| RetGen: A Joint Framework for Retrieval and Grounded Text Generation Modeling. | 0 | 0.34 | 2022 |
| Contextualized Perturbation for Textual Adversarial Attack | 0 | 0.34 | 2021 |
| Automatic Document Sketching - Generating Drafts from Analogous Texts. | 0 | 0.34 | 2021 |
| Text Editing by Command | 0 | 0.34 | 2021 |
| A Controllable Model Of Grounded Response Generation | 0 | 0.34 | 2021 |
| A Recipe for Creating Multimodal Aligned Datasets for Sequential Tasks | 0 | 0.34 | 2020 |
| Dialogue Response Ranking Training with Large-Scale Human Feedback Data. | 0 | 0.34 | 2020 |
| POINTER: Constrained Progressive Text Generation via Insertion-based Generative Pre-training. | 1 | 0.35 | 2020 |
| Domain Adaptive Text Style Transfer | 3 | 0.36 | 2019 |
| Microsoft Icecaps: An Open-Source Toolkit For Conversation Modeling | 0 | 0.34 | 2019 |
| Structuring latent spaces for stylized response generation | 0 | 0.34 | 2019 |
| Consistent Dialogue Generation with Self-supervised Feature Learning. | 1 | 0.35 | 2019 |
| Jointly Optimizing Diversity and Relevance in Neural Response Generation. | 1 | 0.35 | 2019 |
| Generating a Common Question from Multiple Documents using Multi-source Encoder-Decoder Models. | 0 | 0.34 | 2019 |
| Dialog System Technology Challenge 7. | 0 | 0.34 | 2019 |
| A Knowledge-Grounded Neural Conversation Model. | 30 | 0.93 | 2018 |
| Emotional Dialogue Generation using Image-Grounded Language Models | 7 | 0.45 | 2018 |
| Generating Informative and Diverse Conversational Responses via Adversarial Information Maximization. | 8 | 0.44 | 2018 |
| Vision-Based Navigation With Language-Based Assistance Via Imitation Learning With Indirect Intervention | 3 | 0.37 | 2018 |
| Image-Grounded Conversations: Multimodal Context for Natural Question and Response Generation. | 14 | 0.58 | 2017 |
| Multi-Task Learning for Speaker-Role Adaptation in Neural Conversation Models. | 10 | 0.46 | 2017 |
| Steering Output Style and Topic in Neural Response Generation. | 9 | 0.50 | 2017 |
| A Persona-Based Neural Conversation Model | 29 | 1.19 | 2016 |
| Emulating Human Conversations using Convolutional Neural Network-based IR. | 5 | 0.49 | 2016 |
| A Dataset and Evaluation Metrics for Abstractive Compression of Sentences and Short Paragraphs. | 5 | 0.44 | 2016 |
| A Neural Network Approach to Context-Sensitive Generation of Conversational Responses | 180 | 6.33 | 2015 |
| A Diversity-Promoting Objective Function for Neural Conversation Models | 182 | 5.01 | 2015 |
| Diverse Words, Shared Meanings: Statistical Machine Translation for Paraphrase, Grounding, and Intent | 0 | 0.34 | 2012 |
| Hitting the right paraphrases in good time | 29 | 1.04 | 2010 |
| User input and interactions on Microsoft Research ESL Assistant | 7 | 0.60 | 2009 |
| Beyond SumBasic: Task-focused summarization with sentence simplification and lexical expansion | 84 | 2.80 | 2007 |
| Correcting ESL errors using phrasal SMT techniques | 94 | 4.32 | 2006 |
| Echo Chamber: A Game for Eliciting a Colloquial Paraphrase Corpus. | 3 | 0.53 | 2005 |
| Automatically Constructing a Corpus of Sentential Paraphrases | 93 | 2.92 | 2005 |
| Support Vector Machines for Paraphrase Identification and Corpus Construction | 25 | 1.36 | 2005 |
| Monolingual Machine Translation for Paraphrase Generation | 132 | 5.48 | 2004 |
| Unsupervised construction of large paraphrase corpora: exploiting massively parallel news sources | 304 | 17.80 | 2004 |
| A machine learning approach to the automatic evaluation of machine translation | 32 | 3.10 | 2001 |
| Automatically Harvesting Katakana-English Term Pairs from Search Engine Query Logs | 47 | 2.54 | 2001 |
| Robust segmentation of Japanese text into a lattice for parsing | 2 | 0.44 | 2000 |
| Using a broad-coverage parser for word-breaking in Japanese | 2 | 0.49 | 2000 |
