no code implementations • 30 Apr 2024 • Chongyang Shi, Yuheng Bu, Jie Fu
The goal of the observer is to infer some secret, represented by a random variable, from its partial observations, while the goal of the planning agent is to make the secret maximally opaque to the observer while achieving a satisfactory total return.
no code implementations • 26 Apr 2024 • Yinghan Cheng, Qi Zhang, Chongyang Shi, Liang Xiao, Shufeng Hao, Liang Hu
To address these challenges, we present a novel collaborative stance detection framework called (CoSD) which leverages contrastive heterogeneous topic graph learning to learn topic-aware semantics and collaborative signals among texts, topics, and stance labels for enhancing stance detection.
no code implementations • 18 Feb 2024 • Liang Xiao, Qi Zhang, Chongyang Shi, Shoujin Wang, Usman Naseem, Liang Hu
These existing methods fail to handle the complex, subtle twists in news articles, such as syntax-semantics mismatches and prior biases, leading to lower performance and potential failure when modalities or social context are missing.
no code implementations • 21 Dec 2023 • Guangyin Bao, Qi Zhang, Duoqian Miao, Zixuan Gong, Liang Hu, Ke Liu, Yang Liu, Chongyang Shi
In real-world scenarios, multimodal federated learning often faces the practical challenge of intricate modality missing, which poses constraints on building federated frameworks and significantly degrades model inference accuracy.
1 code implementation • 18 Dec 2023 • An Lao, Qi Zhang, Chongyang Shi, Longbing Cao, Kun Yi, Liang Hu, Duoqian Miao
Multimodal content, such as mixing text with images, presents significant challenges to rumor detection in social media.
no code implementations • 25 Oct 2023 • Haoxiang Ma, Chongyang Shi, Shuo Han, Michael R. Dorothy, Jie Fu
This paper studies how covert planning can leverage the coupling of stochastic dynamics and the observer's imperfect observation to achieve optimal task performance without being detected.
no code implementations • 17 Sep 2023 • Xiangrui Su, Qi Zhang, Chongyang Shi, Jiachang Liu, Liang Hu
Existing VQA methods integrate vision modeling and language understanding to explore the deep semantics of the question.
no code implementations • 23 May 2023 • Jiachang Liu, Qi Zhang, Chongyang Shi, Usman Naseem, Shoujin Wang, Ivor Tsang
Abstractive related work generation has attracted increasing attention in generating coherent related work that better helps readers grasp the background in the current research.
no code implementations • 27 Apr 2023 • Qi Zhang, Yayi Yang, Chongyang Shi, An Lao, Liang Hu, Shoujin Wang, Usman Naseem
Accordingly, we propose a novel rumor detection model with hierarchical representation on the bipartite adhoc event trees called BAET.
no code implementations • 3 Apr 2023 • Chongyang Shi, Abhishek N. Kulkarni, Hazhar Rahmani, Jie Fu
Furthermore, if such a strategy does not exist, winning for P1 must entail the price of revealing his secret to the observer.
no code implementations • 3 Jan 2023 • Chongyang Shi, Shuo Han, Jie Fu
In this setup, we investigate P1's strategic planning of action deception that decides when to deviate from the Nash equilibrium in P2's game model and employ a hidden action, so that P1 can maximize the value of action deception, which is the additional payoff compared to P1's payoff in the game where P2 has complete information.
no code implementations • 1 Sep 2022 • Xinyu Jiang, Qi Zhang, Chongyang Shi, Kaiying Jiang, Liang Hu, Shoujin Wang
Story ending generation aims at generating reasonable endings for a given story context.
no code implementations • 29 Jun 2022 • Qi Zhang, Liang Hu, Chongyang Shi, Ke Liu, Longbing Cao
Case-based Reasoning (CBR) on high-dimensional and heterogeneous data is a trending yet challenging and computationally expensive task in the real world.
no code implementations • COLING 2020 • Xu Cao, Deyi Xiong, Chongyang Shi, Chao Wang, Yao Meng, Changjian Hu
Joint intent detection and slot filling has recently achieved tremendous success in advancing the performance of utterance understanding.