Furong Huang
Affiliations:- University of Maryland, College Park, USA
According to our database1,
Furong Huang
authored at least 165 papers
between 2010 and 2024.
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Bibliography
2024
Industrial technology network security measurement in international trade under discrete hopfield neural network.
J. Comput. Methods Sci. Eng., 2024
J. Biomed. Informatics, 2024
Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayesian Theory.
CoRR, 2024
AdvBDGen: Adversarially Fortified Prompt-Specific Fuzzy Backdoor Generator Against LLM Alignment.
CoRR, 2024
GenARM: Reward Guided Generation with Autoregressive Reward Model for Test-time Alignment.
CoRR, 2024
Towards Self-Improvement of LLMs via MCTS: Leveraging Stepwise Knowledge with Curriculum Preference Learning.
CoRR, 2024
Boosting Sample Efficiency and Generalization in Multi-agent Reinforcement Learning via Equivariance.
CoRR, 2024
Easy2Hard-Bench: Standardized Difficulty Labels for Profiling LLM Performance and Generalization.
CoRR, 2024
Balancing Label Imbalance in Federated Environments Using Only Mixup and Artificially-Labeled Noise.
CoRR, 2024
Automatic Pseudo-Harmful Prompt Generation for Evaluating False Refusals in Large Language Models.
CoRR, 2024
Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?
CoRR, 2024
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion.
CoRR, 2024
CoRR, 2024
CoRR, 2024
Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement.
CoRR, 2024
CoRR, 2024
CoRR, 2024
MaxMin-RLHF: Towards Equitable Alignment of Large Language Models with Diverse Human Preferences.
CoRR, 2024
CoRR, 2024
Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generation.
CoRR, 2024
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences.
CoRR, 2024
conv_einsum: A Framework for Representation and Fast Evaluation of Multilinear Operations in Convolutional Tensorial Neural Networks.
CoRR, 2024
Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM).
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
COPlanner: Plan to Roll Out Conservatively but to Explore Optimistically for Model-Based RL.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
PARL: A Unified Framework for Policy Alignment in Reinforcement Learning from Human Feedback.
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Proceedings of the Twelfth International Conference on Learning Representations, 2024
Multi-Stage Balanced Distillation: Addressing Long-Tail Challenges in Sequence-Level Knowledge Distillation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
AutoHallusion: Automatic Generation of Hallucination Benchmarks for Vision-Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024
Hallusionbench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024
Explore Spurious Correlations at the Concept Level in Language Models for Text Classification.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024
2023
Cogn. Process., November, 2023
Trans. Mach. Learn. Res., 2023
CoRR, 2023
CoRR, 2023
RealFM: A Realistic Mechanism to Incentivize Data Contribution and Device Participation.
CoRR, 2023
CoRR, 2023
Safe and Robust Multi-Agent Reinforcement Learning for Connected Autonomous Vehicles under State Perturbations.
CoRR, 2023
Equal Long-term Benefit Rate: Adapting Static Fairness Notions to Sequential Decision Making.
CoRR, 2023
More Context, Less Distraction: Visual Classification by Inferring and Conditioning on Contextual Attributes.
CoRR, 2023
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations.
CoRR, 2023
CoRR, 2023
Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in Multi-Agent RL.
CoRR, 2023
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint.
CoRR, 2023
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Learning Unforeseen Robustness from Out-of-distribution Data Using Equivariant Domain Translator.
Proceedings of the International Conference on Machine Learning, 2023
Proceedings of the International Conference on Machine Learning, 2023
STEERING : Stein Information Directed Exploration for Model-Based Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function.
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Proceedings of the Eleventh International Conference on Learning Representations, 2023
Posterior Coreset Construction with Kernelized Stein Discrepancy for Model-Based Reinforcement Learning.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
NeuroImage, 2022
Frontiers Artif. Intell., 2022
Dagstuhl Reports, 2022
CoRR, 2022
An Energy Optimized Specializing DAG Federated Learning based on Event Triggered Communication.
CoRR, 2022
CoRR, 2022
Certifiably Robust Policy Learning against Adversarial Communication in Multi-agent Systems.
CoRR, 2022
End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking.
CoRR, 2022
Adversarial Auto-Augment with Label Preservation: A Representation Learning Principle Guided Approach.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
Reinforcement Learning under a Multi-agent Predictive State Representation Model: Method and Theory.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL.
Proceedings of the Tenth International Conference on Learning Representations, 2022
Tuformer: Data-driven Design of Transformers for Improved Generalization or Efficiency.
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching.
CoRR, 2021
CoRR, 2021
CoRR, 2021
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations.
CoRR, 2021
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021
Understanding the Generalization Benefit of Model Invariance from a Data Perspective.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Mathematical and Scientific Machine Learning, 2021
Proceedings of the 9th International Conference on Learning Representations, 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
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Novel reconciliation protocol based on spinal code for continuous-variable quantum key distribution.
Quantum Inf. Process., 2020
The function of the hippocampus and middle temporal gyrus in forming new associations and concepts during the processing of novelty and usefulness features in creative designs.
NeuroImage, 2020
Dagstuhl Reports, 2020
CoRR, 2020
Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets.
CoRR, 2020
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers.
CoRR, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Intelligent Systems and Applications, 2020
An end-to-end Differentially Private Latent Dirichlet Allocation Using a Spectral Algorithm.
Proceedings of the 37th International Conference on Machine Learning, 2020
Proceedings of the 8th International Conference on Learning Representations, 2020
Proceedings of the "I Can't Believe It's Not Better!" at NeurIPS Workshops, 2020
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
CoRR, 2019
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019
Proceedings of the 30th British Machine Vision Conference 2019, 2019
2018
Neural correlates of novelty and appropriateness processing in externally induced constraint relaxation.
NeuroImage, 2018
Guaranteed Simultaneous Asymmetric Tensor Decomposition via Orthogonalized Alternating Least Squares.
CoRR, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2016
PhD thesis, 2016
CoRR, 2016
Unsupervised learning of transcriptional regulatory networks via latent tree graphical models.
CoRR, 2016
CoRR, 2016
2015
The neural basis of novelty and appropriateness in processing of creative chunk decomposition.
NeuroImage, 2015
J. Mach. Learn. Res., 2015
Proceedings of the 1st Workshop on Feature Extraction: Modern Questions and Challenges, 2015
Are You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden Group Dynamics via Conditional Latent Tree Models].
Proceedings of the 2015 IEEE International Conference on Data Mining, 2015
Proceedings of The 28th Conference on Learning Theory, 2015
2014
CoRR, 2014
2013
CoRR, 2013
FCD: Fast-concurrent-distributed load balancing under switching costs and imperfect observations.
Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013
2012
High-dimensional Gaussian graphical model selection: walk summability and local separation criterion.
J. Mach. Learn. Res., 2012
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
2011
CoRR, 2011
2010
Prediction-Based Spectrum Aggregation with Hardware Limitation in Cognitive Radio Networks.
Proceedings of the 71st IEEE Vehicular Technology Conference, 2010