CMSC 473/673 - Schedule

The lecture schedule will be updated as the term progresses.

Date	Lecture Topic	Readings for this Lesson	Homework Due
Tue, Jan 27, 2026	No Class - Snow Day
Thu, Jan 29, 2026	No Class - Snow Day
Fri, Jan 30, 2026	Waitlist Deadline
Tue, Feb 3, 2026	What is NLP? [slides]	Jacob Eisenstein, NLP Chapter 1
Thu, Feb 5, 2026	Examples of NLP Tasks [slides]	Dan Jurafsky and James H. Martin, SLP Chapter 2 Jacob Eisenstein, NLP Chapter 2.2 & 4.5
Mon, Feb 9, 2026	Waitlists Deactivated
Tue, Feb 10, 2026	Examples of NLP Tasks + ML Basics [slides]	Ian Goodfellow, Yoshua Bengio, and Aaron Courville, Deep Learning Chapter 5.1-5.3 (ML Basics)
Thu, Feb 12, 2026	NLP Tasks + ML Evaluation [slides]	Jacob Eisenstein, NLP Chapter 4.4 (Evaluating classifiers) Dan Jurafsky and James H. Martin, SLP Chapter 4.9 (Evaluation), 4.10 (Test sets)
Fri, Feb 13, 2026	Last Day to Change Schedule
Tue, Feb 17, 2026	ML Evaluation + Classification with Logistic Regression Models [slides]	Jacob Eisenstein, NLP Chapter 2.5 (Logistic regression) Dan Jurafsky and James H. Martin, NLP Chapter 4.3 (Classification with Logistic Regression)	CATME Survey Due
Thu, Feb 19, 2026	Classification with Logistic Regression Models [slides]
Fri, Feb 20, 2026			HW1: Being up to the Task
Tue, Feb 24, 2026	Vector Embeddings [slides]	Jacob Eisenstein, NLP Chapter 14 (Distributional and distributed semantics) Dan Jurafsky and James H. Martin, SLP Chapter 5 (Embeddings)
Thu, Feb 26, 2026	Vector Embeddings and Learning in Logistic Regression [slides]	Jacob Eisenstein, NLP Chapter B.1 (Gradient Descent) Dan Jurafsky and James H. Martin, NLP Chapter 4.6 (Gradient Descent)
Tue, Mar 3, 2026	N-Gram Language Models	Jacob Eisenstein, NLP Chapter 6.1 (Language models) Dan Jurafsky and James H. Martin, SLP Chapter 3 (N-gram Language Models)	Grad Checkpoint 1: Selection
Thu, Mar 5, 2026	PyTorch & HuggingFace Tutorial
Tue, Mar 10, 2026	Neural Language Models	Dan Jurafsky and James H. Martin, SLP Chapter 6 (Neural Networks) Jacob Eisenstein, NLP Chapter 3 (Nonlinear classification)	Project Milestone 1: Project Proposal
Thu, Mar 12, 2026	Recurrent Neural Network LMs + Seq2Seq	Jacob Eisenstein, NLP Chapter 18.3 intro (Neural machine translation) Dan Jurafsky and James H. Martin, SLP Chapter 13 (RNNs and LSTMs)
Tue, Mar 17, 2026	Spring Break - No Class
Thu, Mar 19, 2026	Spring Break - No Class
Tue, Mar 24, 2026	Attention & Transformers	Jacob Eisenstein, NLP Chapter 18.3.1-18.3.2 (Neural machine translation) Jacob Eisenstein, NLP Chapter 19.1-19.2 (Text generation) Dan Jurafsky and James H. Martin, SLP Chapter 8 (Transformers) Ashish Vaswani, et al., Attention Is All You Need
Thu, Mar 26, 2026	Masked Language Models	Dan Jurafsky and James H. Martin, SLP Chapter 10 (Masked Language Models) Jacob Devlin, Ming-Wei Chang, Kenton Lee, Kristina Toutanova, BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Tue, Mar 31, 2026	Review
Thu, Apr 2, 2026	Exam
Fri, Apr 3, 2026	Last Day to Withdraw from Individual Classes		HW2: Evaluation
Tue, Apr 7, 2026	Decoding, Pretraining & Finetuning	Dan Jurafsky and James H. Martin, SLP Chapter 9 (Post-training) Alec Radford, et al., Language Models are Unsupervised Multitask Learners
Thu, Apr 9, 2026	Prompt Engineering Tutorial	Dan Jurafsky and James H. Martin, SLP Chapter 9.4 (Test-time Compute) Tom B. Brown, et al., Language Models are Few-Shot Learners Jason Wei, et al., Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Tue, Apr 14, 2026	Ethics of NLP	Dan Jurafsky and James H. Martin, SLP Chapter 12.7 (Bias and Ethical Issues) Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, Shmargaret Shmitchell, On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 Roy Schwartz, Jesse Dodge, Noah A. Smith, Oren Etzioni, Green AI	Project Milestone 2: Project Progress
Thu, Apr 16, 2026	Ethics of NLP	Daphne Ippolito, et al., Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy Vered Shwartz, Yejin Choi, Do Neural Language Models Overcome Reporting Bias? Xuhui Zhou, et al., Challenges in Automated Debiasing for Toxic Language Detection
Tue, Apr 21, 2026	Alignment	Dan Jurafsky and James H. Martin, SLP Chapter 9.1-9.3 (Instruction tuning, Learning from preferences...) Long Ouyang, et al., Training language models to follow instructions with human feedback
Thu, Apr 23, 2026	Small LLMs	Dan Jurafsky and James H. Martin, SLP Chapter 10.5.3 Edward J. Hu, et al., LoRA: Low-Rank Adaptation of Large Language Models Noam Shazeer, et al., Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer Geoffrey Hinton, et al., Distilling the Knowledge in a Neural Network Abigail See, et al., Compression of Neural Machine Translation Models via Pruning
Tue, Apr 28, 2026	Retrieval-Augmented Generation (RAG)	Dan Jurafsky and James H. Martin, SLP Chapter 11 (Information Retrieval and Retrieval-Augmented Generation) Yunfan Gao, et al., Retrieval-Augmented Generation for Large Language Models: A Survey	Grad Checkpoint 2: Draft HW 3: Prompt Engineering
Thu, Apr 30, 2026	Automatic Speech Recognition	Dan Jurafsky and James H. Martin, SLP Chapter 15 (Automated Speech Recognition)
Tue, May 5, 2026	Applications: Machine Translation	Dan Jurafsky and James H. Martin, SLP Chapter 12 (Machine Translation) Jacob Eisenstein, NLP Chapter 18 (Neural machine translation)	Grad Checkpoint 3: Feedback
Thu, May 7, 2026	Applications: Dialog Systems	Jacob Eisenstein, NLP Chapter 19.3 (Dialogue) Dan Jurafsky and James H. Martin, SLP Chapter K (Frame-based Dialogue Systems)	Project Milestone 3: Rough Draft
Tue, May 12, 2026	Applications: TBD
Thu, May 14, 2026	Project Presentations, 10:30 AM-12:30 PM		Project Milestone 4: Final Submission Grad Checkpoint 4: Final Submission