34 citations · 64 across the 6 of their papers we have counts for
6 papers
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
Runfa Chen, Yu Rong, Shangmin Guo +4
After the great success of Vision Transformer variants (ViTs) in computer vision, it has also demonstrated great potential in domain adaptive semantic segmentation. Unfortunately,…
Better Supervisory Signals by Observing Learning Paths
Yi Ren, Shangmin Guo, Danica J. Sutherland
Better-supervised models might have better performance. In this paper, we first clarify what makes for good supervision for a classification problem, and then explain two existing…
Inductive Bias and Language Expressivity in Emergent Communication
Shangmin Guo, Yi Ren, Agnieszka Słowik +1
Referential games and reconstruction games are the most common game types for studying emergent languages. We investigate how the type of the language game affects the emergent lan…
Compositional Languages Emerge in a Neural Iterated Learning Model
Yi Ren, Shangmin Guo, Matthieu Labeau +2
The principle of compositionality, which enables natural language to represent complex concepts via a structured combination of simpler ones, allows us to convey an open-ended set…
Emergence of Numeric Concepts in Multi-Agent Autonomous Communication
Shangmin Guo
With the rapid development of deep learning, most of current state-of-the-art techniques in natural langauge processing are based on deep learning models trained with argescaled st…
The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents
Shangmin Guo, Yi Ren, Serhii Havrylov +3
Since first introduced, computer simulation has been an increasingly important tool in evolutionary linguistics. Recently, with the development of deep learning techniques, researc…