{"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/beam-search","entry":"beam_search","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":25,"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":24,"n_samples_ran":3,"n_samples_fingerprinted":1,"n_places":26,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":2,"ran_fixture":0,"ran":1,"unverified":21},"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":"2411.07428","paper":"/paper/just-label-the-repeats-for-in-the-wild-audio","title":"Just Label the Repeats for In-The-Wild Audio-to-Score Alignment","date":"2024-11-11","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"irmakbky/jltr-alignment","path":"magenta/common/beam_search.py","file_url":"https://github.com/irmakbky/jltr-alignment/blob/HEAD/magenta/common/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fc965e87e24dc01d","mcp_get_code":{"code_sha256":"fc965e87e24dc01d"}},{"arxiv_id":"2405.19100","paper":"/paper/enhancing-zero-shot-facial-expression","title":"Enhancing Zero-Shot Facial Expression Recognition by LLM Knowledge Transfer","date":"2024-05-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zengqunzhao/exp-clip","path":"models/BLIP2_T5.py","file_url":"https://github.com/zengqunzhao/exp-clip/blob/HEAD/models/BLIP2_T5.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"9a9839a0184a9bc9","mcp_get_code":{"code_sha256":"9a9839a0184a9bc9"}},{"arxiv_id":"2312.16045","paper":"/paper/algebraic-positional-encodings","title":"Algebraic Positional Encodings","date":"2023-12-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"konstantinoskokos/unitarype","path":"eval/models/nmt/base.py","file_url":"https://github.com/konstantinoskokos/unitarype/blob/HEAD/eval/models/nmt/base.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"CC-BY-SA-4.0","inline_ok":false,"code_sha256_prefix":"1b5b1a8a40b47b92","mcp_get_code":{"code_sha256":"1b5b1a8a40b47b92"}},{"arxiv_id":"2312.12469","paper":"/paper/distilling-autoregressive-models-to-obtain","title":"Distilling Autoregressive Models to Obtain High-Performance Non-Autoregressive Solvers for Vehicle Routing Problems with Faster Inference Speed","date":"2023-12-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xybfight/gnarkd","path":"GNARKD-POMO/TSP/Test_file.py","file_url":"https://github.com/xybfight/gnarkd/blob/HEAD/GNARKD-POMO/TSP/Test_file.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"d9ac4f54def47957","mcp_get_code":{"code_sha256":"d9ac4f54def47957"}},{"arxiv_id":"2310.18443","paper":"/paper/towards-a-fuller-understanding-of-neurons-1","title":"Towards a fuller understanding of neurons with Clustered Compositional Explanations","date":"2023-10-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"krlgroup/clustered-compositional-explanations","path":"src/heuristic_search.py","file_url":"https://github.com/krlgroup/clustered-compositional-explanations/blob/HEAD/src/heuristic_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"4cbadf168b410b2a","mcp_get_code":{"code_sha256":"4cbadf168b410b2a"}},{"arxiv_id":"2306.14256","paper":"/paper/a-multilingual-translator-to-sql-with","title":"A Multilingual Translator to SQL with Database Schema Pruning to Improve Self-Attention","date":"2023-06-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"c4ai/gap-text2sql","path":"mrat-sql-gap/seq2struct/beam_search.py","file_url":"https://github.com/c4ai/gap-text2sql/blob/HEAD/mrat-sql-gap/seq2struct/beam_search.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":"7be6d4f60f88de6f","mcp_get_code":{"code_sha256":"7be6d4f60f88de6f"}},{"arxiv_id":"2207.00301","paper":"/paper/can-we-learn-from-developer-mistakes-learning","title":"Can we learn from developer mistakes? Learning to localize and repair real bugs from real bug fixes","date":"2022-07-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"cedricrupb/nbfbaselines","path":"nbfbaselines/nbfbase.py","file_url":"https://github.com/cedricrupb/nbfbaselines/blob/HEAD/nbfbaselines/nbfbase.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3de1111ec7a95d67","mcp_get_code":{"code_sha256":"3de1111ec7a95d67"}},{"arxiv_id":"2203.10452","paper":"/paper/crossbeam-learning-to-search-in-bottom-up-1","title":"CrossBeam: Learning to Search in Bottom-Up Program Synthesis","date":"2022-03-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"google-research/crossbeam","path":"crossbeam/algorithm/synthesis.py","file_url":"https://github.com/google-research/crossbeam/blob/HEAD/crossbeam/algorithm/synthesis.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"d66de1c630616a06","mcp_get_code":{"code_sha256":"d66de1c630616a06"}},{"arxiv_id":"2203.09509","paper":"/paper/toxigen-a-large-scale-machine-generated","title":"ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection","date":"2022-03-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"microsoft/toxigen","path":"toxigen/alice.py","file_url":"https://github.com/microsoft/toxigen/blob/HEAD/toxigen/alice.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"9211eff610499042","mcp_get_code":{"code_sha256":"9211eff610499042"}},{"arxiv_id":"2110.15797","paper":"/paper/discovering-non-monotonic-autoregressive","title":"Discovering Non-monotonic Autoregressive Orderings with Variational Inference","date":"2021-10-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xuanlinli17/autoregressive_inference","path":"voi/algorithms/beam_search.py","file_url":"https://github.com/xuanlinli17/autoregressive_inference/blob/HEAD/voi/algorithms/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ec90483fc2b722f6","mcp_get_code":{"code_sha256":"ec90483fc2b722f6"}},{"arxiv_id":"2109.03792","paper":"/paper/highly-parallel-autoregressive-entity-linking","title":"Highly Parallel Autoregressive Entity Linking with Discriminative Correction","date":"2021-09-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nicola-decao/efficient-autoregressive-EL","path":"src/beam_search.py","file_url":"https://github.com/nicola-decao/efficient-autoregressive-EL/blob/HEAD/src/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f8d1fe362ffd1e5e","mcp_get_code":{"code_sha256":"f8d1fe362ffd1e5e"}},{"arxiv_id":"2107.05697","paper":"/paper/few-shot-language-coordination-by-modeling","title":"Few-shot Language Coordination by Modeling Theory of Mind","date":"2021-07-12","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"CLAW-Lab/ToM","path":"ibr_game/beam_search.py","file_url":"https://github.com/CLAW-Lab/ToM/blob/HEAD/ibr_game/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"aa908768350f33fc","mcp_get_code":{"code_sha256":"aa908768350f33fc"}},{"arxiv_id":"2106.02039","paper":"/paper/reinforcement-learning-as-one-big-sequence","title":"Offline Reinforcement Learning as One Big Sequence Modeling Problem","date":"2021-06-03","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"JannerM/trajectory-transformer","path":"trajectory/search/core.py","file_url":"https://github.com/JannerM/trajectory-transformer/blob/HEAD/trajectory/search/core.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"c6b3fddb40879156","mcp_get_code":{"code_sha256":"c6b3fddb40879156"}},{"arxiv_id":"2007.08742","paper":"/paper/a-novel-graph-based-multi-modal-fusion-1","title":"A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation","date":"2020-07-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"middlekisser/GMNMT","path":"model/generator.py","file_url":"https://github.com/middlekisser/GMNMT/blob/HEAD/model/generator.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"80b47e9d3749347c","mcp_get_code":{"code_sha256":"80b47e9d3749347c"}},{"arxiv_id":"2007.06943","paper":"/paper/modeling-voting-for-system-combination-in","title":"Modeling Voting for System Combination in Machine Translation","date":"2020-07-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"THUNLP-MT/THUMT","path":"thumt/utils/inference.py","file_url":"https://github.com/THUNLP-MT/THUMT/blob/HEAD/thumt/utils/inference.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"BSD-3-Clause","inline_ok":true,"code_sha256_prefix":"5ca040d32880306a","mcp_get_code":{"code_sha256":"5ca040d32880306a"}},{"arxiv_id":"1912.08777","paper":"/paper/pegasus-pre-training-with-extracted-gap","title":"PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization","date":"2019-12-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"google-research/pegasus","path":"pegasus/layers/beam_search.py","file_url":"https://github.com/google-research/pegasus/blob/HEAD/pegasus/layers/beam_search.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":"f57d0063335e8a9b","mcp_get_code":{"code_sha256":"f57d0063335e8a9b"}},{"arxiv_id":"1912.08777","paper":"/paper/pegasus-pre-training-with-extracted-gap","title":"PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization","date":"2019-12-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"amiyamandal-dev/pegasus","path":"pegasus/layers/beam_search.py","file_url":"https://github.com/amiyamandal-dev/pegasus/blob/HEAD/pegasus/layers/beam_search.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":"e631e67cdf964175","mcp_get_code":{"code_sha256":"e631e67cdf964175"}},{"arxiv_id":"1911.04942","paper":"/paper/rat-sql-relation-aware-schema-encoding-and-1","title":"RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers","date":"2019-11-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Microsoft/rat-sql","path":"ratsql/beam_search.py","file_url":"https://github.com/Microsoft/rat-sql/blob/HEAD/ratsql/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3c377f8696988de8","mcp_get_code":{"code_sha256":"3c377f8696988de8"}},{"arxiv_id":"1907.04138","paper":"/paper/characterization-of-overlap-in-observational","title":"Characterization of Overlap in Observational Studies","date":"2019-07-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"clinicalml/overlap-code","path":"overrule/BCS/beam_search.py","file_url":"https://github.com/clinicalml/overlap-code/blob/HEAD/overrule/BCS/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"02dc109ffee84309","mcp_get_code":{"code_sha256":"02dc109ffee84309"}},{"arxiv_id":"1904.02632","paper":"/paper/a-learned-representation-for-scalable-vector","title":"A Learned Representation for Scalable Vector Graphics","date":"2019-04-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tensorflow/magenta","path":"magenta/common/beam_search.py","file_url":"https://github.com/tensorflow/magenta/blob/HEAD/magenta/common/beam_search.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":"fc965e87e24dc01d","mcp_get_code":{"code_sha256":"fc965e87e24dc01d"}},{"arxiv_id":"1901.04112","paper":"/paper/unsupervised-neural-machine-translation-with","title":"Unsupervised Neural Machine Translation with SMT as Posterior Regularization","date":"2019-01-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Imagist-Shuo/UNMT-SPR","path":"t2tlight/models/beamsearch.py","file_url":"https://github.com/Imagist-Shuo/UNMT-SPR/blob/HEAD/t2tlight/models/beamsearch.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"922e19f82ba4a0c8","mcp_get_code":{"code_sha256":"922e19f82ba4a0c8"}},{"arxiv_id":"1808.10122","paper":"/paper/learning-neural-templates-for-text-generation","title":"Learning Neural Templates for Text Generation","date":"2018-08-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"TobeyYang/S2S_Temp","path":"generate.py","file_url":"https://github.com/TobeyYang/S2S_Temp/blob/HEAD/generate.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":"2b7644a99136563a","mcp_get_code":{"code_sha256":"2b7644a99136563a"}},{"arxiv_id":"1804.09399","paper":"/paper/convolutional-generative-adversarial-networks","title":"Convolutional Generative Adversarial Networks with Binary Neurons for Polyphonic Music Generation","date":"2018-04-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"lucylow/Stochastic_SoundCloud","path":"common/beam_search.py","file_url":"https://github.com/lucylow/Stochastic_SoundCloud/blob/HEAD/common/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"fc965e87e24dc01d","mcp_get_code":{"code_sha256":"fc965e87e24dc01d"}},{"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":"demelin/nematode","path":"codebase/transformer.py","file_url":"https://github.com/demelin/nematode/blob/HEAD/codebase/transformer.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"67a85dfd520243e6","mcp_get_code":{"code_sha256":"67a85dfd520243e6"}},{"arxiv_id":"1508.01211","paper":"/paper/listen-attend-and-spell","title":"Listen, Attend and Spell","date":"2015-08-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"anjandeepsahni/automatic_speech_recognition","path":"Code/beamsearch.py","file_url":"https://github.com/anjandeepsahni/automatic_speech_recognition/blob/HEAD/Code/beamsearch.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"515dc628f1216f81","mcp_get_code":{"code_sha256":"515dc628f1216f81"}},{"arxiv_id":"1411.4555","paper":"/paper/show-and-tell-a-neural-image-caption","title":"Show and Tell: A Neural Image Caption Generator","date":"2014-11-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"guptakhil12/show-tell","path":"beam_search.py","file_url":"https://github.com/guptakhil12/show-tell/blob/HEAD/beam_search.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3b20293ce047ab05","mcp_get_code":{"code_sha256":"3b20293ce047ab05"}}]}