{"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":"/paper/a-langevin-like-sampler-for-discrete","title":"A Langevin-like Sampler for Discrete Distributions","arxiv_id":"2206.09914","date":"2022-06-20","proceeding":null,"authors":["Ruqi Zhang","Xingchao Liu","Qiang Liu"],"abstract":"We propose discrete Langevin proposal (DLP), a simple and scalable gradient-based proposal for sampling complex high-dimensional discrete distributions. In contrast to Gibbs sampling-based methods, DLP is able to update all coordinates in parallel in a single step and the magnitude of changes is controlled by a stepsize. This allows a cheap and efficient exploration in the space of high-dimensional and strongly correlated variables. We prove the efficiency of DLP by showing that the asymptotic bias of its stationary distribution is zero for log-quadratic distributions, and is small for distributions that are close to being log-quadratic. With DLP, we develop several variants of sampling algorithms, including unadjusted, Metropolis-adjusted, stochastic and preconditioned versions. DLP outperforms many popular alternatives on a wide variety of tasks, including Ising models, restricted Boltzmann machines, deep energy-based models, binary neural networks and language generation.","url_abs":"https://arxiv.org/abs/2206.09914v1","url_pdf":"https://arxiv.org/pdf/2206.09914v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"a-langevin-like-sampler-for-discrete","repo_url":"https://github.com/ruqizhang/discrete-langevin","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"efficient-exploration","task_name":"Efficient Exploration"},{"task_slug":"text-generation","task_name":"Text Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2206.09914","atlas_url":"https://app.syntology.ai/?focus=2206.09914","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.09914"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/ruqizhang/discrete-langevin","reach":null}],"summary":{"ran":1,"ran_honours":1,"ran_draft_wrong":1},"by_repo_kind":{"official":{"samples":3,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":3,"samples":[{"code_sha256_prefix":"bdda7af5a7789767","entry":"DiffSampler","repo":"ruqizhang/discrete-langevin","repo_kind":"official","path":"samplers.py","file_url":"https://github.com/ruqizhang/discrete-langevin/blob/HEAD/samplers.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"bdda7af5a7789767"}},{"code_sha256_prefix":"fcaf75203fcaccf7","entry":"get_gt_mean","repo":"ruqizhang/discrete-langevin","repo_kind":"official","path":"ising_sample.py","file_url":"https://github.com/ruqizhang/discrete-langevin/blob/HEAD/ising_sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"fcaf75203fcaccf7"}},{"code_sha256_prefix":"a02110a4efcbc845","entry":"get_log_rmse","repo":"ruqizhang/discrete-langevin","repo_kind":"official","path":"ising_sample.py","file_url":"https://github.com/ruqizhang/discrete-langevin/blob/HEAD/ising_sample.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"a02110a4efcbc845"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}