mlsanityData to 7 Oct 2026

Efficient Natural Language Response Suggestion for Smart Reply

arXiv 1705.00652 ↗First posted 1 May 2017cs.CLcited by 228

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Abstract (arXiv)

This paper presents a computationally efficient machine-learned method for natural language response suggestion. Feed-forward neural networks using n-gram embedding features encode messages into vectors which are optimized to give message-response pairs a high dot-product value. An optimized search finds response suggestions. The method is evaluated in a large-scale commercial e-mail application, Inbox by Gmail. Compared to a sequence-to-sequence approach, the new system achieves the same quality at a small fraction of the computational requirements and latency.

Key facts. Cited by 228 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 May 2017.

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Citing papers per year: 2021: 30; 2022: 40; 2023: 37; 2024: 48; 2025: 40; 2026: 33.

228 papers.

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  1. 2021SimCSE: Simple Contrastive Learning of Sentence Embeddingscited by 2,168
  2. 2021Learning To Retrieve Prompts for In-Context Learningcited by 641
  3. 2021Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Modelscited by 462
  4. 2021Large Dual Encoders Are Generalizable Retrieverscited by 454
  5. 2021RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-rankingcited by 175
  6. 2024A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systemscited by 170
  7. 2021GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrievalcited by 119
  8. 2021TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learningcited by 116
  9. 2021CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIPcited by 88
  10. 2021Open Domain Question Answering over Tables via Dense Retrievalcited by 74
  11. 2021PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrievalcited by 50
  12. 2021LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrievalcited by 44
38 more
  1. 2021A Statutory Article Retrieval Dataset in Frenchcited by 40
  2. 2024GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuningcited by 40
  3. 2023TPTU-v2: Boosting Task Planning and Tool Usage of Large Language Model-based Agents in Real-world Systemscited by 39
  4. 2025A Survey of Multimodal Retrieval-Augmented Generationcited by 37
  5. 2022SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embeddingcited by 36
  6. 2023Interpretable Long-Form Legal Question Answering with Retrieval-Augmented Large Language Modelscited by 35
  7. 2022Speaking Multiple Languages Affects the Moral Bias of Language Modelscited by 34
  8. 2024The Chronicles of RAG: The Retriever, the Chunk and the Generatorcited by 34
  9. 2022UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Miningcited by 33
  10. 2023QUEST: A Retrieval Dataset of Entity-Seeking Queries with Implicit Set Operationscited by 30
  11. 2022Non-Contrastive Learning Meets Language-Image Pre-Trainingcited by 25
  12. 2021A Proposed Conceptual Framework for a Representational Approach to Information Retrievalcited by 24
  13. 2022LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrievalcited by 24
  14. 2022Decoupled Context Processing for Context Augmented Language Modelingcited by 24
  15. 2021Artificial intelligence in communication impacts language and social relationshipscited by 22
  16. 2024Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERTcited by 21
  17. 2023Improving Hateful Meme Detection through Retrieval-Guided Contrastive Learningcited by 20
  18. 2021DialogueCSE: Dialogue-based Contrastive Learning of Sentence Embeddingscited by 19
  19. 2022Exploring Dual Encoder Architectures for Question Answeringcited by 19
  20. 2022E2S2: Encoding-Enhanced Sequence-to-Sequence Pretraining for Language Understanding and Generationcited by 19
  21. 2024Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?cited by 19
  22. 2022Noise-Robust De-Duplication at Scalecited by 17
  23. 2023Extreme Multi-Label Skill Extraction Training using Large Language Modelscited by 17
  24. 2021Learning to Select External Knowledge with Multi-Scale Negative Samplingcited by 16
  25. 2022Few-Shot Learning with Siamese Networks and Label Tuningcited by 15
  26. 2022DeepJoin: Joinable Table Discovery with Pre-trained Language Modelscited by 15
  27. 2023One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Supportcited by 15
  28. 2024PIRB: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methodscited by 14
  29. 2024MeanCache: User-Centric Semantic Caching for LLM Web Servicescited by 14
  30. 2022Retweet-BERT: Political Leaning Detection Using Language Features and Information Diffusion on Social Networkscited by 13
  31. 2022RedHOT: A Corpus of Annotated Medical Questions, Experiences, and Claims on Social Mediacited by 13
  32. 2022Specialized Document Embeddings for Aspect-based Similarity of Research Paperscited by 12
  33. 2022Don't Judge a Language Model by Its Last Layer: Contrastive Learning with Layer-Wise Attention Poolingcited by 12
  34. 2024Deep Learning-based Computational Job Market Analysis: A Survey on Skill Extraction and Classification from Job Postingscited by 12
  35. 2022Training Effective Neural Sentence Encoders from Automatically Mined Paraphrasescited by 11
  36. 2023Social-LLM: Modeling User Behavior at Scale using Language Models and Social Network Datacited by 11
  37. 2024Generative Dense Retrieval: Memory Can Be a Burdencited by 11
  38. 2021Unsupervised Contextual Paraphrase Generation using Lexical Control and Reinforcement Learningcited by 10

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