Publications

2025

Tai Nguyen, Phong Le, Carola Doerr, and Nguyen Dang. Multi-parameter Control for the (1+(λ, λ))-GA on OneMax via Deep Reinforcement Learning. Proceedings of the 18th ACM/SIGEVO Conference on Foundations of Genetic Algorithms. 2025
Tai Nguyen, Phong Le, André Biedenkapp, Carola Doerr, and Nguyen Dang. On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(λ,λ))-GA. Proceedings of the Genetic and Evolutionary Computation Conference. 2025

Daniel Akkerman, Phong Le, and Raquel G. Alhama. The Emergence of Compositional Languages in Multi-entity Referential Games: from Image to Graph Representations. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. 2024

Thy Thy Tran, Phong Le, and Sophia Ananiadou. One-shot to Weakly-Supervised Relation Classification using Language Models. 3rd Conference on Automated Knowledge Base Construction. 2021

Thy Thy Tran, Phong Le, and Sophia Ananiadou. Revisiting Unsupervised Relation Extraction. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020
Phong Le and Willem Zuidema. DoLFIn: Distributions over Latent Features for Interpretability. Proceedings of the 28th International Conference on Computational Linguistics. 2020

Phong Le and Ivan Titov. Boosting Entity Linking Performance by Leveraging Unlabeled Documents. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019
Phong Le and Ivan Titov. Distant Learning for Entity Linking with Automatic Noise Detection. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. 2019
Willem Zuidema and Phong Le. Vector-Based and Neural Models of Semantics. Human Language: From Genes and Brains to Behavior. 2019

Phong Le and Ivan Titov. Improving Entity Linking by Modeling Latent Relations between Mentions. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2018

Phong Le and Ivan Titov. Optimizing Differentiable Relaxations of Coreference Evaluation Metrics. Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017). 2017

Phong Le. Learning Vector Representations for Sentences-The Recursive Deep Learning Approach. PhD Thesis. University of Amsterdam. 2016
Phong Le and Willem Zuidema. Quantifying the Vanishing Gradient and Long Distance Dependency Problem in Recursive Neural Networks and Recursive LSTMs. Proceedings of the 1st Workshop on Representation Learning for NLP. 2016
Phong Le, Marc Dymetman, and Jean-Michel Renders. LSTM-Based Mixture-of-Experts for Knowledge-Aware Dialogues. Proceedings of the 1st Workshop on Representation Learning for NLP. 2016

Phong Le and Willem Zuidema. Compositional Distributional Semantics with Long Short Term Memory. Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics. 2015
Phong Le. Enhancing the Inside-Outside Recursive Neural Network Reranker for Dependency Parsing. Proceedings of the 14th International Conference on Parsing Technologies. 2015
Phong Le and Willem Zuidema. The Forest Convolutional Network: Compositional Distributional Semantics with a Neural Chart and without Binarization. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. 2015
Phong Le and Willem Zuidema. Unsupervised Dependency Parsing: Let`s Use Supervised Parsers. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2015

Phong Le and Willem Zuidema. Inside-outside semantics: A framework for neural models of semantic composition. NIPS 2014 Workshop on Deep Learning and Representation Learning. 2014
Phong Le and Willem Zuidema. The Inside-Outside Recursive Neural Network model for Dependency Parsing. Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2014

Phong Le, Willem Zuidema, and Remko Scha. Learning from errors: Using vector-based compositional semantics for parse reranking. Proceedings of the Workshop on Continuous Vector Space Models and their Compositionality. 2013

Phong Le and Willem Zuidema. Learning Compositional Semantics for Open Domain Semantic Parsing. Proceedings of COLING 2012. 2012
Phong Le. Learning Semantic Parsing. MSc Thesis. University of Amsterdam. 2012

Phong Le, Anh Duc Duong, Hai Quan Vu, and Nam Trung Pham. Adaptive Hybrid Mean Shift and Particle Filter. 2009 IEEE-RIVF International Conference on Computing and Communication Technologies. 2009