CS388: Natural Language Processing
11 days ago
- Deep Learning
- Natural Language Inference
- Ethics in NLP
- Online Course
- Question Answering
- Natural Language Processing
- The course is on Natural Language Processing and the materials are for an online masters course
- The lectures are available on YouTube
- There are several assignments on different topics such as sentiment classification, neural networks, and transformer language modeling
- The course covers topics like word embeddings, bias in word embeddings, and deep averaging networks
- Structured prediction topics include part-of-speech tagging, syntactic parsing, and dependencies
- Modern large language models like GPT-3 and zero/few-shot prompting are discussed
- Explanations in NLP, including model interpretability and local explanations, are part of the course content
- Several papers related to Natural Language Inference (NLI) explore different aspects of understanding text and generating explanations
- Studies investigate the reliability and effectiveness of explanations in textual reasoning and word problem solving
- Research on Question Answering (QA) covers topics such as machine comprehension, adversarial evaluation, open-domain QA, and multi-hop QA
- Dialogue systems, including chatbots, are explored for task-oriented dialogues and context-sensitive responses
- Machine Translation (MT) research delves into word alignment, neural models, and pre-trained approaches
- Summarization research covers extractive and pre-trained methods for generating factual summaries
- Multilingual studies include cross-lingual tagging, pre-training, and word embeddings for multilingual transfer learning
- Language grounding research focuses on connecting language to real-world concepts and vision
- Ethical considerations in Natural Language Processing (NLP) span areas like bias mitigation, exclusion, dangers of automation, and ethical use guidelines