Shangmin Guo

According to our database, Shangmin Guo authored at least 23 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Language Model Evolution: An Iterated Learning Perspective.

Yi Ren, Shangmin Guo, Linlu Qiu, Bailin Wang, Danica J. Sutherland

CoRR, 2024

Direct Language Model Alignment from Online AI Feedback.

Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu, Misha Khalman, Felipe Llinares, Alexandre Ramé, Thomas Mesnard, Yao Zhao, Bilal Piot, Johan Ferret, Mathieu Blondel

CoRR, 2024

ICED: Zero-Shot Transfer in Reinforcement Learning via In-Context Environment Design.

Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V. Albrecht

CoRR, 2024

Sample Relationship from Learning Dynamics Matters for Generalisation.

Shangmin Guo, Yi Ren, Stefano V. Albrecht, Kenny Smith

CoRR, 2024

Economics Arena for Large Language Models.

Shangmin Guo, Haoran Bu, Haochuan Wang, Yi Ren, Dianbo Sui, Yuming Shang, Siting Lu

CoRR, 2024

Decoding-time Realignment of Language Models.

Tianlin Liu, Shangmin Guo, Leonardo Bianco, Daniele Calandriello, Quentin Berthet, Felipe Llinares-López, Jessica Hoffmann, Lucas Dixon, Michal Valko, Mathieu Blondel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design.

Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V. Albrecht

Proceedings of the Forty-first International Conference on Machine Learning, 2024

lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning.

Shangmin Guo, Yi Ren, Stefano V. Albrecht, Kenny Smith

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

How the level sampling process impacts zero-shot generalisation in deep reinforcement learning.

Samuel Garcin, James Doran, Shangmin Guo, Christopher G. Lucas, Stefano V. Albrecht

CoRR, 2023

How to prepare your task head for finetuning.

Yi Ren, Shangmin Guo, Wonho Bae, Danica J. Sutherland

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Communicative Efficiency or Iconic Learning: Do Acquisition and Communicative Pressures Interact to Shape Colour- Naming Systems?

Balint Gyevnar, Gautier Dagan, Coleman Haley, Shangmin Guo, Frank Mollica

Entropy, 2022

Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation.

Runfa Chen, Yu Rong, Shangmin Guo, Jiaqi Han, Fuchun Sun, Tingyang Xu, Wenbing Huang

CoRR, 2022

Deep reinforcement learning for multi-agent interaction.

Ibrahim H. Ahmed, Cillian Brewitt, Ignacio Carlucho, Filippos Christianos, Mhairi Dunion, Elliot Fosong, Samuel Garcin, Shangmin Guo, Balint Gyevnar, Trevor McInroe, Georgios Papoudakis, Arrasy Rahman, Lukas Schäfer, Massimiliano Tamborski, Giuseppe Vecchio, Cheng Wang, Stefano V. Albrecht

AI Commun., 2022

Better Supervisory Signals by Observing Learning Paths.

Yi Ren, Shangmin Guo, Danica J. Sutherland

Proceedings of the Tenth International Conference on Learning Representations, 2022

Expressivity of Emergent Languages is a Trade-off between Contextual Complexity and Unpredictability.

Shangmin Guo, Yi Ren, Kory Wallace Mathewson, Simon Kirby, Stefano V. Albrecht, Kenny Smith

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability.

Shangmin Guo, Yi Ren, Kory W. Mathewson, Simon Kirby, Stefano V. Albrecht, Kenny Smith

CoRR, 2021

2020

Inductive Bias and Language Expressivity in Emergent Communication.

Shangmin Guo, Yi Ren, Agnieszka Slowik, Kory W. Mathewson

CoRR, 2020

Compositional languages emerge in a neural iterated learning model.

Yi Ren, Shangmin Guo, Matthieu Labeau, Shay B. Cohen, Simon Kirby

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Emergence of Numeric Concepts in Multi-Agent Autonomous Communication.

Shangmin Guo

CoRR, 2019

The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents.

Shangmin Guo, Yi Ren, Serhii Havrylov, Stella Frank, Ivan Titov, Kenny Smith

CoRR, 2019

2017

IJCNLP-2017 Task 5: Multi-choice Question Answering in Examinations.

Shangmin Guo, Kang Liu, Shizhu He, Cao Liu, Jun Zhao, Zhuoyu Wei

Proceedings of the IJCNLP 2017, Shared Tasks, Taipei, Taiwan, November 27, 2017

Which is the Effective Way for Gaokao: Information Retrieval or Neural Networks?

Shangmin Guo, Xiangrong Zeng, Shizhu He, Kang Liu, Jun Zhao

Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, 2017

2016

Employing External Rich Knowledge for Machine Comprehension.

Bingning Wang, Shangmin Guo, Kang Liu, Shizhu He, Jun Zhao

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016