41 citations · 163 across the 57 of their papers we have counts for
18 papers · 1 filter
Towards Stable and Structured Time Series Generation with Perturbation-Aware Flow Matching
Jintao Zhang, Mingyue Cheng, Zirui Liu +3
Time series generation is critical for a wide range of applications, which greatly supports downstream analytical and decision-making tasks. However, the inherent temporal heteroge…
Agent-R1: A Unified and Modular Framework for Agentic Reinforcement Learning
Mingyue Cheng, Shuo Yu, Daoyu Wang +7
Large language models (LLMs) have rapidly evolved from single-turn text generators into the foundation of increasingly capable agents. As these agents take on more complex reasonin…
PaperArena: An Evaluation Benchmark for Tool-Augmented Agentic Reasoning on Scientific Literature
Daoyu Wang, Mingyue Cheng, Shuo Yu +4
Understanding and reasoning on the large-scale scientific literature is a crucial touchstone for large language model (LLM) based agents. However, existing works are mainly restric…
MemWeaver: A Hierarchical Memory from Textual Interactive Behaviors for Personalized Generation
Shuo Yu, Mingyue Cheng, Daoyu Wang +4
The primary form of user-internet engagement is shifting from leveraging implicit feedback signals, such as browsing and clicks, to harnessing the rich explicit feedback provided b…
TableMind: An Autonomous Programmatic Agent for Tool-Augmented Table Reasoning
Chuang Jiang, Mingyue Cheng, Xiaoyu Tao +3
Table reasoning requires models to jointly perform comprehensive semantic understanding and precise numerical operations. Although recent large language model (LLM)-based methods h…
Re3: Learning to Balance Relevance & Recency for Temporal Information Retrieval
Jiawei Cao, Jie Ouyang, Zhaomeng Zhou +4
Temporal Information Retrieval (TIR) is a critical yet unresolved task for modern search systems, retrieving documents that not only satisfy a query's information need but also adh…
FlowRec: Prior-Informed Flow Matching for Efficient Sequential Recommendation Generation
Li Li, Mingyue Cheng, Yuyang Ye +2
Sequential recommendation aims to predict each user's next preferred item based on their historical interactions. Recently, diffusion-based approaches have demonstrated strong gene…
Visual Autoregressive Modeling for Instruction-Guided Image Editing
Qingyang Mao, Qi Cai, Yehao Li +5
Recent advances in diffusion models have brought remarkable visual fidelity to instruction-guided image editing. However, their global denoising process inherently entangles the ed…
TestAgent: An Adaptive and Intelligent Expert for Human Assessment
Junhao Yu, Yan Zhuang, YuXuan Sun +5
Accurately assessing internal human states is key to understanding preferences, offering personalized services, and identifying challenges in real-world applications. Originating f…
Are LLMs Stable Formal Logic Translators in Logical Reasoning Across Linguistically Diversified Texts?
Qingchuan Li, Jiatong Li, Zirui Liu +4
Logical reasoning with large language models (LLMs) has received growing attention. One mainstream approach translates natural language into formal logic and then applies symbolic…
am-ELO: A Stable Framework for Arena-based LLM Evaluation
Zirui Liu, Jiatong Li, Yan Zhuang +5
Arena-based evaluation is a fundamental yet significant evaluation paradigm for modern AI models, especially large language models (LLMs). Existing framework based on ELO rating sy…
Can Slow-thinking LLMs Reason Over Time? Empirical Studies in Time Series Forecasting
Mingyue Cheng, Jiahao Wang, Daoyu Wang +3
Time series forecasting (TSF) is a fundamental and widely studied task, spanning methods from classical statistical approaches to modern deep learning and multimodal language model…
Improving Time Series Forecasting via Instance-aware Post-hoc Revision
Zhiding Liu, Mingyue Cheng, Guanhao Zhao +3
Time series forecasting plays a vital role in various real-world applications and has attracted significant attention in recent decades. While recent methods have achieved remarkab…
Multimodal Forecasting of Sparse Intraoperative Hypotension Events Powered by Language Model
Jintao Zhang, Zirui Liu, Mingyue Cheng +5
Intraoperative hypotension (IOH) frequently occurs under general anesthesia and is strongly linked to adverse outcomes such as myocardial injury and increased mortality. Despite it…
A Comprehensive Survey on Cross-Domain Recommendation: Taxonomy, Progress, and Prospects
Hao Zhang, Mingyue Cheng, Qi Liu +5
Recommender systems (RS) have become crucial tools for information filtering in various real world scenarios. And cross domain recommendation (CDR) has been widely explored in rece…
A Survey on Knowledge-Oriented Retrieval-Augmented Generation
Mingyue Cheng, Yucong Luo, Jie Ouyang +9
Retrieval-Augmented Generation (RAG) has gained significant attention in recent years for its potential to enhance natural language understanding and generation by combining large-…
HoH: A Dynamic Benchmark for Evaluating the Impact of Outdated Information on Retrieval-Augmented Generation
Jie Ouyang, Tingyue Pan, Mingyue Cheng +4
While Retrieval-Augmented Generation (RAG) has emerged as an effective approach for addressing the knowledge outdating problem in Large Language Models (LLMs), it still faces a cri…
TextMatch: Enhancing Image-Text Consistency Through Multimodal Optimization
Yucong Luo, Mingyue Cheng, Jie Ouyang +2
Text-to-image generative models excel in creating images from text but struggle with ensuring alignment and consistency between outputs and prompts. This paper introduces TextMatch…