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Find link is a tool written by Edward Betts.searching for Natural language generation 27 found (102 total)
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Naomi Sager
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ISBN 978-0-521-63198-3. Aspects of Automated Natural Language Generation: 6th International Workshop on Natural Language Generation Trento, Italy, April 5–7, 1992.OpenCog (1,250 words) [view diff] exact match in snippet view article find links to article
which encodes semantic and syntactic relations in Atomese. A natural language generation system. An implementation of Psi-Theory for handling emotionalGPT-3 (4,934 words) [view diff] case mismatch in snippet view article find links to article
web pages. In February 2020, Microsoft introduced its Turing Natural Language Generation (T-NLG), which they claimed was "largest language model everDiscourse relation (1,179 words) [view diff] case mismatch in snippet view article find links to article
Structure Theory: Description and Construction of Text Structures", Natural Language Generation: New Results in Artificial Intelligence, Psychology and LinguisticsRich Representation Language (1,068 words) [view diff] exact match in snippet view article find links to article
between various actions. The scene descriptions are fed to the natural language generation module which produces suitable sentences. The generation of naturalNeil McIntosh (paediatrician) (801 words) [view diff] exact match in snippet view article
graph is poorer than 100 words: A comparison of computerised natural language generation, human generated descriptions and graphical displays in neonatalAssociation for Computational Linguistics (876 words) [view diff] case mismatch in snippet view article find links to article
State Methods SIGGEN Archived 12 May 2008 at the Wayback Machine Natural Language Generation SIGHAN Chinese Language Processing SIGHUM Language TechnologiesSoar (cognitive architecture) (3,645 words) [view diff] exact match in snippet view article
"Real-time natural language generation in NL-Soar". INLG. Proceedings of the Seventh International Workshop on Natural Language Generation: 199–206. doi:10Richard P. Gabriel (919 words) [view diff] exact match in snippet view article find links to article
WAITS. He earned a PhD in computer science (on the topic of natural language generation); and he and his wife Kathy had a son. Around this time, he becameMagnetic Scrolls (1,711 words) [view diff] case mismatch in snippet view article find links to article
Publishing. p. 109. ISBN 9781501348976. Montfort, N. (2006). "Natural Language Generation and Narrative Variation in Interactive Fiction" (PDF). ProceedingsDigital poetry (2,134 words) [view diff] case mismatch in snippet view article find links to article
Proceedings of the INLG 2016 Workshop on Computational Creativity in Natural Language Generation: 61–70. doi:10.18653/v1/W16-5509. hdl:2318/1603816. S2CID 10752052Steve Young (software engineer) (980 words) [view diff] case mismatch in snippet view article
Tsung-Hsien Wen; et al. (2015). "Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems" (PDF). Proc EMNLP. arXiv:1508.01745Timeline of artificial intelligence (4,397 words) [view diff] case mismatch in snippet view article find links to article
"Web Semantics: Microsoft Project Turing introduces Turing Natural Language Generation (T-NLG)". Wired. ISSN 1059-1028. Archived from the original onRegina Barzilay (952 words) [view diff] case mismatch in snippet view article find links to article
Cohesion Models, with Applications to Text Summarization and Natural Language Generation". "Regina Barzilay, 34 / Teaching computers to read and write"Studies in Natural Language Processing (134 words) [view diff] case mismatch in snippet view article find links to article
Translator ISBN 0521770777 Reiter, E. & R. Dale 2000 Building Natural Language Generation Systems ISBN 0521620368 Rosner, M. & R. Johnson (eds) 1992 ComputationalJudgement of the German Federal Court of Justice on Google's autocomplete function (2,660 words) [view diff] no match in snippet view article find links to article
Telemedicus (2014). Retrieved 25.2.2016. See for example the "natural-language generation platform" "Quill" which is capable of creating a "convincinglyMarilyn Walker (439 words) [view diff] case mismatch in snippet view article find links to article
systems. She also pioneered the use of statistical NLP methods for Natural Language Generation with the development of the first statistical sentence plannerKnowledge Based Software Assistant (2,073 words) [view diff] exact match in snippet view article find links to article
ambiguous to serve as a good format for defining a system. However, natural language generation was seen to be feasible as a way to generate textual descriptionsAI alignment (11,666 words) [view diff] case mismatch in snippet view article find links to article
Fung, Pascale (February 1, 2022). "Survey of Hallucination in Natural Language Generation". ACM Computing Surveys. 55 (12): 1–38. arXiv:2202.03629. doi:10Active Intelligence Pte Ltd (394 words) [view diff] exact match in snippet view article find links to article
is an AI engine composed of natural language processing and natural language generation elements enabling financial institutions to connect with customersAndrzej Bogusławski (990 words) [view diff] exact match in snippet view article find links to article
lexicography. In the 1960s he hypothesised the emergence of natural language generation with the aid of elementary linguistic units. In the 1970s heTurkish grammar (8,987 words) [view diff] case mismatch in snippet view article find links to article
Turkish in Proceedings of the Seventh International Workshop on Natural Language Generation Pages 117–126 https://arxiv.org/abs/cmp-lg/9407017v1 Slobin,Hallucination (artificial intelligence) (4,557 words) [view diff] case mismatch in snippet view article
Andrea; Fung, Pascale (November 2022). "Survey of Hallucination in Natural Language Generation" (pdf). ACM Computing Surveys. 55 (12). Association for ComputingThe Pile (dataset) (1,225 words) [view diff] case mismatch in snippet view article
to train other models, including Microsoft's Megatron-Turing Natural Language Generation, Meta AI's Open Pre-trained Transformers, LLaMA, and GalacticaEleutherAI (2,810 words) [view diff] case mismatch in snippet view article find links to article
to train other models, including Microsoft's Megatron-Turing Natural Language Generation, Meta AI's Open Pre-trained Transformers, LLaMA, and GalacticaAdversarial stylometry (3,782 words) [view diff] case mismatch in snippet view article find links to article
Rewriting". Proceedings of the 12th International Conference on Natural Language Generation. pp. 247–257. doi:10.18653/v1/W19-8633. Zhai, Wanyue; RusertReinforcement learning from human feedback (4,911 words) [view diff] case mismatch in snippet view article find links to article
"Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation". arXiv:2305.00955 [cs.CL]. Xie, Tengyang; Jiang, Nan; Wang,