3 citations · 7 across the 12 of their papers we have counts for
12 papers
ContextFlow: Hierarchical Task-State Alignment for Long-Horizon Embodied Agents
Shuhan Guo, Kun Zhang, Haifei Liu +4
Long-horizon embodied agents increasingly delegate navigation, search, approach, and manipulation to specialist executors. As these executors become stronger, the main bottleneck s…
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…
LLM-Empowered Representation Learning for Emerging Item Recommendation
Ziying Zhang, Quanming Yao, Yaqing Wang
In this work, we tackle the challenge of recommending emerging items, whose interactions gradually accumulate over time. Existing methods often overlook this dynamic process, typic…
Asking LLMs to Verify First is Almost Free Lunch
Shiguang Wu, Quanming Yao
To enhance the reasoning capabilities of Large Language Models (LLMs) without high costs of training, nor extensive test-time sampling, we introduce Verification-First (VF), a stra…
Attending on Multilevel Structure of Proteins enables Accurate Prediction of Cold-Start Drug-Target Interactions
Ziying Zhang, Yaqing Wang, Yuxuan Sun +2
Cold-start drug-target interaction (DTI) prediction focuses on interaction between novel drugs and proteins. Previous methods typically learn transferable interaction patterns betw…
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…
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…
Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions
Yaqing Wang, Hongming Piao, Daxiang Dong +2
In recommendation systems, new items are continuously introduced, initially lacking interaction records but gradually accumulating them over time. Accurately predicting the click-t…
Beyond Scaleup: Knowledge-aware Parsimony Learning from Deep Networks
Quanming Yao, Yongqi Zhang, Yaqing Wang +3
The brute-force scaleup of training datasets, learnable parameters and computation power, has become a prevalent strategy for developing more robust learning models. However, due t…
Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning
Yaqing Wang, Zaifei Yang, Quanming Yao
Background: Discovering potential drug-drug interactions (DDIs) is a long-standing challenge in clinical treatments and drug developments. Recently, deep learning techniques have b…
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction
Shiguang Wu, Yaqing Wang, Quanming Yao
Molecular property prediction (MPP) plays a crucial role in biomedical applications, but it often encounters challenges due to a scarcity of labeled data. Existing works commonly a…