Huimin Zeng

Orcid: 0000-0003-0198-2352

Affiliations:
  • University of Illinois Urbana-Champaign, USA


According to our database1, Huimin Zeng authored at least 38 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Transferable Sequential Recommendation via Vector Quantized Meta Learning.
CoRR, 2024

Federated Recommendation via Hybrid Retrieval Augmented Generation.
CoRR, 2024

SymLearn: A Symbiotic Crowd-AI Collective Learning Framework to Web-based Healthcare Policy Adherence Assessment.
Proceedings of the ACM on Web Conference 2024, 2024

MMAdapt: A Knowledge-guided Multi-source Multi-class Domain Adaptive Framework for Early Health Misinformation Detection.
Proceedings of the ACM on Web Conference 2024, 2024

Linear Recurrent Units for Sequential Recommendation.
Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Fair Sequential Recommendation without User Demographics.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Open-Vocabulary Federated Learning with Multimodal Prototyping.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Evidence-Driven Retrieval Augmented Response Generation for Online Misinformation.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

A Domain Adaptive Graph Learning Framework to Early Detection of Emergent Healthcare Misinformation on Social Media.
Proceedings of the Eighteenth International AAAI Conference on Web and Social Media, 2024

Mitigating Demographic Bias of Federated Learning Models via Robust-Fair Domain Smoothing: A Domain-Shifting Approach.
Proceedings of the 44th IEEE International Conference on Distributed Computing Systems, 2024

Train Once, Deploy Anywhere: Matryoshka Representation Learning for Multimodal Recommendation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Tripartite Intelligence: Synergizing Deep Neural Network, Large Language Model, and Human Intelligence for Public Health Misinformation Detection (Archival Full Paper).
Proceedings of the ACM Collective Intelligence Conference, 2024

Fair Federated Learning with Biased Vision-Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Retrieval Augmented Fact Verification by Synthesizing Contrastive Arguments.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Fairness-aware training of face attribute classifiers via adversarial robustness.
Knowl. Based Syst., March, 2023

CollabEquality: A Crowd-AI Collaborative Learning Framework to Address Class-wise Inequality in Web-based Disaster Response.
Proceedings of the ACM Web Conference 2023, 2023

A Crowdsourced Learning Framework to Optimize Cross-Event QoS in AI-powered Social Sensing.
Proceedings of the 20th Annual IEEE International Conference on Sensing, 2023

On Optimizing Model Generality in AI-based Disaster Damage Assessment: A Subjective Logic-driven Crowd-AI Hybrid Learning Approach.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

On Adversarial Robustness of Demographic Fairness in Face Attribute Recognition.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Manipulating Out-Domain Uncertainty Estimation in Deep Neural Networks via Targeted Clean-Label Poisoning.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

MetaAdapt: Domain Adaptive Few-Shot Misinformation Detection via Meta Learning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Zero- and Few-Shot Event Detection via Prompt-Based Meta Learning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

A Crowd-AI Collaborative Duo Relational Graph Learning Framework towards Social Impact Aware Photo Classification.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
CrowdOptim: A Crowd-driven Neural Network Hyperparameter Optimization Approach to AI-based Smart Urban Sensing.
Proc. ACM Hum. Comput. Interact., 2022

Defending Substitution-Based Profile Pollution Attacks on Sequential Recommenders.
Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

On Attacking Out-Domain Uncertainty Estimation in Deep Neural Networks.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Crowd, Expert & AI: A Human-AI Interactive Approach Towards Natural Language Explanation Based COVID-19 Misinformation Detection.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive Adaptation.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Efficient Localness Transformer for Smart Sensor-Based Energy Disaggregation.
Proceedings of the 18th International Conference on Distributed Computing in Sensor Systems, 2022

Domain Adaptation for Question Answering via Question Classification.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

Contrastive Domain Adaptation for Early Misinformation Detection: A Case Study on COVID-19.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Boosting Demographic Fairness of Face Attribute Classifiers via Latent Adversarial Representations.
Proceedings of the IEEE International Conference on Big Data, 2022

Unsupervised Domain Adaptation for COVID-19 Information Service with Contrastive Adversarial Domain Mixup.
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2022

A Knowledge-driven Domain Adaptive Approach to Early Misinformation Detection in an Emergent Health Domain on Social Media.
Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2022

2021
Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders.
CoRR, 2021

Black-Box Attacks on Sequential Recommenders via Data-Free Model Extraction.
Proceedings of the RecSys '21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021, 2021

ExgFair: A Crowdsourcing Data Exchange Approach To Fair Human Face Datasets Augmentation.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021


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