Huaxiu Yao

Orcid: 0000-0002-8691-9629

According to our database1, Huaxiu Yao authored at least 99 papers between 2017 and 2024.

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Bibliography

2024
Conservative Prediction via Data-Driven Confidence Minimization.
Trans. Mach. Learn. Res., 2024

VHELM: A Holistic Evaluation of Vision Language Models.
CoRR, 2024

On Unsupervised Prompt Learning for Classification with Black-box Language Models.
CoRR, 2024

NEAT: Nonlinear Parameter-efficient Adaptation of Pre-trained Models.
CoRR, 2024

Embodiment-Agnostic Action Planning via Object-Part Scene Flow.
CoRR, 2024

Can Editing LLMs Inject Harm?
CoRR, 2024

RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models.
CoRR, 2024

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
CoRR, 2024

It Takes Two: On the Seamlessness between Reward and Policy Model in RLHF.
CoRR, 2024

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models.
CoRR, 2024

Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement.
CoRR, 2024

Calibrated Self-Rewarding Vision Language Models.
CoRR, 2024

LITE: Modeling Environmental Ecosystems with Multimodal Large Language Models.
CoRR, 2024

Electrocardiogram Instruction Tuning for Report Generation.
CoRR, 2024

Distribution-Free Fair Federated Learning with Small Samples.
CoRR, 2024

C<sup>3</sup>: Confidence Calibration Model Cascade for Inference-Efficient Cross-Lingual Natural Language Understanding.
CoRR, 2024

Word-Sequence Entropy: Towards Uncertainty Estimation in Free-Form Medical Question Answering Applications and Beyond.
CoRR, 2024

AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition.
CoRR, 2024

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning.
CoRR, 2024

Selective Learning: Towards Robust Calibration with Dynamic Regularization.
CoRR, 2024

Generating Chain-of-Thoughts with a Direct Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought.
CoRR, 2024

Multimodal Clinical Trial Outcome Prediction with Large Language Models.
CoRR, 2024

Mementos: A Comprehensive Benchmark for Multimodal Large Language Model Reasoning over Image Sequences.
CoRR, 2024

TrustLLM: Trustworthiness in Large Language Models.
CoRR, 2024

AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

CAT: Interpretable Concept-based Taylor Additive Models.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

One Meta-tuned Transformer is What You Need for Few-shot Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Conformal Prediction for Deep Classifier via Label Ranking.
Proceedings of the Forty-first International Conference on Machine Learning, 2024


HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Improving Domain Generalization with Domain Relations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fine-Tuning Language Models for Factuality.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

How Many Are in This Image A Safety Evaluation Benchmark for Vision LLMs.
Proceedings of the Computer Vision - ECCV 2024, 2024

Multimodal Representation Learning by Alternating Unimodal Adaptation.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Towards Reliable Learning in the Wild: Generalization and Adaptation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations.
Trans. Mach. Learn. Res., 2023

Holistic Evaluation of Language Models.
Trans. Mach. Learn. Res., 2023

How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs.
CoRR, 2023

FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems.
CoRR, 2023

Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification.
CoRR, 2023

Holistic Analysis of Hallucination in GPT-4V(ision): Bias and Interference Challenges.
CoRR, 2023

Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks.
CoRR, 2023

Leveraging Domain Relations for Domain Generalization.
CoRR, 2023

An Iterative Self-Learning Framework for Medical Domain Generalization.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Meta-Learning with Neural Bandit Scheduler.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Train-Validation Split in Meta-Learning with Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Macedon: Minimizing Representation Coding Rate Reduction for Cross-Lingual Natural Language Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
Knowledge-Driven New Drug Recommendation.
CoRR, 2022

Diversify and Disambiguate: Learning From Underspecified Data.
CoRR, 2022

GRASP: Navigating Retrosynthetic Planning with Goal-driven Policy.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

C-Mixup: Improving Generalization in Regression.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Spatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Improving Out-of-Distribution Robustness via Selective Augmentation.
Proceedings of the International Conference on Machine Learning, 2022

Meta-Learning with Fewer Tasks through Task Interpolation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Improving Meta-learning for Low-resource Text Classification and Generation via Memory Imitation.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Inductive Contextual Relation Learning for Personalization.
ACM Trans. Inf. Syst., 2021

Citywide Traffic Volume Inference with Surveillance Camera Records.
IEEE Trans. Big Data, 2021

Relation-aware Meta-learning for E-commerce Market Segment Demand Prediction with Limited Records.
Proceedings of the WSDM '21, 2021

Meta-learning with an Adaptive Task Scheduler.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Functionally Regionalized Knowledge Transfer for Low-resource Drug Discovery.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Improving Generalization in Meta-learning via Task Augmentation.
Proceedings of the 38th International Conference on Machine Learning, 2021

Knowledge-Aware Meta-learning for Low-Resource Text Classification.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Neural Utility Functions.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Relation-aware Meta-learning for Market Segment Demand Prediction with Limited Records.
CoRR, 2020

Don't Overlook the Support Set: Towards Improving Generalization in Meta-learning.
CoRR, 2020

Graph Convolutional Networks against Degree-Related Biases.
CoRR, 2020

Transferring Robustness for Graph Neural Network Against Poisoning Attacks.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Learning with Small Data.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Online Structured Meta-learning.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning with Small Data.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Automated Relational Meta-learning.
Proceedings of the 8th International Conference on Learning Representations, 2020

Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Few-Shot Knowledge Graph Completion.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

MetaLight: Value-Based Meta-Reinforcement Learning for Traffic Signal Control.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Graph Few-Shot Learning via Knowledge Transfer.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Predicting Academic Performance for College Students: A Campus Behavior Perspective.
ACM Trans. Intell. Syst. Technol., 2019

Non-Stationary Model for Crime Rate Inference Using Modern Urban Data.
IEEE Trans. Big Data, 2019

Transferable Neural Processes for Hyperparameter Optimization.
CoRR, 2019

Targeted Source Detection for Environmental Data.
CoRR, 2019

Robust Graph Neural Network Against Poisoning Attacks via Transfer Learning.
CoRR, 2019

Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction.
Proceedings of the World Wide Web Conference, 2019

Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference.
Proceedings of the World Wide Web Conference, 2019

Hierarchically Structured Meta-learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Modeling Spatial-Temporal Dynamics for Traffic Prediction.
CoRR, 2018

IntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Representation Learning for Large-Scale Dynamic Networks.
Proceedings of the Database Systems for Advanced Applications, 2018

Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Predicting Academic Performance via Semi-supervised Learning with Constructed Campus Social Network.
Proceedings of the Database Systems for Advanced Applications, 2017


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