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20242026
most citedEnhancing Time Series Forecasting via Multi-Level Text Alignment with LLMs

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2026

When Does Consistency Pay Off? Relational Constraints for LLM-based Document-Level Relation Extraction under Incomplete Annotations

Mingxuan Sun

Consistency-based repair is widely assumed to improve LLM-based document-level relation extraction (DocRE), but this assumption can fail when the benchmark itself is incompletely a…

cs.CR2026

Spatiotemporal-Aware Bit-Flip Injection on DNN-based Advanced Driver Assistance Systems (extended version)

Taibiao Zhao, Xiang Zhang, Mingxuan Sun +2

Modern advanced driver assistance systems (ADAS) rely on deep neural networks (DNNs) for perception and planning. Since DNNs' parameters reside in DRAM during inference, bit flips…

cs.LG2025

FLEX-MoE: Federated Mixture-of-Experts with Load-balanced Expert Assignment for Edge Computing

Boyang Zhang, Xiaobing Chen, Songyang Zhang +4

Mixture-of-Experts (MoE) models enable scalable neural networks through conditional computation, offering enhanced effectiveness and efficiency for next-generation wireless communi…

cs.LG2025

Learning to Rank with Top- Fairness

Boyang Zhang, Quanqi Hu, Mingxuan Sun +2

Fairness in ranking models is crucial, as disparities in exposure can disproportionately affect protected groups. Most fairness-aware ranking systems focus on ensuring comparable a…

cs.LG2025

Pruning and Malicious Injection: A Retraining-Free Backdoor Attack on Transformer Models

Taibiao Zhao, Mingxuan Sun, Hao Wang +2

Transformer models have demonstrated exceptional performance and have become indispensable in computer vision (CV) and natural language processing (NLP) tasks. However, recent stud…

cs.LG2025

Efficient Training of Large-Scale AI Models Through Federated Mixture-of-Experts: A System-Level Approach

Xiaobing Chen, Boyang Zhang, Xiangwei Zhou +4

The integration of Federated Learning (FL) and Mixture-of-Experts (MoE) presents a compelling pathway for training more powerful, large-scale artificial intelligence models (LAMs)…

cs.CL2025★ 1 cited

Enhancing Time Series Forecasting via Multi-Level Text Alignment with LLMs

Taibiao Zhao, Xiaobing Chen, Mingxuan Sun

The adaptation of large language models (LLMs) to time series forecasting poses unique challenges, as time series data is continuous in nature, while LLMs operate on discrete token…

cs.GT2024

DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game

Xiaobing Chen, Xiangwei Zhou, Songyang Zhang +1

Despite some promising results in federated learning using game-theoretical methods, most existing studies mainly employ a one-level game in either a cooperative or competitive env…