Hongjie Chen

Orcid: 0000-0002-8755-2099

Affiliations:

Virginia Tech, Blacksburg, VA, USA

According to our database¹, Hongjie Chen authored at least 33 papers between 2018 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Bibliography

2026

A Survey on LLM-based Conversational User Simulation.

[BibT_eX]

[DOI]

CoRR, April, 2026

Variable-Length Audio Fingerprinting.

[BibT_eX]

[DOI]

CoRR, March, 2026

InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions.

[BibT_eX]

[DOI]

CoRR, March, 2026

Human-Aligned MLLM Judges for Fine-Grained Image Editing Evaluation: A Benchmark, Framework, and Analysis.

[BibT_eX]

[DOI]

CoRR, February, 2026

Segment Length Matters: A Study of Segment Lengths on Audio Fingerprinting Performance.

[BibT_eX]

[DOI]

CoRR, January, 2026

LayoutBench: Performance Benchmarking of Cloud Storage Layouts for Multimedia Data.

[BibT_eX]

[DOI]

Proceedings of the Sixth European Workshop on Machine Learning and Systems, EuroMLSys 2026, 2026

A Survey on LLM-based Conversational User Simulation.

[BibT_eX]

[DOI]

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

2025

Learning to Route LLMs from Bandit Feedback: One Policy, Many Trade-offs.

[BibT_eX]

[DOI]

CoRR, October, 2025

Measuring Time-Series Dataset Similarity using Wasserstein Distance.

[BibT_eX]

[DOI]

CoRR, July, 2025

A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality.

[BibT_eX]

[DOI]

CoRR, July, 2025

Efficient Model Selection for Time Series Forecasting via LLMs.

[BibT_eX]

[DOI]

CoRR, April, 2025

Edges Matter: An Analysis of Graph Time-Series Representations for Temporal Networks.

[BibT_eX]

[DOI]

IEEE Trans. Netw. Sci. Eng., 2025

Personalization of Large Language Models: A Survey.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2025

Forecasting Time Series with LLMs via Patch-Based Prompting and Decomposition.

[BibT_eX]

[DOI]

Mayank Bumb

Anshul Vemulapalli

Sri Harsha Vardhan Prasad Jella

Proceedings of the 39th Pacific Asia Conference on Language, Information and Computation, 2025

Probabilistic Hypergraph Recurrent Neural Networks for Time-series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF International Conference on Computer Vision, ICCV 2025, 2025

A Quantitative Metric Selection Approach for Time-series Forecasting Foundation Models.

[BibT_eX]

[DOI]

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

From Selection to Generation: A Survey of LLM-based Active Learning.

[BibT_eX]

[DOI]

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

GUI Agents: A Survey.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Graph Time-series Modeling in Deep Learning: A Survey.

[BibT_eX]

[DOI]

Hongjie Chen

Hoda Eldardiry

ACM Trans. Knowl. Discov. Data, June, 2024

Graph-based Time-series Forecasting in Deep Learning.

[BibT_eX]

[DOI]

Hongjie Chen

PhD thesis, 2024

GUI Agents: A Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Personalized Multimodal Large Language Models: A Survey.

[BibT_eX]

[DOI]

CoRR, 2024

Evolving Super Graph Neural Networks for Large-Scale Time-Series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2024

A Study of Foundation Models for Large-scale Time-series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2024

LIVE-ITS: LSH-based Interactive Visualization Explorer for Large-Scale Incomplete Time Series.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2024

2023

Graph Deep Factors for Probabilistic Time-series Forecasting.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, February, 2023

Hypergraph Neural Networks for Time-series Forecasting.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Big Data, 2023

2021

Graph Deep Factors for Forecasting with Applications to Cloud Resource Allocation.

[BibT_eX]

[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Context Integrated Relational Spatio-Temporal Resource Forecasting.

[BibT_eX]

[DOI]

Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020

Graph Deep Factors for Forecasting.

[BibT_eX]

[DOI]

CoRR, 2020

A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting.

[BibT_eX]

[DOI]

CoRR, 2020

2018

LncRNA-disease association prediction based on neighborhood information aggregation in neural network.

[BibT_eX]

[DOI]

Alfonso Rodríguez-Patón

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Hongjie Chen

Timeline

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