{"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/dynamic-fusion-network-for-multi-domain-end","title":"Dynamic Fusion Network for Multi-Domain End-to-end Task-Oriented Dialog","arxiv_id":"2004.11019","date":"2020-04-23","proceeding":"ACL 2020 6","authors":["Libo Qin","Xiao Xu","Wanxiang Che","Yue Zhang","Ting Liu"],"abstract":"Recent studies have shown remarkable success in end-to-end task-oriented dialog system. However, most neural models rely on large training data, which are only available for a certain number of task domains, such as navigation and scheduling. This makes it difficult to scalable for a new domain with limited labeled data. However, there has been relatively little research on how to effectively use data from all domains to improve the performance of each domain and also unseen domains. To this end, we investigate methods that can make explicit use of domain knowledge and introduce a shared-private network to learn shared and specific knowledge. In addition, we propose a novel Dynamic Fusion Network (DF-Net) which automatically exploit the relevance between the target domain and each domain. Results show that our model outperforms existing methods on multi-domain dialogue, giving the state-of-the-art in the literature. Besides, with little training data, we show its transferability by outperforming prior best model by 13.9\\% on average.","url_abs":"https://arxiv.org/abs/2004.11019v3","url_pdf":"https://arxiv.org/pdf/2004.11019v3.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":"dynamic-fusion-network-for-multi-domain-end","repo_url":"https://github.com/LooperXX/DF-Net","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"scheduling","task_name":"Scheduling"},{"task_slug":"task-oriented-dialogue-systems","task_name":"Task-Oriented Dialogue Systems"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/task-oriented-dialogue-systems-on-kvret","task":"Task-Oriented Dialogue Systems","dataset":"KVRET","model":"DF-Net","rank_in_archive_order":3,"of":10,"metrics":{"BLEU":"15.2","Entity F1":"62.5"},"uses_additional_data":false},{"leaderboard":"/sota/task-oriented-dialogue-systems-on-kvret-1","task":"Task-Oriented Dialogue Systems","dataset":"Kvret","model":"DF-Net","rank_in_archive_order":1,"of":1,"metrics":{"Entity F1":"62.7"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2004.11019","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2004.11019"}},"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":"deterministic:regex_extraction","url":"https://github.com/LooperXX/DF-Net","reach":null}],"summary":{"unverified":1},"by_repo_kind":{"official":{"samples":1,"ran":0,"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":1,"samples":[{"code_sha256_prefix":"e703ecc564ae027a","entry":"DFNet","repo":"LooperXX/DF-Net","repo_kind":"official","path":"models/model.py","file_url":"https://github.com/LooperXX/DF-Net/blob/HEAD/models/model.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"e703ecc564ae027a"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}