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2020 – today
- 2024
[c7]Mojtaba Valizadeh, Philip John Gorinski, Ignacio Iacobacci, Martin Berger:
Correct and Optimal: The Regular Expression Inference Challenge. IJCAI 2024: 6486-6494- [i11]Rafael Kourdis, Gabriel Gordon-Hall, Philip John Gorinski:
αVIL: Learning to Leverage Auxiliary Tasks for Multitask Learning. CoRR abs/2405.07769 (2024) - 2023
- [c6]Philip John Gorinski, Matthieu Zimmer, Gerasimos Lampouras, Derrick-Goh-Xin Deik, Ignacio Iacobacci:
Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code Synthesis. EMNLP (Findings) 2023: 370-384 - [i10]Yunjie He, Philip John Gorinski, Ieva Staliunaite, Pontus Stenetorp:
Graph Attention with Hierarchies for Multi-hop Question Answering. CoRR abs/2301.11792 (2023) - [i9]Mojtaba Valizadeh, Philip John Gorinski, Ignacio Iacobacci, Martin Berger:
The Regular Expression Inference Challenge. CoRR abs/2308.07899 (2023) - [i8]Philip John Gorinski, Matthieu Zimmer, Gerasimos Lampouras, Derrick-Goh-Xin Deik, Ignacio Iacobacci:
Automatic Unit Test Data Generation and Actor-Critic Reinforcement Learning for Code Synthesis. CoRR abs/2310.13669 (2023) - 2022
- [i7]Alexander I. Cowen-Rivers, Philip John Gorinski, Aivar Sootla, Asif Khan, Furui Liu, Jun Wang, Jan Peters, Haitham Bou-Ammar:
Structured Q-learning For Antibody Design. CoRR abs/2209.04698 (2022) - [i6]Ieva Staliunaite, Philip John Gorinski, Ignacio Iacobacci:
Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Study. CoRR abs/2210.06418 (2022) - 2021
- [c5]Ieva Staliunaite, Philip John Gorinski, Ignacio Iacobacci:
Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation. AAAI 2021: 13834-13842 - [i5]Ieva Staliunaite, Philip John Gorinski, Ignacio Iacobacci:
Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation. CoRR abs/2101.04966 (2021) - 2020
- [c4]Gabriel Gordon-Hall, Philip John Gorinski, Shay B. Cohen:
Learning Dialog Policies from Weak Demonstrations. ACL 2020: 1394-1405 - [c3]Yusheng Tian, Philip John Gorinski:
Improving End-to-End Speech-to-Intent Classification with Reptile. INTERSPEECH 2020: 891-895 - [i4]Gabriel Gordon-Hall, Philip John Gorinski, Gerasimos Lampouras, Ignacio Iacobacci:
Show Us the Way: Learning to Manage Dialog from Demonstrations. CoRR abs/2004.08114 (2020) - [i3]Gabriel Gordon-Hall, Philip John Gorinski, Shay B. Cohen:
Learning Dialog Policies from Weak Demonstrations. CoRR abs/2004.11054 (2020) - [i2]Yusheng Tian, Philip John Gorinski:
Improving End-to-End Speech-to-Intent Classification with Reptile. CoRR abs/2008.01994 (2020)
2010 – 2019
- 2019
- [i1]Philip John Gorinski, Honghan Wu
, Claire Grover, Richard Tobin, Conn Talbot, Heather Whalley, Cathie Sudlow, William Whiteley, Beatrice Alex:
Named Entity Recognition for Electronic Health Records: A Comparison of Rule-based and Machine Learning Approaches. CoRR abs/1903.03985 (2019) - 2018
- [c2]Philip John Gorinski, Mirella Lapata:
What's This Movie About? A Joint Neural Network Architecture for Movie Content Analysis. NAACL-HLT 2018: 1770-1781 - 2015
- [c1]Philip John Gorinski, Mirella Lapata:
Movie Script Summarization as Graph-based Scene Extraction. HLT-NAACL 2015: 1066-1076
Coauthor Index
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