Task Specific Research4 KMMLU: A Korean Benchmark for LLMs KMMLU: Measuring Massive Multitask Language Understanding in Korean Guijin Son, Hanwool Lee, Sungdong Kim, etc. 18 Feb 2024 MMLU There exist various benchmarks for evaluating and understanding the capabilities of Large Language Models (LLMs), such as commonsense reasoning, code generation, and multi-turn conversations. Massive Multitask Language Understanding (MMLU) is one of these benchmarks, c.. 2024. 3. 29. Detecting Whether A Text is Written in GPT DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature Eric Mitchell, Yoonho Lee, Chelsea Finn, etc. 26 Jan 2023 DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature The fluency and factual knowledge of large language models (LLMs) heightens the need for corresponding systems to detect whether a piece of text is machine-written. For example.. 2023. 2. 27. LUKE: Language Understanding with Knowledge-Based Embeddings LUKE: Deep Contextualized Entity Representation with Entity-aware Self-attention Ikuya Yamade, Akari Asai, etc. 2 Oct 2020 Abstract As the title exposes, this paper, which indicates LUKE, proposes a deeply contextualized entity representations based on bidirectional transformer. Luke has achieved state-of-the-art on five well-known entity related tasks, such as NER (Named Entity Recognition) and.. 2023. 2. 4. A Paradigm Shift for Non-english(Korean) Language Processing KR-BERT: A Small-Scale Korean-Specific Language Model Sangah Lee, Hansol Jang, etc. 11 Aug 2020 Abstract The world’s dominant machine learning model for language processing called Bidirectional Encoder Representation from Transformer (BERT) have also made various task-specific models throughout the history. This paper suggests one of the language model which is also derived from BERT, called KR-.. 2023. 1. 17. 이전 1 다음
