{"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/sublayerconnection","entry":"SublayerConnection","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":16,"n_papers_ran":15,"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":20,"n_samples_ran":19,"n_samples_fingerprinted":0,"n_places":20,"n_places_pointer_only":14,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":19,"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":"2605.28166","paper":"/paper/arxiv-2605-28166","title":"QuITE: Query-Based Irregular Time Series Embedding","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"Meaningfull9502/QuITE","path":"models/embeddings/quite.py","file_url":"https://github.com/Meaningfull9502/QuITE/blob/HEAD/models/embeddings/quite.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8a1bd5878f5a16da","mcp_get_code":{"code_sha256":"8a1bd5878f5a16da"}},{"arxiv_id":"2603.15774","paper":"/paper/arxiv-2603-15774","title":"Domain Adaptation Without the Compute Burden for Efficient Whole Slide Image Analysis","date":null,"month_inferred_from_arxiv_id":"2026-03","title_source":"syntology","repo":"umarikkar/eWSI","path":"models/wsi_models.py","file_url":"https://github.com/umarikkar/eWSI/blob/HEAD/models/wsi_models.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"37cd4b9de4d72c3b","mcp_get_code":{"code_sha256":"37cd4b9de4d72c3b"}},{"arxiv_id":"2505.16298","paper":"/paper/flow-matching-based-sequential-recommender","title":"Flow Matching based Sequential Recommender Model","date":"2025-05-22","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"FengLiu-1/FMRec","path":"src/fmrec.py","file_url":"https://github.com/FengLiu-1/FMRec/blob/HEAD/src/fmrec.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"5045d6f935fdd8ed","mcp_get_code":{"code_sha256":"5045d6f935fdd8ed"}},{"arxiv_id":"2503.07635","paper":"/paper/cross-modal-causal-relation-alignment-for-1","title":"Cross-modal Causal Relation Alignment for Video Question Grounding","date":"2025-03-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"WissingChen/CRA-GQA","path":"models/cra.py","file_url":"https://github.com/WissingChen/CRA-GQA/blob/HEAD/models/cra.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"11448d9a3a1f9888","mcp_get_code":{"code_sha256":"11448d9a3a1f9888"}},{"arxiv_id":"2410.05711","paper":"/paper/diffusion-auto-regressive-transformer-for","title":"Diffusion Auto-regressive Transformer for Effective Self-supervised Time Series Forecasting","date":"2024-10-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mingyue-cheng/timemae","path":"model/TimeMAE.py","file_url":"https://github.com/mingyue-cheng/timemae/blob/HEAD/model/TimeMAE.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"8d9d95edd7487e3f","mcp_get_code":{"code_sha256":"8d9d95edd7487e3f"}},{"arxiv_id":"2405.03943","paper":"/paper/predictive-modeling-with-temporal-graphical","title":"Predictive Modeling with Temporal Graphical Representation on Electronic Health Records","date":"2024-05-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"The-Real-JerryChen/TRANS","path":"models/Seqmodels.py","file_url":"https://github.com/The-Real-JerryChen/TRANS/blob/HEAD/models/Seqmodels.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c155570232cc0f8c","mcp_get_code":{"code_sha256":"c155570232cc0f8c"}},{"arxiv_id":"2404.13478","paper":"/paper/deep-se-3-equivariant-geometric-reasoning-for","title":"Deep SE(3)-Equivariant Geometric Reasoning for Precise Placement Tasks","date":"2024-04-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"r-pad/taxpose","path":"taxpose/nets/transformer_flow.py","file_url":"https://github.com/r-pad/taxpose/blob/HEAD/taxpose/nets/transformer_flow.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"dd481d1dfb89ace0","mcp_get_code":{"code_sha256":"dd481d1dfb89ace0"}},{"arxiv_id":"2210.01753","paper":"/paper/hypro-a-hybridly-normalized-probabilistic","title":"HYPRO: A Hybridly Normalized Probabilistic Model for Long-Horizon Prediction of Event Sequences","date":"2022-10-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ant-research/hypro_tpp","path":"hypro_tpp/models/xfmr_nhp_fast.py","file_url":"https://github.com/ant-research/hypro_tpp/blob/HEAD/hypro_tpp/models/xfmr_nhp_fast.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"d68aa2c5bcfcfed4","mcp_get_code":{"code_sha256":"d68aa2c5bcfcfed4"}},{"arxiv_id":"2202.13024","paper":"/paper/assist-towards-label-noise-robust-dialogue-1","title":"ASSIST: Towards Label Noise-Robust Dialogue State Tracking","date":"2022-02-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"smartyfh/dst-assist","path":"STAR/models/DST.py","file_url":"https://github.com/smartyfh/dst-assist/blob/HEAD/STAR/models/DST.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"02fd36c752af5459","mcp_get_code":{"code_sha256":"02fd36c752af5459"}},{"arxiv_id":"2202.04298","paper":"/paper/image-difference-captioning-with-pre-training","title":"Image Difference Captioning with Pre-training and Contrastive Learning","date":"2022-02-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yaolinli/IDC","path":"bird/modules_pretrain_bird.py","file_url":"https://github.com/yaolinli/IDC/blob/HEAD/bird/modules_pretrain_bird.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"36faad4da521bc32","mcp_get_code":{"code_sha256":"36faad4da521bc32"}},{"arxiv_id":"2109.01862","paper":"/paper/pushing-paraphrase-away-from-original","title":"Pushing Paraphrase Away from Original Sentence: A Multi-Round Paraphrase Generation Approach","date":"2021-09-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"L-Zhe/BTmPG","path":"model/VAE.py","file_url":"https://github.com/L-Zhe/BTmPG/blob/HEAD/model/VAE.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"1048bbfb6e6d2ceb","mcp_get_code":{"code_sha256":"1048bbfb6e6d2ceb"}},{"arxiv_id":"2102.05095","paper":"/paper/is-space-time-attention-all-you-need-for","title":"Is Space-Time Attention All You Need for Video Understanding?","date":"2021-02-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jerrywn121/TianChi_AIEarth","path":"STTransformer/transformer.py","file_url":"https://github.com/jerrywn121/TianChi_AIEarth/blob/HEAD/STTransformer/transformer.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"2c2573860f1078bc","mcp_get_code":{"code_sha256":"2c2573860f1078bc"}},{"arxiv_id":"2010.16056","paper":"/paper/generating-radiology-reports-via-memory","title":"Generating Radiology Reports via Memory-driven Transformer","date":"2020-10-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"cuhksz-nlp/R2Gen","path":"modules/encoder_decoder.py","file_url":"https://github.com/cuhksz-nlp/R2Gen/blob/HEAD/modules/encoder_decoder.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"777d5cf5b297d69f","mcp_get_code":{"code_sha256":"777d5cf5b297d69f"}},{"arxiv_id":"2002.03912","paper":"/paper/a-probabilistic-formulation-of-unsupervised-1","title":"A Probabilistic Formulation of Unsupervised Text Style Transfer","date":"2020-02-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"thu-coai/NAST","path":"styletransformer/transformer.py","file_url":"https://github.com/thu-coai/NAST/blob/HEAD/styletransformer/transformer.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3e2638d464cbc25c","mcp_get_code":{"code_sha256":"3e2638d464cbc25c"}},{"arxiv_id":"1810.04805","paper":"/paper/bert-pre-training-of-deep-bidirectional","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","date":"2018-10-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"fanchenyou/transformer-study","path":"transformer_bert_from_scratch_5.py","file_url":"https://github.com/fanchenyou/transformer-study/blob/HEAD/transformer_bert_from_scratch_5.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"740ab852bb4af958","mcp_get_code":{"code_sha256":"740ab852bb4af958"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tbmoon/LANL_Earthquake_Prediction","path":"models.py","file_url":"https://github.com/tbmoon/LANL_Earthquake_Prediction/blob/HEAD/models.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"c1c1fcac165ebbbe","mcp_get_code":{"code_sha256":"c1c1fcac165ebbbe"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"WenYanger/General-Transformer-Pytorch","path":"Transformer.py","file_url":"https://github.com/WenYanger/General-Transformer-Pytorch/blob/HEAD/Transformer.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e3dd527ebadcc280","mcp_get_code":{"code_sha256":"e3dd527ebadcc280"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"harvardnlp/annotated-transformer","path":"the_annotated_transformer.py","file_url":"https://github.com/harvardnlp/annotated-transformer/blob/HEAD/the_annotated_transformer.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"5355a1e39fb57df9","mcp_get_code":{"code_sha256":"5355a1e39fb57df9"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"redevaaa/Transformer-for-EEG","path":"lib/eeg_transformer.py","file_url":"https://github.com/redevaaa/Transformer-for-EEG/blob/HEAD/lib/eeg_transformer.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"81d503b96d97cd7b","mcp_get_code":{"code_sha256":"81d503b96d97cd7b"}},{"arxiv_id":"1706.03762","paper":"/paper/attention-is-all-you-need","title":"Attention Is All You Need","date":"2017-06-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"moon23k/Transformer_Anchors","path":"model/scratch_model.py","file_url":"https://github.com/moon23k/Transformer_Anchors/blob/HEAD/model/scratch_model.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"60bcfaa11065f7db","mcp_get_code":{"code_sha256":"60bcfaa11065f7db"}}]}