18 citations · 63 across the 54 of their papers we have counts for
5 papers · 1 filter
RecNet: Self-Evolving Preference Propagation for Agentic Recommender Systems
Bingqian Li, Xiaolei Wang, Junyi Li +5
Agentic recommender systems leverage Large Language Models (LLMs) to model complex user behaviors and support personalized decision-making. However, existing methods primarily mode…
Experience-Guided Reflective Co-Evolution of Prompts and Heuristics for Automatic Algorithm Design
Yihong Liu, Junyi Li, Wayne Xin Zhao +2
Combinatorial optimization problems are traditionally tackled with handcrafted heuristic algorithms, which demand extensive domain expertise and significant implementation effort.…
Sticker-TTS: Learn to Utilize Historical Experience with a Sticker-driven Test-Time Scaling Framework
Jie Chen, Jinhao Jiang, Yingqian Min +4
Large reasoning models (LRMs) have exhibited strong performance on complex reasoning tasks, with further gains achievable through increased computational budgets at inference. Howe…
R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning
Huatong Song, Jinhao Jiang, Yingqian Min +5
Existing Large Reasoning Models (LRMs) have shown the potential of reinforcement learning (RL) to enhance the complex reasoning capabilities of Large Language Models~(LLMs). While…
Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning Systems
Yingqian Min, Zhipeng Chen, Jinhao Jiang +11
Recently, slow-thinking reasoning systems, such as o1, have demonstrated remarkable capabilities in solving complex reasoning tasks. These systems typically engage in an extended t…