반응형 자연어처리572 [2022-09-24] 오늘의 자연어처리 Approaching English-Polish Machine Translation Quality Assessment with Neural-based Methods This paper presents our contribution to the PolEval 2021 Task 2: Evaluation of translation quality assessment metrics. We describe experiments with pre-trained language models and state-of-the-art frameworks for translation quality assessment in both nonblind and blind versions of the task. Our solutions .. 2022. 9. 24. [2022-09-23] 오늘의 자연어처리 Setting the rhythm scene: deep learning-based drum loop generation from arbitrary language cues Generative artificial intelligence models can be a valuable aid to music composition and live performance, both to aid the professional musician and to help democratize the music creation process for hobbyists. Here we present a novel method that, given an English word or phrase, generates 2 compasses.. 2022. 9. 23. [2022-09-22] 오늘의 자연어처리 Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering When answering a question, humans utilize the information available across different modalities to synthesize a consistent and complete chain of thought (CoT). This process is normally a black box in the case of deep learning models like large-scale language models. Recently, science question benchmarks have.. 2022. 9. 22. [2022-09-21] 오늘의 자연어처리 ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification Lexical simplification (LS) is the task of automatically replacing complex words for easier ones making texts more accessible to various target populations (e.g. individuals with low literacy, individuals with learning disabilities, second language learners). To train and test models, LS systems usually require corpora that feature.. 2022. 9. 21. 이전 1 ··· 123 124 125 126 127 128 129 ··· 143 다음 반응형