activity
20222026
most citedExploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights

41 citations · 163 across the 57 of their papers we have counts for

collaborators

64 papers

cs.LG2026

World2TS: Real-World Event Context for Time-Series Forecasting

Zhiding Liu, Jiqian Yang, Mingyue Cheng +2

Time-series forecasting plays a vital role in a wide range of real-world applications. Recent approaches have achieved strong performance by modeling temporal correlations and cros…

cs.IR2026

ScholarQuest: A Taxonomy-Guided Benchmark for Agentic Academic Paper Search in Open Literature Environments

Tingyue Pan, Mingyue Cheng, Daoyu Wang +4

Academic paper search is a core step in scientific research, and LLM-based search agents are emerging as a promising paradigm for iterative, intent-driven literature exploration. H…

cs.CL2026

ScholarSum: Student-Teacher Abstractive Summarization via Knowledge Graph Reasoning and Reflective Refinement

Bohou Zhang, Xiaoyu Tao, Mingyue Cheng +2

Abstractive summarization plays a crucial role in enabling efficient understanding of scientific literature, yet it inherently demands both linguistic fluency and factual faithfuln…

cs.CL2026

TabClaw: An Interactive and Self-Evolving Agent for Spreadsheet Manipulation and Table Reasoning

Mingyue Cheng, Shuo Yu, Daoyu Wang +5

Spreadsheets and tables are widely used representations for structured data analysis, but effective analysis still requires substantial manual effort and domain expertise. Recent l…

cs.LG2026

AgentWorld: A Data Factory for Training LLM Agents from Multi-Turn Interactions

Daoyu Wang, Mingyue Cheng, Qingchuan Li +4

Training LLMs to act as capable agents requires learning from multi-turn interactions with environments. However, multi-turn interaction trajectories generated by heterogeneous age…

cs.LG2026

CastFlow: Bridging Evidence Acquisition and Accurate Prediction in Agentic Time Series Forecasting

Bokai Pan, Mingyue Cheng, Zhiding Liu +6

Time series forecasting is a fundamental task in temporal data analytics, and large language model (LLM)-based agents offer a promising paradigm through autonomous tool interaction…

cs.AI2026

GeoDecider: An Evidence-Grounded Agent for Geological Interpretation via Deliberative Reasoning

Xiaoyu Tao, Mingyue Cheng, Jiahao Wang +6

Geological interpretation infers subsurface properties and structures from indirect geophysical observations. Well-log classification provides a measurable setting by assigning geo…

cs.LG2026

Position: Beyond Model-Centric Prediction -- Agentic Time Series Forecasting

Mingyue Cheng, Xiaoyu Tao, Qi Liu +2

Time series forecasting has traditionally been formulated as a model-centric, static, and single-pass prediction problem that maps historical observations to future values. While t…

cs.CL2026

TableMind++: An Uncertainty-Aware Programmatic Agent for Tool-Augmented Table Reasoning

Mingyue Cheng, Shuo Yu, Chuang Jiang +5

Table reasoning requires models to jointly perform semantic understanding and precise numerical operations. Most existing methods rely on a single-turn reasoning paradigm over tabl…

cs.LG2026

StaTS: Spectral Trajectory Schedule Learning for Adaptive Time Series Forecasting with Frequency Guided Denoiser

Jintao Zhang, Zirui Liu, Mingyue Cheng +3

Diffusion models have been used for probabilistic time series forecasting and show strong potential. However, fixed noise schedules often produce intermediate states that are hard…

cs.LG2026

CoGenCast: A Coupled Autoregressive-Flow Generative Framework for Time Series Forecasting

Mingyue Cheng, Yaguo Liu, Daoyu Wang +2

Time series forecasting can be viewed as a generative problem that requires both semantic understanding over contextual conditions and stochastic modeling of continuous temporal dy…

cs.LG2026

MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning

Xiaoyu Tao, Mingyue Cheng, Ze Guo +4

Time series forecasting (TSF) plays a critical role in decision-making for many real-world applications. Recently, large language model (LLM)- based forecasters have made promising…

cs.LG2026

InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement

Mingyue Cheng, Xiaoyu Tao, Huajian Zhang +5

Most existing time series classification methods adopt a discriminative paradigm that maps input sequences directly to one-hot encoded class labels. While effective, this paradigm…

cs.LG2026

PiXTime: A Model for Federated Time Series Forecasting with Heterogeneous Data across Nodes

Yiming Zhou, Jiahao Wang, Mingyue Cheng +3

While collaborative forecasting on distributed time series is highly desirable, directly pooling localized datasets is often impractical due to data sharing constraints. Federated…

cs.CL2026

Mind2Report: Expert-Level Commercial Report Synthesis via Cognitive Deep Research Agent

Mingyue Cheng, Daoyu Wang, Qi Liu +7

Synthesizing informative commercial reports from massive and noisy web sources is critical for high-stakes business decisions. Although recent deep research agents (DRAs) achieve n…

cs.LG2025

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…

cs.CL2025

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…

cs.AI2025

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…

cs.CL2025

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…

cs.AI2025

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…

cs.IR2025

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…

cs.IR2025

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…

cs.CV2025

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…

cs.AI2025

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…