- Haitian Sun, William W. Cohen, Ruslan Salakhutdinov (2023): Scenario-based Question Answering with Interacting Contextual Properties in ICLR-2023.
- Wenhu Chen, Pat Verga, Michiel de Jong, John Wieting, William W. Cohen (2022): Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering in EACL-2022.
- Extends the techniques of Mention Memory in several important ways. (1) The memory is a memory of generated question-answer pairs, which is more interpretable than neural entity-mention encodings; (2) it is based on pre-trained T5, not a custom Transformer; and (3) it allows use of the token-level encoding of retrieved QA pairs as well as neural encodings of them for reasoning. Using QA pairs instead of passages allows a clever pre-training trick for learning to retrieve, and the model greatly outperfoms a prior similar model (i.e., RePAQ) on smaller QA benchmarks.

- Yi Tay, Vinh Q. Tran, Mostafa Dehghani, Jianmo Ni, Dara Bahri, Harsh Mehta, Zhen Qin, Kai Hui, Zhe Zhao, Jai Gupta, Tal Schuster, William W. Cohen and Donald Metzler (2022): Transformer Memory as a Differentiable Search Index in NeurIPS 2022.
- Siddhant Arora, Danish Pruthi, Norman Sadeh, William W. Cohen, Zachary C. Lipton, Graham Neubig (2022): Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations in AAAI 2022.
- Danish Pruthi, Bhuwan Dhingra, Livio Baldini Soares, Michael Collins, Zachary C. Lipton, Graham Neubig, William W. Cohen (2020): Evaluating Explanations: How Much Do Explanations From the Teacher Aid Students? in preparation.
- William Yang Wang, Kathryn Mazaitis, and William W. Cohen (2015): A Soft Version of Predicate Invention Based on Structured Sparsity in IJCAI-2015.
- William Yang Wang, Kathryn Mazaitis, Ni Lao, Tom Mitchell, and William W. Cohen (2015): Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic in Machine Learning, 2015.
- William Yang Wang, Kathryn Mazaitis, William W. Cohen (2013): Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic in CIKM-2013.
- Honorable Mention for Best Paper at CIKM-2013

- William Yang Wang, Kathryn Mazaitis, William W. Cohen (2013): Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic in arxiv 1305.2254.
- William Yang Wang, Kathryn Mazaitis, William W. Cohen (2013): Programming with Personalized PageRank: A Locally Groundable First-Order Probabilistic Logic in ICML 2103 Workshop on Inferning.
- William W. Cohen, Russell Greiner, and Dale Schuurmans (1994): Probabilistic hill-climbing in Computational learning theory and natural learning systems (Volume II), MIT Press..
- William W. Cohen (1994): Incremental abductive EBL in Machine Learning 15(1): 5-24 (1994).
- William W. Cohen (1994): Grammatically biased learning: learning logic programs using an explicit antecedent description language in Artif. Intell. 68(2): 303-366 (1994).
- William W. Cohen (1992): Using distribution-free learning theory to analyze solution path caching mechanisms in Computational Intelligence 8: 336-375 (1992).
- William W. Cohen (1992): Desiderata for generalization-to-n algorithms in AII 1992: 140-150.
- William W. Cohen (1992): Compiling prior knowledge into an explicit bias in ICML 1992: 102-110.
- William W. Cohen (1992): Abductive explanation based learning: A solution to the multiple inconsistent explanation problem in Machine Learning 8: 167-219 (1992).
- William W. Cohen (1993): A Review of `Creating a Memory of Causal Relationships' by Michael Pazzani in Machine Learning (1993).
- William W. Cohen (1991): The generality of overgenerality in ICML 1991: 490-494.
- William W. Cohen (1990): Learning from textbook knowledge: A case study in AAAI 1990: 743-748.
- William W. Cohen (1990): Learning approximate control rules of high utility in ICML 1990: 268-276.
- William W. Cohen (1990): An analysis of representation shift in concept learning in ICML 1990: 104-112.
- William W. Cohen (1990): Learning from Examples and an "Abductive Theory" in Proc. of the 1990 AAAI Spring Symposium on Abduction.
- William W. Cohen (1988): Generalizing number and learning from multiple examples in explanation-based learning in ICML 1988: 256-269.
- William W. Cohen, Jack Mostow & Alex Borgida (1988): Generalizing number in explanation-based learning in Proc. of the 1988 AAAI Spring Symposium on Explanation-Based Learning.

[Selected papers| By topic: GNAT System| Retrieval Augmented LMs| Applications| Collaborative Filtering| Intelligent Tutoring| Explanation-Based Learning| Formal Results| Learning in Graphs| Inductive Logic Programming| Neural Knowledge Representation| Topic Modeling| Matching/Data Integration| Deep Learning| Prediction-powered inference| Rule Learning| Text Categorization| Info Extraction/Reading/QA| By year: All papers]