{"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/ask-me-anything-dynamic-memory-networks-for","title":"Ask Me Anything: Dynamic Memory Networks for Natural Language Processing","arxiv_id":"1506.07285","date":"2015-06-24","proceeding":null,"authors":["Ankit Kumar","Ozan .Irsoy","Peter Ondruska","Mohit Iyyer","James Bradbury","Ishaan Gulrajani","Victor Zhong","Romain Paulus","Richard Socher"],"abstract":"Most tasks in natural language processing can be cast into question answering\n(QA) problems over language input. We introduce the dynamic memory network\n(DMN), a neural network architecture which processes input sequences and\nquestions, forms episodic memories, and generates relevant answers. Questions\ntrigger an iterative attention process which allows the model to condition its\nattention on the inputs and the result of previous iterations. These results\nare then reasoned over in a hierarchical recurrent sequence model to generate\nanswers. The DMN can be trained end-to-end and obtains state-of-the-art results\non several types of tasks and datasets: question answering (Facebook's bAbI\ndataset), text classification for sentiment analysis (Stanford Sentiment\nTreebank) and sequence modeling for part-of-speech tagging (WSJ-PTB). The\ntraining for these different tasks relies exclusively on trained word vector\nrepresentations and input-question-answer triplets.","url_abs":"http://arxiv.org/abs/1506.07285v5","url_pdf":"http://arxiv.org/pdf/1506.07285v5.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":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/Asteur/someChatbot","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/DongjunLee/dmn-tensorflow","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/ajenningsfrankston/Dynamic-Memory-Network-Plus-master","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/jxz542189/dmn_plus","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/macco3k/deepstories","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/mindspore-courses/DeepNLP-models-MindSpore","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"mindspore","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/navodhya/DMN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/rgsachin/DMTN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/scakc/QAwiki","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"ask-me-anything-dynamic-memory-networks-for","repo_url":"https://github.com/vchudinov/dynamic_memory_networks_with_keras","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"GPL-3.0"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"part-of-speech-tagging","task_name":"Part-Of-Speech Tagging"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"sentiment-analysis","task_name":"Sentiment Analysis"},{"task_slug":"text-classification","task_name":"Text Classification"}],"methods":[{"method_slug":"dynamic-memory-network","method_name":"Dynamic Memory Network"},{"method_slug":"gru","method_name":"GRU"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[{"slug":"dynamic-memory-network","name":"Dynamic Memory Network","full_name":"Dynamic Memory Network"}],"results":[{"leaderboard":"/sota/sentiment-analysis-on-sst-2-binary","task":"Sentiment Analysis","dataset":"SST-2 Binary classification","model":"DMN [ankit16]","rank_in_archive_order":66,"of":87,"metrics":{"Accuracy":"88.6"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1506.07285","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1506.07285"}},"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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