2023-05 Reading Paper

2023-05-05

These two papers mainly discuss the development history and framework introduction of large language models. For friends who are not familiar with machine learning, it may be a bit difficult to read, but actually you don't need to understand all the concepts. Just skim through it once. In addition, I personally feel that understanding the model framework can help understand why the prompt is written that way.

• LLMSurvey
• The Practical Guides for Large Language Models

2023-05-06

• Shap·E: Generating Conditional 3D Implicit FunctionsThe Practical Guides for Large Language Models.
• The Elephant in the Room: This paper mainly uses a corpus with comprehensive metadata of 78,187 NLP publications and 701 resumes of NLP publication authors, to explore the industry presence in the field since the early 90s. The authors found that the number of authors with industry affiliations in NLP has been steady before a steep increase over the past five years (180% growth from 2017 to 2022). They also found in recent years, some internet companies have published a large number of papers (Jimmy: I've been reading more and more AI related papers recently, and I feel that in the LLMs era, research and engineering are deeply integrated).

2023-05-07

• Analyzing Hong Kong’s Legal Judgments from a Computational Linguistics point-of-view: This paper mainly discusses how to use natural language processing techniques to analyze legal judgments from Hong Kong courts. I don't know much about Hong Kong's laws, but from the examples and conclusions in the paper, it should be able to improve work efficiency.
• The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers?: This paper is mainly a survey, the results show that Gen Z participants were generally optimistic about the potential benefits of AI, including enhanced productivity, efficiency, and personalized learning, and expressed intentions to use AI in various educational scenarios. Gen X and Gen Y teachers acknowledged the potential benefits of AI but expressed heightened concerns about overreliance, ethical and pedagogical implications, emphasizing the need for AI to be used responsibly.