Gabriel Poesia
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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
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