{"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/find-denominator","entry":"find_denominator","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":5,"n_papers_ran":0,"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":1,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":1},"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":"2602.01570","paper":"/paper/arxiv-2602-01570","title":"One-Step Diffusion for Perceptual Image Compression","date":null,"month_inferred_from_arxiv_id":"2026-02","title_source":"syntology","repo":"cheesejiang/OSDiff","path":"model/osdiff.py","file_url":"https://github.com/cheesejiang/OSDiff/blob/HEAD/model/osdiff.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"4f8734a02fc01ca2","mcp_get_code":{"code_sha256":"4f8734a02fc01ca2"}},{"arxiv_id":"2511.22549","paper":"/paper/arxiv-2511-22549","title":"Diff-ICMH: Harmonizing Machine and Human Vision in Image Compression with Generative Prior","date":null,"month_inferred_from_arxiv_id":"2025-11","title_source":"syntology","repo":"RuoyuFeng/Diff-ICMH","path":"model/diffeic.py","file_url":"https://github.com/RuoyuFeng/Diff-ICMH/blob/HEAD/model/diffeic.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"4f8734a02fc01ca2","mcp_get_code":{"code_sha256":"4f8734a02fc01ca2"}},{"arxiv_id":"2410.02640","paper":"/paper/diffusion-based-extreme-image-compression","title":"RDEIC: Accelerating Diffusion-Based Extreme Image Compression with Relay Residual Diffusion","date":"2024-10-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"huai-chang/rdeic","path":"model/rdeic.py","file_url":"https://github.com/huai-chang/rdeic/blob/HEAD/model/rdeic.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"4f8734a02fc01ca2","mcp_get_code":{"code_sha256":"4f8734a02fc01ca2"}},{"arxiv_id":"2409.09144","paper":"/paper/primedepth-efficient-monocular-depth","title":"PrimeDepth: Efficient Monocular Depth Estimation with a Stable Diffusion Preimage","date":"2024-09-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"vislearn/PrimeDepth","path":"ldm/modules/diffusionmodules/labeller.py","file_url":"https://github.com/vislearn/PrimeDepth/blob/HEAD/ldm/modules/diffusionmodules/labeller.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"4f8734a02fc01ca2","mcp_get_code":{"code_sha256":"4f8734a02fc01ca2"}},{"arxiv_id":"2404.18820","paper":"/paper/towards-extreme-image-compression-with-latent","title":"Towards Extreme Image Compression with Latent Feature Guidance and Diffusion Prior","date":"2024-04-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"huai-chang/DiffEIC","path":"model/diffeic.py","file_url":"https://github.com/huai-chang/DiffEIC/blob/HEAD/model/diffeic.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"4f8734a02fc01ca2","mcp_get_code":{"code_sha256":"4f8734a02fc01ca2"}}]}