반응형 오늘의 자연어 처리572 [2023-03-12] 오늘의 자연어처리 Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback Large language models (LLMs) are used to generate content for a wide range of tasks, and are set to reach a growing audience in coming years due to integration in product interfaces like ChatGPT or search engines like Bing. This intensifies the need to ensure .. 2023. 3. 12. [2023-03-11] 오늘의 자연어처리 Disambiguation of Company names via Deep Recurrent Networks Name Entity Disambiguation is the Natural Language Processing task of identifying textual records corresponding to the same Named Entity, i.e. real-world entities represented as a list of attributes (names, places, organisations, etc.). In this work, we face the task of disambiguating companies on the basis of their written names. We pr.. 2023. 3. 11. [2023-03-10] 오늘의 자연어처리 CroCoSum: A Benchmark Dataset for Cross-Lingual Code-Switched Summarization Cross-lingual summarization (CLS) has attracted increasing interest in recent years due to the availability of large-scale web-mined datasets and the advancements of multilingual language models. However, given the rareness of naturally occurring CLS resources, the majority of datasets are forced to rely on translation w.. 2023. 3. 10. [2023-03-09] 오늘의 자연어처리 A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its impressive performance. In fact, ChatGPT and other Gene.. 2023. 3. 9. 이전 1 ··· 77 78 79 80 81 82 83 ··· 143 다음 반응형