{"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/time-text","entry":"time_text","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":9,"n_papers_ran":9,"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":2,"n_samples_ran":2,"n_samples_fingerprinted":2,"n_places":10,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":2,"unverified":0},"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":"2605.00310","paper":"/paper/arxiv-2605-00310","title":"Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"ai-spatial/GeoSR-Bench","path":"MODIS_L8/SR_Models/CFAT_M2L8/utils.py","file_url":"https://github.com/ai-spatial/GeoSR-Bench/blob/HEAD/MODIS_L8/SR_Models/CFAT_M2L8/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"2605.00310","paper":"/paper/arxiv-2605-00310","title":"Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"ai-spatial/GeoSR-Bench","path":"MODIS_L8/SR_Models/SRNO_M2L8/utils.py","file_url":"https://github.com/ai-spatial/GeoSR-Bench/blob/HEAD/MODIS_L8/SR_Models/SRNO_M2L8/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"6a243afbe200f82c","mcp_get_code":{"code_sha256":"6a243afbe200f82c"}},{"arxiv_id":"2506.22624","paper":"/paper/seg-r1-segmentation-can-be-surprisingly","title":"Seg-R1: Segmentation Can Be Surprisingly Simple with Reinforcement Learning","date":"2025-06-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"geshang777/FOCUS","path":"focus/evaluation/utils.py","file_url":"https://github.com/geshang777/FOCUS/blob/HEAD/focus/evaluation/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"2506.22246","paper":"/paper/eamamba-efficient-all-around-vision-state","title":"EAMamba: Efficient All-Around Vision State Space Model for Image Restoration","date":"2025-06-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"daidaijr/EAMamba","path":"utils.py","file_url":"https://github.com/daidaijr/EAMamba/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"2407.05082","paper":"/paper/dmtg-one-shot-differentiable-multi-task","title":"DMTG: One-Shot Differentiable Multi-Task Grouping","date":"2024-07-06","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ethanygao/DMTG","path":"utils/model_utils.py","file_url":"https://github.com/ethanygao/DMTG/blob/HEAD/utils/model_utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"2312.07374","paper":"/paper/relax-image-specific-prompt-requirement-in","title":"Relax Image-Specific Prompt Requirement in SAM: A Single Generic Prompt for Segmenting Camouflaged Objects","date":"2023-12-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jyLin8100/GenSAM","path":"utils.py","file_url":"https://github.com/jyLin8100/GenSAM/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"2111.08918","paper":"/paper/local-texture-estimator-for-implicit","title":"Local Texture Estimator for Implicit Representation Function","date":"2021-11-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jaewon-lee-b/lte","path":"utils.py","file_url":"https://github.com/jaewon-lee-b/lte/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"2108.11084","paper":"/paper/efficient-transformer-for-single-image-super","title":"Transformer for Single Image Super-Resolution","date":"2021-08-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"luissen/esrt","path":"utils.py","file_url":"https://github.com/luissen/esrt/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"Pak_B-Spline_Texture_Coefficients_Estimator_for_Screen_Content_Image_Super-Resolution_CVPR_2023_paper","paper":null,"title":"arXiv:Pak_B-Spline_Texture_Coefficients_Estimator_for_Screen_Content_Image_Super-Resolution_CVPR_2023_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"ByeongHyunPak/btc","path":"utils.py","file_url":"https://github.com/ByeongHyunPak/btc/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}},{"arxiv_id":"Han_ABCD_Arbitrary_Bitwise_Coefficient_for_De-Quantization_CVPR_2023_paper","paper":null,"title":"arXiv:Han_ABCD_Arbitrary_Bitwise_Coefficient_for_De-Quantization_CVPR_2023_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"WooKyoungHan/ABCD","path":"utils.py","file_url":"https://github.com/WooKyoungHan/ABCD/blob/HEAD/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"14982a5b13861f94","mcp_get_code":{"code_sha256":"14982a5b13861f94"}}]}