d88add499"}},{"arxiv_id":"2109.13228","paper":"/paper/pass-an-imagenet-replacement-for-self","title":"PASS: An ImageNet replacement for self-supervised pretraining without humans","date":"2021-09-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"facebookresearch/dino","path":"visualize_attention.py","file_url":"https://github.com/facebookresearch/dino/blob/HEAD/visualize_attention.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"c83fb22106327e13","mcp_get_code":{"code_sha256":"c83fb22106327e13"}},{"arxiv_id":"2010.16262","paper":"/paper/experimental-design-for-mri-by-greedy-policy","title":"Experimental design for MRI by greedy policy search","date":"2020-10-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Timsey/pg_mri","path":"src/helpers/transforms.py","file_url":"https://github.com/Timsey/pg_mri/blob/HEAD/src/helpers/transforms.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"92c6e74cc5959c54","mcp_get_code":{"code_sha256":"92c6e74cc5959c54"}},{"arxiv_id":"2003.06975","paper":"/paper/taco-trash-annotations-in-context-for-litter","title":"TACO: Trash Annotations in Context for Litter Detection","date":"2020-03-16","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"pedropro/TACO","path":"detector/visualize.py","file_url":"https://github.com/pedropro/TACO/blob/HEAD/detector/visualize.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cdda836085a5b1af","mcp_get_code":{"code_sha256":"cdda836085a5b1af"}},{"arxiv_id":"2001.03799","paper":"/paper/dudornet-learning-a-dual-domain-recurrent","title":"DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior","date":"2020-01-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bbbbbbzhou/DuDoRNet","path":"datasets/utilizes.py","file_url":"https://github.com/bbbbbbzhou/DuDoRNet/blob/HEAD/datasets/utilizes.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b83db16e1077b04c","mcp_get_code":{"code_sha256":"b83db16e1077b04c"}},{"arxiv_id":"1909.05803","paper":"/paper/self-assembling-modular-networks-for","title":"Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning","date":"2019-09-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jiangycTarheel/NMN-MultiHopQA","path":"snmn/nmn.py","file_url":"https://github.com/jiangycTarheel/NMN-MultiHopQA/blob/HEAD/snmn/nmn.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6662273c573ec3c2","mcp_get_code":{"code_sha256":"6662273c573ec3c2"}},{"arxiv_id":"1901.02970","paper":"/paper/normalized-object-coordinate-space-for","title":"Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation","date":"2019-01-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sahithchada/NOCS_PyTorch","path":"visualize.py","file_url":"https://github.com/sahithchada/NOCS_PyTorch/blob/HEAD/visualize.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cdda836085a5b1af","mcp_get_code":{"code_sha256":"cdda836085a5b1af"}},{"arxiv_id":"1705.09759","paper":"/paper/casenet-deep-category-aware-semantic-edge","title":"CASENet: Deep Category-Aware Semantic Edge Detection","date":"2017-05-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Lavender105/DFF","path":"exps/visualize/visualize.py","file_url":"https://github.com/Lavender105/DFF/blob/HEAD/exps/visualize/visualize.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"087e827fb18a4eb5","mcp_get_code":{"code_sha256":"087e827fb18a4eb5"}},{"arxiv_id":"1703.06870","paper":"/paper/mask-r-cnn","title":"Mask R-CNN","date":"2017-03-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection","path":"Radar_RGB_Camera_Object_Detection/mrcnn/visualize.py","file_url":"https://github.com/RituYadav92/Radar-RGB-Attentive-Multimodal-Object-Detection/blob/HEAD/Radar_RGB_Camera_Object_Detection/mrcnn/visualize.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"cdda836085a5b1af","mcp_get_code":{"code_sha256":"cdda836085a5b1af"}},{"arxiv_id":"1702.01983","paper":"/paper/face-aging-with-conditional-generative","title":"Face Aging With Conditional Generative Adversarial Networks","date":"2017-02-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Vishal-V/GSoC-TensorFlow-2019","path":"mask_rcnn/visualize.py","file_url":"https://github.com/Vishal-V/GSoC-TensorFlow-2019/blob/HEAD/mask_rcnn/visualize.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"cdda836085a5b1af","mcp_get_code":{"code_sha256":"cdda836085a5b1af"}},{"arxiv_id":"1612.03242","paper":"/paper/stackgan-text-to-photo-realistic-image","title":"StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks","date":"2016-12-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Vishal-V/GSoC","path":"mask_rcnn/visualize.py","file_url":"https://github.com/Vishal-V/GSoC/blob/HEAD/mask_rcnn/visualize.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"cdda836085a5b1af","mcp_get_code":{"code_sha256":"cdda836085a5b1af"}},{"arxiv_id":"aaai_25475","paper":null,"title":"arXiv:aaai_25475","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"IndigoPurple/DEQSCI","path":"utils/forward_models_mri.py","file_url":"https://github.com/IndigoPurple/DEQSCI/blob/HEAD/utils/forward_models_mri.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6f81f2b3e0a764fb","mcp_get_code":{"code_sha256":"6f81f2b3e0a764fb"}}]}