Meetings
Reading groups and talks
2022 Fall
Every other Thursday from 3-4pm through Zoom. Please sign-up here for future readings.
| Date | Title | Speaker/Discussant | Other Links |
|---|---|---|---|
| 24 November | Tidyparse: Real-time Context Free Error Correction | Breandan Considine | slides |
| 10 November | Introduction to OpenRewrite | Jonathan Schneider | |
| 27 October | Code Translation with Compiler Representations | Avinash Bhat | slides |
| 13 October | Collaborative Coding with Large (and Larger) Language Model | Jacob Austin | slides |
| 6 October | CodeGeeX: A Multilingual Code Generative Model | Justine Gehring |
2022 Spring
| Date | Title | Speaker/Discussant | Other Links |
|---|---|---|---|
| 10 May | Saturated Transformers are Constant-Depth Threshold Circuits | William Merrill | slides |
| 3 May | A Systematic Evaluation of Large Language Models of Code | Vincent Hellendoorn | slides |
| 26 April | Quiver Geometry | Taliesin Beynon | slides |
| 22 March | Neural Software Analysis: Learning Developer Tools from Code | Michael Pradel | |
| 8 March | Competition-Level Code Generation with AlphaCode | Dzmitry Bahdanau | slides |
| 22 February | Learning Patterns from User Interfaces to Automate Software Engineering Tasks | Kevin Moran | |
| 1 February | Traceability Transformed: Generating more Accurate Links with Pre-Trained BERT Models | Justine Gehring | slides |
2021 Fall
| Date | Title | Speaker/Discussant | Other Links |
|---|---|---|---|
| 30 November | Bug Detection & Repair with Machine Learning | Miltos Allamanis | slides |
| 26 November | A Logical Perspective on Program Synthesis and Neuro-Symbolic AI | Sebastijan Dumančić | |
| 9 November | Neurosymbolic Agents: A Proposal | David Yu-Tung Hui | |
| 12 October | Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks | Justine Gehring | slides |
| 12 October | Evaluating Large Language Models Trained on Code | Disha Shrivastava | |
| 28 September | Graphs for functional-style Python code | Arnaud Bergeron | |
| 28 September | Learning Structural Edits via Incremental Tree Transformations | Breandan Considine | slides |
| 14 September | Graph Attention Networks | David Yu-Tung Hui | slides |
2021 Summer
| Date | Title | Speaker/Discussant | Other Links |
|---|---|---|---|
| 17 August | Graph-based, Self-Supervised Program Repair from Diagnostic Feedback | Justine Gehring | slides |
| 3 August | Program Synthesis with Pragmatic Communication | David Yu-Tung Hui | slides |
| 20 July | Thinking Like Transformers | Breandan Considine | slides |
| 6 July | Communicating Natural Programs to Humans and Machines | Disha Shrivastava | |
| 22 June | How could Neural Networks understand Programs? | Justine Gehring | slides |
| 8 June | Discovering Reinforcement Learning Algorithms | David Yu-Tung Hui | slides |
| 11 May | GraphCodeBERT: Code Representations with Data Flow | Breandan Considine | slides |
2021 Spring
| Date | Title | Speaker/Discussant | Other Links |
|---|---|---|---|
| 13 April | Compositional Generalization via Neural-Symbolic Stack Machines | Disha Shrivastava | |
| 30 March | Neural Production Systems | Breandan Considine | |
| 17 March | Emergent Symbols through Binding in External Memory | David Yu-Tung Hui | |
| 2 March | Learning Compositional Rules via Neural Program Synthesis | Disha Shrivastava | |
| 16 February | Write, Execute, Assess: Program Synthesis with a REPL | Breandan Considine |