{"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/learning-to-encode-text-as-human-readable","title":"Learning to Encode Text as Human-Readable Summaries using Generative Adversarial Networks","arxiv_id":"1810.02851","date":"2018-10-05","proceeding":"EMNLP 2018 10","authors":["Yau-Shian Wang","Hung-Yi Lee"],"abstract":"Auto-encoders compress input data into a latent-space representation and\nreconstruct the original data from the representation. This latent\nrepresentation is not easily interpreted by humans. In this paper, we propose\ntraining an auto-encoder that encodes input text into human-readable sentences,\nand unpaired abstractive summarization is thereby achieved. The auto-encoder is\ncomposed of a generator and a reconstructor. The generator encodes the input\ntext into a shorter word sequence, and the reconstructor recovers the generator\ninput from the generator output. To make the generator output human-readable, a\ndiscriminator restricts the output of the generator to resemble human-written\nsentences. By taking the generator output as the summary of the input text,\nabstractive summarization is achieved without document-summary pairs as\ntraining data. Promising results are shown on both English and Chinese corpora.","url_abs":"http://arxiv.org/abs/1810.02851v1","url_pdf":"http://arxiv.org/pdf/1810.02851v1.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":"learning-to-encode-text-as-human-readable","repo_url":"https://github.com/yaushian/Unparalleled-Text-Summarization-using-GAN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"abstractive-text-summarization","task_name":"Abstractive Text Summarization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1810.02851","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1810.02851"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+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/yaushian/Unparalleled-Text-Summarization-using-GAN","reach":null}],"summary":{"ran_draft_wrong":1,"ran_violates":1},"by_repo_kind":{"listed":{"samples":2,"ran":2,"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":2,"samples":[{"code_sha256_prefix":"c204acb9ea9e761d","entry":"read_json","repo":"yaushian/Unparalleled-Text-Summarization-using-GAN","repo_kind":"listed","path":"make_pretrain.py","file_url":"https://github.com/yaushian/Unparalleled-Text-Summarization-using-GAN/blob/HEAD/make_pretrain.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"c204acb9ea9e761d"}},{"code_sha256_prefix":"9b500ce7cd81a36f","entry":"swap","repo":"yaushian/Unparalleled-Text-Summarization-using-GAN","repo_kind":"listed","path":"make_pretrain.py","file_url":"https://github.com/yaushian/Unparalleled-Text-Summarization-using-GAN/blob/HEAD/make_pretrain.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"9b500ce7cd81a36f"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}