1 code implementation • EMNLP (NLP-COVID19) 2020 • Adam Poliak, Max Fleming, Cash Costello, Kenton Murray, Mahsa Yarmohammadi, Shivani Pandya, Darius Irani, Milind Agarwal, Udit Sharma, Shuo Sun, Nicola Ivanov, Lingxi Shang, Kaushik Srinivasan, Seolhwa Lee, Xu Han, Smisha Agarwal, João Sedoc
We release a dataset of over 2, 100 COVID19 related Frequently asked Question-Answer pairs scraped from over 40 trusted websites.
no code implementations • WMT (EMNLP) 2020 • Marina Fomicheva, Shuo Sun, Lisa Yankovskaya, Frédéric Blain, Vishrav Chaudhary, Mark Fishel, Francisco Guzmán, Lucia Specia
We explore (a) a black-box approach to QE based on pre-trained representations; and (b) glass-box approaches that leverage various indicators that can be extracted from the neural MT systems.
no code implementations • CCL 2020 • Shuo Sun, Hongxu Hou, Nier Wu, Ziyue Guo, Chaowei Zhang
Reinforcement learning (RL) has made remarkable progress in neural machine translation (NMT).
no code implementations • EMNLP 2020 • Shuo Sun, Kevin Duh
We present CLIRMatrix, a massively large collection of bilingual and multilingual datasets for Cross-Lingual Information Retrieval extracted automatically from Wikipedia.
no code implementations • 19 Mar 2024 • Shuo Sun, Malcolm Mielle, Achim J. Lilienthal, Martin Magnusson
We propose a dense RGBD SLAM system based on 3D Gaussian Splatting that provides metrically accurate pose tracking and visually realistic reconstruction.
no code implementations • 28 Feb 2024 • Wentao Zhang, Lingxuan Zhao, Haochong Xia, Shuo Sun, Jiaze Sun, Molei Qin, Xinyi Li, Yuqing Zhao, Yilei Zhao, Xinyu Cai, Longtao Zheng, Xinrun Wang, Bo An
Notably, FinAgent is the first advanced multimodal foundation agent designed for financial trading tasks.
1 code implementation • 17 Nov 2023 • Wentao Zhang, Yilei Zhao, Shuo Sun, Jie Ying, Yonggang Xie, Zitao Song, Xinrun Wang, Bo An
Specifically, the target stock pool of different investors varies dramatically due to their discrepancy on market states and individual investors may temporally adjust stocks they desire to trade (e. g., adding one popular stocks), which lead to customizable stock pools (CSPs).
no code implementations • 16 Oct 2023 • Shuo Sun, Yuchen Zhang, Jiahuan Yan, Yuze Gao, Donovan Ong, Bin Chen, Jian Su
The success of ChatGPT has ignited an AI race, with researchers striving to develop new large language models (LLMs) that can match or surpass the language understanding and generation abilities of commercial ones.
no code implementations • 26 Sep 2023 • Shuo Sun, Zekai Gu, Tianchen Sun, Jiawei Sun, Chengran Yuan, Yuhang Han, Dongen Li, Marcelo H. Ang Jr
Realistic and diverse traffic scenarios in large quantities are crucial for the development and validation of autonomous driving systems.
1 code implementation • 22 Sep 2023 • Molei Qin, Shuo Sun, Wentao Zhang, Haochong Xia, Xinrun Wang, Bo An
In stage II, we construct a pool of diverse RL agents for different market trends, distinguished by return rates, where hundreds of RL agents are trained with different preferences of return rates and only a tiny fraction of them will be selected into the pool based on their profitability.
no code implementations • 14 Sep 2023 • Haochong Xia, Shuo Sun, Xinrun Wang, Bo An
Financial simulators play an important role in enhancing forecasting accuracy, managing risks, and fostering strategic financial decision-making.
no code implementations • 14 Jan 2023 • Shuo Sun, Molei Qin, Xinrun Wang, Bo An
Specifically, i) we propose AlphaMix+ as a strong FinRL baseline, which leverages mixture-of-experts (MoE) and risk-sensitive approaches to make diversified risk-aware investment decisions, ii) we evaluate 8 FinRL methods in 4 long-term real-world datasets of influential financial markets to demonstrate the usage of our PRUDEX-Compass, iii) PRUDEX-Compass together with 4 real-world datasets, standard implementation of 8 FinRL methods and a portfolio management environment is released as public resources to facilitate the design and comparison of new FinRL methods.
1 code implementation • 6 Dec 2022 • Wanqi Xue, Qingpeng Cai, Zhenghai Xue, Shuo Sun, Shuchang Liu, Dong Zheng, Peng Jiang, Kun Gai, Bo An
Though promising, the application of RL heavily relies on well-designed rewards, but designing rewards related to long-term user engagement is quite difficult.
no code implementations • 7 Jun 2022 • Shuo Sun, Rundong Wang, Bo An
To tackle these two limitations, we first reformulate quantitative investment as a multi-task learning problem.
no code implementations • 15 Dec 2021 • Shuo Sun, Wanqi Xue, Rundong Wang, Xu He, Junlei Zhu, Jian Li, Bo An
Reinforcement learning (RL) techniques have shown great success in many challenging quantitative trading tasks, such as portfolio management and algorithmic trading.
no code implementations • 29 Sep 2021 • Zhuoyi Lin, Biao Ye, Xu He, Shuo Sun, Rundong Wang, Rui Yin, Xu Chi, Chee Keong Kwoh
A machine learning system is typically composed of model and data.
no code implementations • 28 Sep 2021 • Shuo Sun, Rundong Wang, Bo An
RL's impact is pervasive, recently demonstrating its ability to conquer many challenging QT tasks.
no code implementations • EMNLP 2021 • Shuo Sun, Ahmed El-Kishky, Vishrav Chaudhary, James Cross, Francisco Guzmán, Lucia Specia
Sentence-level Quality estimation (QE) of machine translation is traditionally formulated as a regression task, and the performance of QE models is typically measured by Pearson correlation with human labels.
no code implementations • Asian Chapter of the Association for Computational Linguistics 2020 • Shuo Sun, Marina Fomicheva, Fr{\'e}d{\'e}ric Blain, Vishrav Chaudhary, Ahmed El-Kishky, Adithya Renduchintala, Francisco Guzm{\'a}n, Lucia Specia
Predicting the quality of machine translation has traditionally been addressed with language-specific models, under the assumption that the quality label distribution or linguistic features exhibit traits that are not shared across languages.
1 code implementation • LREC 2022 • Marina Fomicheva, Shuo Sun, Erick Fonseca, Chrysoula Zerva, Frédéric Blain, Vishrav Chaudhary, Francisco Guzmán, Nina Lopatina, Lucia Specia, André F. T. Martins
We present MLQE-PE, a new dataset for Machine Translation (MT) Quality Estimation (QE) and Automatic Post-Editing (APE).
1 code implementation • ACL 2020 • Shuo Sun, Suzanna Sia, Kevin Duh
We present CLIReval, an easy-to-use toolkit for evaluating machine translation (MT) with the proxy task of cross-lingual information retrieval (CLIR).
no code implementations • ACL 2020 • Shuo Sun, Francisco Guzm{\'a}n, Lucia Specia
Recent advances in pre-trained multilingual language models lead to state-of-the-art results on the task of quality estimation (QE) for machine translation.
3 code implementations • 21 May 2020 • Marina Fomicheva, Shuo Sun, Lisa Yankovskaya, Frédéric Blain, Francisco Guzmán, Mark Fishel, Nikolaos Aletras, Vishrav Chaudhary, Lucia Specia
Quality Estimation (QE) is an important component in making Machine Translation (MT) useful in real-world applications, as it is aimed to inform the user on the quality of the MT output at test time.
no code implementations • 8 May 2020 • Shuo Sun, Kevin Duh
Learning to rank is an important task that has been successfully deployed in many real-world information retrieval systems.
no code implementations • 27 Mar 2020 • Daniil M. Lukin, Alexander D. White, Rahul Trivedi, Melissa A. Guidry, Naoya Morioka, Charles Babin, Öney O. Soykal, Jawad Ul Hassan, Nguyen Tien Son, Takeshi Ohshima, Praful K. Vasireddy, Mamdouh H. Nasr, Shuo Sun, Jean-Phillipe W. MacLean, Constantin Dory, Emilio A. Nanni, Jörg Wrachtrup, Florian Kaiser, Jelena Vučković
To enable the experimental demonstration of this spectral control scheme, we investigate the Stark tuning properties of the silicon vacancy in silicon carbide, a color center with promise for optical quantum information processing technologies.
Quantum Physics Optics
6 code implementations • EACL 2021 • Holger Schwenk, Vishrav Chaudhary, Shuo Sun, Hongyu Gong, Francisco Guzmán
We present an approach based on multilingual sentence embeddings to automatically extract parallel sentences from the content of Wikipedia articles in 85 languages, including several dialects or low-resource languages.
no code implementations • 31 May 2019 • Vojtěch Kovařík, Dominik Seitz, Viliam Lisý, Jan Rudolf, Shuo Sun, Karel Ha
We provide a formal definition of depth-limited games together with an accessible and rigorous explanation of the underlying concepts, both of which were previously missing in imperfect-information games.
no code implementations • NAACL 2018 • Shota Sasaki, Shuo Sun, Shigehiko Schamoni, Kevin Duh, Kentaro Inui
Cross-lingual information retrieval (CLIR) is a document retrieval task where the documents are written in a language different from that of the user{'}s query.