9 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…
GraphOracle: Efficient Fully-Inductive Knowledge Graph Reasoning via Relation-Dependency Graphs
Enjun Du, Siyi Liu, Yongqi Zhang
Knowledge graph reasoning in the fully-inductive setting, where both entities and relations at test time are unseen during training, remains an open challenge. In this work, we int…
Benchmarking drug-drug interaction prediction methods: a perspective of distribution changes
Zhenqian Shen, Mingyang Zhou, Yongqi Zhang +1
Motivation: Emerging drug-drug interaction (DDI) prediction is crucial for new drugs but is hindered by distribution changes between known and new drugs in real-world scenarios. Cu…
Case-Based Reasoning Enhances the Predictive Power of LLMs in Drug-Drug Interaction
Guangyi Liu, Yongqi Zhang, Xunyuan Liu +1
Drug-drug interaction (DDI) prediction is critical for treatment safety. While large language models (LLMs) show promise in pharmaceutical tasks, their effectiveness in DDI predict…
Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering
Guangyi Liu, Yongqi Zhang, Yong Li +1
Large Language Models (LLMs) excel at intuitive, implicit reasoning. Guiding LLMs to construct thought chains can enhance their deliberate reasoning abilities, but also faces chall…
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…