TTDS: Schedule

Week

• IR in Practice Chapters 1 & 2

• Intro to IR Chapter 2 --> 2.2.4
• IR in Practice Chapter 4
• Zipf’s law, Vsouce
• Benford’s law, Numberphile

• Intro to IR Chapters 1, 2.4 and 3.1-3.4
• IR in Practice chapter 5

• Intro to IR Chapters 6.2 to 6.4 and 12
• IR in Practice Chapter 7
• Robertson, Stephen E., et al. "Okapi at TREC-3."
• J. Ponte and W. B. Croft. "A language modeling approach to information retrieval."

• Intro to IR Chapters 8
• IR in Practice Chapter 8
• C Buckley and E. M. Voorhees. "Retrieval Evaluation with Incomplete Information."

• Intro to IR Chapters 9
• IR in Practice Chapter 6.2, 6.3
• Magdy W. and G. J. F. Jones. A Study on Query Expansion Methods for Patent Retrieval

• Intro to IR Chapter 19, 21.2
• IR in Practice Chapter 3, 4.5, 10.3
• How Search Works? (YouTube)
• Page, L., Brin, S., Motwani, R., & Winograd, T. (1999). The PageRank citation ranking: Bringing order to the web.
• Dumais, S., Banko, M., Brill, E., Lin, J., & Ng, A. (2002) Web question answering: Is more always better?. SIGIR 2002.

• Manning: IR book section 13.5
• “Probabilistic Topic Models” by David Blei
• “Latent Dirichlet Allocation” by David Blei, Andrew Y. Ng, and Michael I. Jordan
• “Probabilistic Topic Models” by Mark Steyvers and Tom Griffiths
• Guest lecture (2017) by David Blei

• Fabrizio Sebastiani: Machine Learning in Automated Text CategorizationACM Computing Surveys, 2002, https://arxiv.org/pdf/cs/0110053
• Yoav Goldberg: A Primer on Neural Network Models for Natural Language Processing, https://arxiv.org/abs/1510.00726
• Magdy W., H. Sajjad, T. El-Ganainy and F. Sebastiani. (2015) Bridging Social Media via Distant Supervision. Springer SNAM 2015 link, arXiv
• Additional reading: Nguyen, D. P., Gravel, R., Trieschnigg, R. B., & Meder, T. How old do you think I am? A study of language and age in Twitter. ICWSM 2013
• Huggingface (2024). Text Classification. Link: https://huggingface.co/tasks/text-classification
• Sentence Transformers (2024)
  Link: https://www.sbert.net/ 

• Ramesh, N. (2004). Discriminative models for information retrieval. SIGIR.
• Burges, C. J. (2010). From ranknet to lambdarank to lambdamart: An overview. Learning, 11(23-581), 81.

19 - RAG

• Lewis et al. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. NeurIPS 2020. https://arxiv.org/abs/2005.11401
• Jiang et al. Active Retrieval Augmented Generation. EMNLP 2023. https://arxiv.org/abs/2305.06983
• Vaswani et al. Attention is All You Need. https://arxiv.org/abs/1706.03762
• Guest Lecture by Amin Ahmad
• Pasquale Minervini, NLU-11 Natural Language Understanding Generation and Machine Translation.