TH
Ting Hua
cs.CLcs.AIcs.LGcs.CRcs.CYcs.HCcs.SIInternetModels, Theoreticalphysics.soc-ph
On Valency
published · living versionsW_gupj3vwm·v1 · currentpublished
'Beating the news' with EMBERS: Forecasting Civil Unrest using Open Source Indicators
with Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah, Nathan Self +25
1 version
Preprints & journals
8 papers in the corpus · 2014–2025Dynamic Noise Preference Optimization: Self-Improvement of Large Language Models with Self-Synthetic Data2502.05400v4 · Haoyan Yang, Khiem Le, Ting Hua et al.2025 · 0 citationsarXiv
ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning2501.15316v2 · Shangqian Gao, Ting Hua, Reza Shirkavand et al.2025 · 0 citationsarXiv
Exploring Conversational Design Choices in LLMs for Pedagogical Purposes: Socratic and Narrative Approaches for Improving Instructor's Teaching Practice2509.12107v1 · Si Chen, Isabel R. Molnar, Peiyu Li et al.2025 · 0 citationsarXiv
DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models2410.11988v2 · Shangqian Gao, Chi-Heng Lin, Ting Hua et al.2024 · 12 citationsarXiv
TrojLLM: A Black-box Trojan Prompt Attack on Large Language Models2306.06815v3 · Jiaqi Xue, Mengxin Zheng, Ting Hua et al.2023 · 15 citationsarXiv
Hyperparameter-free Continuous Learning for Domain Classification in Natural Language Understanding2201.01420v1 · Ting Hua, Yilin Shen, Changsheng Zhao et al.2022 · 3 citationsProceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies,pages 2669--2678
Unsupervised spatial event detection in targeted domains with applications to civil unrest modeling.25350136 · Zhao, Liang, Chen, Feng, Dai, Jing et al.2015 · 66 citationsPloS one. 2014;9(10):e110206
'Beating the news' with EMBERS: Forecasting Civil Unrest using Open Source Indicators1402.7035v2 · Naren Ramakrishnan, Patrick Butler, Sathappan Muthiah et al.2014 · 49 citationsarXivon Valency
Career total: 22 works. 8 are in this corpus.
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