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We introduce Hybrid\nCode Networks (HCNs), which combine an RNN with domain-specific knowledge\nencoded as software and system action templates. Compared to existing\nend-to-end approaches, HCNs considerably reduce the amount of training data\nrequired, while retaining the key benefit of inferring a latent representation\nof dialog state. In addition, HCNs can be optimized with supervised learning,\nreinforcement learning, or a mixture of both. HCNs attain state-of-the-art\nperformance on the bAbI dialog dataset, and outperform two commercially\ndeployed customer-facing dialog systems.","url_abs":"http://arxiv.org/abs/1702.03274v2","url_pdf":"http://arxiv.org/pdf/1702.03274v2.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":"hybrid-code-networks-practical-and-efficient","repo_url":"https://github.com/deepmipt/DeepPavlov","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"hybrid-code-networks-practical-and-efficient","repo_url":"https://github.com/jojonki/hybrid-code-networks","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"hybrid-code-networks-practical-and-efficient","repo_url":"https://github.com/zayedshah/Dumping-Green","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"},{"task_slug":"reinforcement-learning-1","task_name":"Reinforcement Learning (RL)"},{"task_slug":"reinforcement-learning-2","task_name":"reinforcement-learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1702.03274","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1702.03274"}},"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. 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