Materials

You can download the external materials and exam questions here. 🔔 Subscribe to our newsletter for the latest updates on LLMs!

Exam Questions

• Quiz-1 Question Paper
• Mid-Semester Examination Question Paper
• Quiz-2 Question Paper
• End-Semester Examination Question Paper

Textbook

• Introduction to Large Language Models, Tanmoy Chakraborty

Reference Books

• Speech and Language Processing, Dan Jurafsky and James H. Martin
• Foundations of Statistical Natural Language Processing, Chris Manning and Hinrich Schütze
• Natural Language Processing, Jacob Eisenstein
• A Primer on Neural Network Models for Natural Language Processing, Yoav Goldberg

Research Papers (As Recommended in Class)

Journals

• Computational Linguistics, TACL, JMLR, TMLR, etc.

Conferences

• ACL, EMNLP, NAACL, NeurIPS, ICLR, ICML, AAAI, WWW, KDD, SIGIR, etc.

Related Courses (Non-exhaustive)

• CMU CS 11-711: Advanced NLP, Graham Neubig
• UMass Amherst CS 685: Advanced NLP, Mohit Iyyer
• Stanford CS224N: NLP with Deep Learning, Chris Manning
• Princeton COS 597G: Understanding Large Language Models, Danqi Chen
• UT Austin CS388/AI388/DSC395T: Natural Language Processing, Greg Durrett
• Stanford CS324: Large Language Models
• CMSC 473/673: Natural Language Processing at UMBC, Lara Martin
• CMU CS 11-830: Computational Ethics for NLP
• JHU CS 601.471/671 NLP: Self-supervised Models, Daniel Khashabi
• WING.NUS Large Language Models