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Yet it is limited because it cannot\noutput interpretable actions as in traditional systems, which hinders humans\nfrom understanding its generation process. We present an unsupervised discrete\nsentence representation learning method that can integrate with any existing\nencoder-decoder dialog models for interpretable response generation. Building\nupon variational autoencoders (VAEs), we present two novel models, DI-VAE and\nDI-VST that improve VAEs and can discover interpretable semantics via either\nauto encoding or context predicting. Our methods have been validated on\nreal-world dialog datasets to discover semantic representations and enhance\nencoder-decoder models with interpretable generation.","url_abs":"http://arxiv.org/abs/1804.08069v1","url_pdf":"http://arxiv.org/pdf/1804.08069v1.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":"unsupervised-discrete-sentence-representation","repo_url":"https://github.com/snakeztc/NeuralDialog-LAED","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"unsupervised-discrete-sentence-representation","repo_url":"https://github.com/ShiminLei/LA-Dialog-Generation-System","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"dialogue-generation","task_name":"Dialogue Generation"},{"task_slug":"dialogue-interpretation","task_name":"Dialogue Interpretation"},{"task_slug":"representation-learning","task_name":"Representation Learning"},{"task_slug":"response-generation","task_name":"Response Generation"},{"task_slug":"sentence","task_name":"Sentence"},{"task_slug":"text-generation","task_name":"Text Generation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1804.08069","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1804.08069"}},"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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