{"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/normalize-range","entry":"normalize_range","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":7,"n_papers_ran":3,"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":6,"n_samples_ran":2,"n_samples_fingerprinted":2,"n_places":8,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":2,"unverified":4},"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":"2605.19811","paper":"/paper/arxiv-2605-19811","title":"LionMuon: Alternating Spectral and Sign Descent for Efficient Training","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"brain-lab-research/lion-muon","path":"src/optim/muon.py","file_url":"https://github.com/brain-lab-research/lion-muon/blob/HEAD/src/optim/muon.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ccaf2bdc7c8eeafa","mcp_get_code":{"code_sha256":"ccaf2bdc7c8eeafa"}},{"arxiv_id":"2603.00357","paper":"/paper/arxiv-2603-00357","title":"SPARe: Stacked Parallelism with Adaptive Reordering for Fault-Tolerant LLM Pretraining Systems with 100k+ GPUs","date":null,"month_inferred_from_arxiv_id":"2026-03","title_source":"syntology","repo":"padsysl/SPARe","path":"platform/generate_platform.py","file_url":"https://github.com/padsysl/SPARe/blob/HEAD/platform/generate_platform.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"227f20ed76a76988","mcp_get_code":{"code_sha256":"227f20ed76a76988"}},{"arxiv_id":"2601.14603","paper":"/paper/arxiv-2601-14603","title":"Variance-Adaptive Muon: Accelerating LLM Pretraining with NSR-Modulated and Variance-Scaled Momentum","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"jingru-lee/Variance-Adaptive-Muon","path":"Suite_A/src/optim/muon.py","file_url":"https://github.com/jingru-lee/Variance-Adaptive-Muon/blob/HEAD/Suite_A/src/optim/muon.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ccaf2bdc7c8eeafa","mcp_get_code":{"code_sha256":"ccaf2bdc7c8eeafa"}},{"arxiv_id":"2601.14603","paper":"/paper/arxiv-2601-14603","title":"Variance-Adaptive Muon: Accelerating LLM Pretraining with NSR-Modulated and Variance-Scaled Momentum","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"jingru-lee/Variance-Adaptive-Muon","path":"Suite_A/src/optim/muon_vs.py","file_url":"https://github.com/jingru-lee/Variance-Adaptive-Muon/blob/HEAD/Suite_A/src/optim/muon_vs.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"335254babb23e8b3","mcp_get_code":{"code_sha256":"335254babb23e8b3"}},{"arxiv_id":"2503.00533","paper":"/paper/bodygen-advancing-towards-efficient-1","title":"BodyGen: Advancing Towards Efficient Embodiment Co-Design","date":"2025-03-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"GenesisOrigin/BodyGen","path":"khrylib/robot/xml_robot.py","file_url":"https://github.com/GenesisOrigin/BodyGen/blob/HEAD/khrylib/robot/xml_robot.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":"66a0415bf6172ec1","mcp_get_code":{"code_sha256":"66a0415bf6172ec1"}},{"arxiv_id":"2309.08596","paper":"/paper/robust-e-nerf-nerf-from-sparse-noisy-events","title":"Robust e-NeRF: NeRF from Sparse & Noisy Events under Non-Uniform Motion","date":"2023-09-15","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"wengflow/robust-e-nerf","path":"robust_e_nerf/utils/tensor_ops.py","file_url":"https://github.com/wengflow/robust-e-nerf/blob/HEAD/robust_e_nerf/utils/tensor_ops.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a6b7bfde2f40ad45","mcp_get_code":{"code_sha256":"a6b7bfde2f40ad45"}},{"arxiv_id":"2306.00036","paper":"/paper/symmetry-aware-robot-design-with-structured","title":"Symmetry-Aware Robot Design with Structured Subgroups","date":"2023-05-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"drdh/sard","path":"khrylib/robot/xml_robot.py","file_url":"https://github.com/drdh/sard/blob/HEAD/khrylib/robot/xml_robot.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5e0c4aa3258c0ef5","mcp_get_code":{"code_sha256":"5e0c4aa3258c0ef5"}},{"arxiv_id":"2110.03659","paper":"/paper/transform2act-learning-a-transform-and","title":"Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design","date":"2021-10-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Khrylx/Transform2Act","path":"khrylib/robot/xml_robot.py","file_url":"https://github.com/Khrylx/Transform2Act/blob/HEAD/khrylib/robot/xml_robot.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5e0c4aa3258c0ef5","mcp_get_code":{"code_sha256":"5e0c4aa3258c0ef5"}}]}