12 papers
Mechanistic Attention Guidance for Agent Memory Refinement
Yechao Hong, Haiquan Qiu, Yaqing Wang +1
Existing self-evolving memory systems mainly improve agent memory based on textual outputs, such as task trajectories and reflections. However, this text-based paradigm rarely inco…
Language Model Networks: Supervision-Efficient Learning through Dense Communication
Shiguang Wu, Yaqing Wang, Quanming Yao
Language models are increasingly used not only as standalone predictors but also as components in larger inference systems, from test-time scaling to multi-agent collaboration. We…
Searching Meta Reasoning Skeleton to Guide LLM Reasoning
Ziying Zhang, Yaqing Wang, Quanming Yao
Meta reasoning behaviors work as a skeleton to guide large language model (LLM) reasoning, thus help to improve reasoning performance. However, prior researches implement meta reas…
PSPA-Bench: A Personalized Benchmark for Smartphone GUI Agent
Hongyi Nie, Xunyuan Liu, Yudong Bai +4
Smartphone GUI agents execute tasks by operating directly on app interfaces, offering a path to broad capability without deep system integration. However, real-world smartphone use…
DGNet: Discrete Green Networks for Data-Efficient Learning of Spatiotemporal PDEs
Yingjie Tan, Quanming Yao, Yaqing Wang
Spatiotemporal partial differential equations (PDEs) underpin a wide range of scientific and engineering applications. Neural PDE solvers offer a promising alternative to classical…
Self-Generative Adversarial Fine-Tuning for Large Language Models
Shiguang Wu, Yaqing Wang, Quanming Yao
Fine-tuning large language models (LLMs) for alignment typically relies on supervised fine-tuning or reinforcement learning from human feedback, both limited by the cost and scarci…