Accepted Papers
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1. A HINT from Arithmetic: On Systematic Generalization of Perception, Syntax, and Semantics
Qing Li; Siyuan Huang; Yining Hong; Yixin Zhu; Ying Nian Wu; Song-Chun Zhu[Paper][Poster][Video]
2. Pairwise Relations Discriminator for Unsupervised Raven's Progressive Matrices
Nicholas Quek; Duo Wang; Mateja Jamnik[Paper][Poster]
3. Beyond the Tactic-State Automaton
Daniel Selsam[Paper][Poster]
4. TacticZero: Learning to Prove Theorems from Scratch with Deep Reinforcement Learning
Minchao Wu; Michael Norrish; Christian Walder; Amir Dezfouli[Paper][Poster]
5. Measuring and Improving BERT's Mathematical Abilities by Predicting the Order of Reasoning
Piotr Piękos; Henryk Michalewski; Mateusz Malinowski[Paper][Poster]
6. Analyzing the Nuances of Transformers' Polynomial Simplification Abilitiess
Vishesh Agarwal; Somak Aditya; Navin Goyal[Paper][Poster][Video]
7. Investigating the Limitations of Transformers with Simple Arithmetic Tasks
Rodrigo Nogueira; Jimmy Lin; Zhiying Jiang[Paper][Poster]
8. Automated Conjecturing in QuickSpec
Moa Johansson; Nicholas Smallbone[Paper][Poster]
9. The Role of General Intelligence in Mathematical Reasoning
Aviv Keren[Paper][Poster][Video]
10. Distilling Wikipedia Mathematical Knowledge into Neural Network Models
Joanne T Kim; Mikel Landajuela; Brenden K Petersen[Paper][Poster]
11. Improving Exploration in Policy Gradient Search: Application to Symbolic Optimization
Mikel Landajuela; Brenden K Petersen; Sookyung Kim; Claudio Santiago; Ruben Glatt; Nathan Mundhenk; Jacob Pettit; Daniel Faissol[Paper][Poster]
12. Training a First-Order Theorem Prover from Synthetic Data
Vlad Firoiu; Eser Aygün; Ankit Anand; Zafarali Ahmed; Xavier Glorot; Laurent Orseau; Doina Precup; Shibl Mourad[Paper][Poster]
13. AUGMENTING THE HUMAN MATHEMATICIAN
Hester Breman; Renee Hoekzema; Mikkel Johansen; Henrik Kragh Sørensen[Paper][Poster]
14. LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning
Yuhuai Wu; Markus N Rabe; Wenda Li; Jimmy Ba; Roger B Grosse; Christian Szegedy[Paper][Poster]
15. REFACTOR: Learning to Extract Theorems from Proofs
Jin Peng Zhou; Yuhuai Wu; Qiyang Li; Roger B Grosse[Paper][Poster]
16. Proof Artifact Co-training for Theorem Proving With Language Models
Jesse M Han; Jason Rute; Yuhuai Wu; Edward Ayers; Stanislas Polu[Paper][Poster]
17. Measuring Mathematical Problem Solving With the MATH Dataset
Dan Hendrycks; Collin Burns; Saurav K Kadavath; Akul Arora; Steven Basart; Eric Tang; Dawn Song; Jacob Steinhardt[Paper][Poster]
18. Pretrained Transformers as Universal Computation Engines
Kevin Lu; Aditya Grover; Pieter Abbeel; Igor Mordatch[Paper][Poster]
19. Measuring Coding Challenge Competence With APPS
Dan Hendrycks; Steven Basart; Saurav K Kadavath; Mantas Mazeika; Akul Arora; Ethan Guo; Collin Burns; Samir Puranik; Horace He; Dawn Song; Jacob Steinhardt[Paper][Poster]
20. Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets
Harrison Edwards; Alethea Power; Yuri Burda; Igor Babuschkin; Vedant Misra[Paper][Poster]