{"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/compute","entry":"compute","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":13,"n_papers_ran":7,"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":15,"n_samples_ran":7,"n_samples_fingerprinted":2,"n_places":15,"n_places_pointer_only":7,"by_status":{"ran_honours":1,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":2,"ran":4,"unverified":8},"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":"2606.11880","paper":"/paper/arxiv-2606-11880","title":"SG2Loc: Sequential Visual Localization on 3D Scene Graphs","date":null,"month_inferred_from_arxiv_id":"2026-06","title_source":"syntology","repo":"DmblnNicole/sg2loc","path":"sg2loc/evaluation/pose_metrics.py","file_url":"https://github.com/DmblnNicole/sg2loc/blob/HEAD/sg2loc/evaluation/pose_metrics.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"eb536fd3421b6015","mcp_get_code":{"code_sha256":"eb536fd3421b6015"}},{"arxiv_id":"2605.02675","paper":"/paper/arxiv-2605-02675","title":"Online Generalised Predictive Coding","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"MLDawn/ODEM","path":"functions/lambda_to_precision.py","file_url":"https://github.com/MLDawn/ODEM/blob/HEAD/functions/lambda_to_precision.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"AGPL-3.0","inline_ok":false,"code_sha256_prefix":"a51f4d96306a48fd","mcp_get_code":{"code_sha256":"a51f4d96306a48fd"}},{"arxiv_id":"2605.02675","paper":"/paper/arxiv-2605-02675","title":"Online Generalised Predictive Coding","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"MLDawn/ODEM","path":"functions/compute_Jacobian.py","file_url":"https://github.com/MLDawn/ODEM/blob/HEAD/functions/compute_Jacobian.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"AGPL-3.0","inline_ok":false,"code_sha256_prefix":"ad40a1a8b6cbc9ce","mcp_get_code":{"code_sha256":"ad40a1a8b6cbc9ce"}},{"arxiv_id":"2601.05913","paper":"/paper/arxiv-2601-05913","title":"Distilling Lightweight Domain Experts from Large ML Models by Identifying Relevant Subspaces","date":null,"month_inferred_from_arxiv_id":"2026-01","title_source":"syntology","repo":"p16i/subdistill","path":"xaikd/jacobian.py","file_url":"https://github.com/p16i/subdistill/blob/HEAD/xaikd/jacobian.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"0b7310099b8bbd1b","mcp_get_code":{"code_sha256":"0b7310099b8bbd1b"}},{"arxiv_id":"2510.14230","paper":"/paper/arxiv-2510-14230","title":"LOTA: Bit-Planes Guided AI-Generated Image Detection","date":null,"month_inferred_from_arxiv_id":"2025-10","title_source":"syntology","repo":"hongsong-wang/LOTA","path":"bit_patch.py","file_url":"https://github.com/hongsong-wang/LOTA/blob/HEAD/bit_patch.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"14bcf83a645b5b40","mcp_get_code":{"code_sha256":"14bcf83a645b5b40"}},{"arxiv_id":"2510.04714","paper":"/paper/arxiv-2510-04714","title":"Object-Centric Representation Learning for Enhanced 3D Semantic Scene Graph Prediction","date":null,"month_inferred_from_arxiv_id":"2025-10","title_source":"syntology","repo":"VisualScienceLab-KHU/OCRL-3DSSG-Codes","path":"data_processing/compute_weight_occurrences.py","file_url":"https://github.com/VisualScienceLab-KHU/OCRL-3DSSG-Codes/blob/HEAD/data_processing/compute_weight_occurrences.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"72485f52d0f05d21","mcp_get_code":{"code_sha256":"72485f52d0f05d21"}},{"arxiv_id":"2406.19236","paper":"/paper/human-aware-vision-and-language-navigation","title":"Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions","date":"2024-06-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"lpercc/ha3d_simulator","path":"human-viewpoint_annotation/GUI.py","file_url":"https://github.com/lpercc/ha3d_simulator/blob/HEAD/human-viewpoint_annotation/GUI.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"da343e316b1e1233","mcp_get_code":{"code_sha256":"da343e316b1e1233"}},{"arxiv_id":"2402.01123","paper":"/paper/a-single-simple-patch-is-all-you-need-for-ai","title":"A Single Simple Patch is All You Need for AI-generated Image Detection","date":"2024-02-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"bcmi/SSP-AI-Generated-Image-Detection","path":"utils/patch.py","file_url":"https://github.com/bcmi/SSP-AI-Generated-Image-Detection/blob/HEAD/utils/patch.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"981b7b1273758511","mcp_get_code":{"code_sha256":"981b7b1273758511"}},{"arxiv_id":"2401.17139","paper":"/paper/large-language-model-evaluation-via-matrix","title":"Diff-eRank: A Novel Rank-Based Metric for Evaluating Large Language Models","date":"2024-01-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"waltonfuture/Diff-eRank","path":"utils/diff_erank_single_sentence.py","file_url":"https://github.com/waltonfuture/Diff-eRank/blob/HEAD/utils/diff_erank_single_sentence.py","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"39f68f78aa11f9b5","mcp_get_code":{"code_sha256":"39f68f78aa11f9b5"}},{"arxiv_id":"2401.16745","paper":"/paper/mt-eval-a-multi-turn-capabilities-evaluation","title":"MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models","date":"2024-01-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"kwanwaichung/mt-eval","path":"utils/bleu.py","file_url":"https://github.com/kwanwaichung/mt-eval/blob/HEAD/utils/bleu.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"7661d3caced944b7","mcp_get_code":{"code_sha256":"7661d3caced944b7"}},{"arxiv_id":"2210.11694","paper":"/paper/multi-view-reasoning-consistent-contrastive","title":"Multi-View Reasoning: Consistent Contrastive Learning for Math Word Problem","date":"2022-10-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zwq2018/multi-view-consistency-for-mwp","path":"src/eval/utils.py","file_url":"https://github.com/zwq2018/multi-view-consistency-for-mwp/blob/HEAD/src/eval/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"6cca9d6a936ecfcc","mcp_get_code":{"code_sha256":"6cca9d6a936ecfcc"}},{"arxiv_id":"2109.08927","paper":"/paper/weakly-supervised-explainable-phrasal","title":"Weakly Supervised Explainable Phrasal Reasoning with Neural Fuzzy Logic","date":"2021-09-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"manga-uofa/epr","path":"main_finetune_epr.py","file_url":"https://github.com/manga-uofa/epr/blob/HEAD/main_finetune_epr.py","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"9942fd5b531ac7ea","mcp_get_code":{"code_sha256":"9942fd5b531ac7ea"}},{"arxiv_id":"2106.06695","paper":"/paper/skiing-on-simplices-kernel-interpolation-on","title":"SKIing on Simplices: Kernel Interpolation on the Permutohedral Lattice for Scalable Gaussian Processes","date":"2021-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"activatedgeek/simplex-gp","path":"experiments/mvm_err.py","file_url":"https://github.com/activatedgeek/simplex-gp/blob/HEAD/experiments/mvm_err.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":"621e361c396ba3b5","mcp_get_code":{"code_sha256":"621e361c396ba3b5"}},{"arxiv_id":"1608.06993","paper":"/paper/densely-connected-convolutional-networks","title":"Densely Connected Convolutional Networks","date":"2016-08-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"GeoTrouvetout/Vehicle_ReID","path":"vehicle_reid/latent_representation.py","file_url":"https://github.com/GeoTrouvetout/Vehicle_ReID/blob/HEAD/vehicle_reid/latent_representation.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"408652244f294883","mcp_get_code":{"code_sha256":"408652244f294883"}},{"arxiv_id":"1608.06993","paper":"/paper/densely-connected-convolutional-networks","title":"Densely Connected Convolutional Networks","date":"2016-08-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"GeoTrouvetout/Vehicle_ReID","path":"vehicle_reid/performance.py","file_url":"https://github.com/GeoTrouvetout/Vehicle_ReID/blob/HEAD/vehicle_reid/performance.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"4fb9f8b3cf01ab1a","mcp_get_code":{"code_sha256":"4fb9f8b3cf01ab1a"}}]}