8 citations · 22 across the 30 of their papers we have counts for
8 papers · 1 filter
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…
Towards Context-aware Reasoning-enhanced Generative Searching in E-commerce
Zhiding Liu, Ben Chen, Mingyue Cheng +6
Search-based recommendation is one of the most critical application scenarios in e-commerce platforms. Users' complex search contexts--such as spatiotemporal factors, historical in…
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…
Benchmarking Multimodal LLMs on Recognition and Understanding over Chemical Tables
Yitong Zhou, Mingyue Cheng, Qingyang Mao +7
With the widespread application of multimodal large language models in scientific intelligence, there is an urgent need for more challenging evaluation benchmarks to assess their a…
Time Series Forecasting via Reasoning: A Slow-Thinking Approach with Reinforcement Fine-Tuned LLMs
Yitong Zhou, Yucong Luo, Mingyue Cheng +4
To advance time series forecasting (TSF), various methods have been proposed to improve prediction accuracy, evolving from statistical techniques to data-driven deep learning archi…
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…
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-…