1 code implementation • 6 Apr 2024 • Yingting Li, Rishabh Bhardwaj, Ambuj Mehrish, Bo Cheng, Soujanya Poria
In this work, we present HyperTTS, which comprises a small learnable network, "hypernetwork", that generates parameters of the Adapter blocks, allowing us to condition Adapters on speaker representations and making them dynamic.
1 code implementation • 31 Mar 2024 • Xiang Li, Fan Bu, Ambuj Mehrish, Yingting Li, Jiale Han, Bo Cheng, Soujanya Poria
The pursuit of modern models, like Diffusion Models (DMs), holds promise for achieving high-fidelity, real-time speech synthesis.
no code implementations • 29 Feb 2024 • Bryan Habas, Bo Cheng
Inverted landing is a routine behavior among a number of animal fliers.
1 code implementation • 24 Feb 2024 • Shengkun Ma, Jiale Han, Yi Liang, Bo Cheng
Continual Few-shot Relation Extraction (CFRE) is a practical problem that requires the model to continuously learn novel relations while avoiding forgetting old ones with few labeled training data.
no code implementations • 10 Oct 2023 • Hongbin Xu, Yamei Xia, Shuai Zhao, Bo Cheng
We improve the self-attention by isolating connections between irrelevant objects that makes it focus on local regions but not global regions.
1 code implementation • 22 Oct 2022 • Jiale Han, Shuai Zhao, Bo Cheng, Shengkun Ma, Wei Lu
Current prompt tuning methods mostly convert the downstream tasks to masked language modeling problems by adding cloze-style phrases and mapping all labels to verbalizations with fixed length, which has proven effective for tasks with simple label spaces.
Ranked #2 on Relation Extraction on Re-TACRED
no code implementations • 22 Sep 2022 • Bryan Habas, Jack W. Langelaan, Bo Cheng
Inverted landing in a rapid and robust manner is a challenging feat for aerial robots, especially while depending entirely on onboard sensing and computation.
1 code implementation • NAACL 2022 • Devamanyu Hazarika, Yingting Li, Bo Cheng, Shuai Zhao, Roger Zimmermann, Soujanya Poria
In this work, we hope to address that by (i) Proposing simple diagnostic checks for modality robustness in a trained multimodal model.
no code implementations • 4 May 2022 • Yi Liang, Shuai Zhao, Bo Cheng, Yuwei Yin, Hao Yang
Few-shot relation learning refers to infer facts for relations with a limited number of observed triples.
no code implementations • Findings (EMNLP) 2021 • Xu Wang, Hainan Zhang, Shuai Zhao, Yanyan Zou, Hongshen Chen, Zhuoye Ding, Bo Cheng, Yanyan Lan
Furthermore, the consistency signals between each candidate and the speaker's own history are considered to drive a model to prefer a candidate that is logically consistent with the speaker's history logic.
1 code implementation • EMNLP 2021 • Jiale Han, Bo Cheng, Wei Lu
Few-shot relation extraction (FSRE) focuses on recognizing novel relations by learning with merely a handful of annotated instances.
1 code implementation • 20 May 2021 • Bo Cheng, Ruhui Xue, Hang Yang, Laili Zhu, Wei Xiang
We propose a deep learning model that can help radiologists and clinicians use chest X-rays to diagnose COVID-19 cases and show the diagnostic features of pneumonia.
no code implementations • 1 Apr 2021 • Xu Wang, Shuai Zhao, Bo Cheng, Jiale Han, Yingting Li, Hao Yang, Ivan Sekulic, Guoshun Nan
Question Answering (QA) models over Knowledge Bases (KBs) are capable of providing more precise answers by utilizing relation information among entities.
2 code implementations • 18 Mar 2021 • Yang Guan, Yangang Ren, Qi Sun, Shengbo Eben Li, Haitong Ma, Jingliang Duan, Yifan Dai, Bo Cheng
In this paper, we present an interpretable and computationally efficient framework called integrated decision and control (IDC) for automated vehicles, which decomposes the driving task into static path planning and dynamic optimal tracking that are structured hierarchically.
2 code implementations • 23 Feb 2021 • Yang Guan, Jingliang Duan, Shengbo Eben Li, Jie Li, Jianyu Chen, Bo Cheng
Formally, MPG is constructed as a weighted average of the data-driven and model-driven PGs, where the former is the derivative of the learned Q-value function, and the latter is that of the model-predictive return.
no code implementations • 23 Feb 2021 • Zhengyu Liu, Jingliang Duan, Wenxuan Wang, Shengbo Eben Li, Yuming Yin, Ziyu Lin, Qi Sun, Bo Cheng
This paper proposes an off-line algorithm, called Recurrent Model Predictive Control (RMPC), to solve general nonlinear finite-horizon optimal control problems.
no code implementations • 20 Feb 2021 • Zhengyu Liu, Jingliang Duan, Wenxuan Wang, Shengbo Eben Li, Yuming Yin, Ziyu Lin, Bo Cheng
This paper proposes an offline control algorithm, called Recurrent Model Predictive Control (RMPC), to solve large-scale nonlinear finite-horizon optimal control problems.
no code implementations • COLING 2020 • Xu Wang, Shuai Zhao, Jiale Han, Bo Cheng, Hao Yang, Jianchang Ao, Zhenzi Li
The structural information of Knowledge Bases (KBs) has proven effective to Question Answering (QA).
no code implementations • Findings of the Association for Computational Linguistics 2020 • Jiale Han, Bo Cheng, Xu Wang
The incompleteness of knowledge base (KB) is a vital factor limiting the performance of question answering (QA).
no code implementations • 28 Feb 2020 • Yao Mu, Shengbo Eben Li, Chang Liu, Qi Sun, Bingbing Nie, Bo Cheng, Baiyu Peng
This paper presents a mixed reinforcement learning (mixed RL) algorithm by simultaneously using dual representations of environmental dynamics to search the optimal policy with the purpose of improving both learning accuracy and training speed.
3 code implementations • 9 Jan 2020 • Jingliang Duan, Yang Guan, Shengbo Eben Li, Yangang Ren, Bo Cheng
In reinforcement learning (RL), function approximation errors are known to easily lead to the Q-value overestimations, thus greatly reducing policy performance.
no code implementations • 23 Dec 2019 • Yang Guan, Shengbo Eben Li, Jingliang Duan, Jie Li, Yangang Ren, Qi Sun, Bo Cheng
Reinforcement learning (RL) algorithms have been successfully applied to a range of challenging sequential decision making and control tasks.
no code implementations • 26 Nov 2019 • Jingliang Duan, Zhengyu Liu, Shengbo Eben Li, Qi Sun, Zhenzhong Jia, Bo Cheng
CADP linearizes the constrained optimization problem locally into a quadratically constrained linear programming problem, and then obtains the optimal update of the policy network by solving its dual problem.
no code implementations • 6 Jun 2019 • Long Xin, Pin Wang, Ching-Yao Chan, Jianyu Chen, Shengbo Eben Li, Bo Cheng
As autonomous vehicles (AVs) need to interact with other road users, it is of importance to comprehensively understand the dynamic traffic environment, especially the future possible trajectories of surrounding vehicles.
no code implementations • WS 2018 • Sizhen Li, Shuai Zhao, Bo Cheng, Hao Yang
With huge amount of information generated every day on the web, fact checking is an important and challenging task which can help people identify the authenticity of most claims as well as providing evidences selected from knowledge source like Wikipedia.