Paper reviews

Some brief thoughts on papers I've been reading.

• [arXiv] Generative Language Modeling for Automated Theorem Proving

• [ICLR 2014] Auto-Encoding Variatonal Bayes

• [ICLR 2017] Categorical Reparameterization with Gumbel-Softmax

• [EMNLP 2020] Unsupervised Question Decomposition for Question Answering

• [NeurIPS 2019] Representation Learning with Contrastive Predictive Coding

• [Psychological Review 2007] Word Learning as Bayesian Inference

• [ICFP 2011] Parsing with Derivatives: A Functional Pearl

• [Cognition 2012] The communicative function of ambiguity in language

• [KDD 2016] "Why Should I Trust You?": Explaining the Predictions of Any Classifier

• [CHI 2020] An Interaction Design for Machine Teaching to Develop AI Tutors

• [TCS 2020] Anchoring Utterances

• [arXiv 2020] Program Synthesis with Pragmatic Communication

• [NeurIPS 2019] Write, Execute, Assess: Program Synthesis with a REPL

• [ICLR 2019] Execution-Guided Neural Program Synthesis

• [NeurIPS 2018] Learning to Infer Graphics Programs from Hand-Drawn Images

• [CVPR 2016] Neural Module Networks

• [BRMIC 2004] AutoTutor: A tutor with dialogue in natural language

• [CVPR 2020] ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks

• [arXiv 2020] Language Models are Few-Shot Learners

• [POPL 2004] Abstractions from proofs