5 papers · 1 filter
G-reasoner: Foundation Models for Unified Reasoning over Graph-structured Knowledge
Linhao Luo, Zicheng Zhao, Junnan Liu +9
Large language models (LLMs) excel at complex reasoning but remain limited by static and incomplete parametric knowledge. Retrieval-augmented generation (RAG) mitigates this by inc…
Deep Tabular Research via Continual Experience-Driven Execution
Junnan Dong, Chuang Zhou, Zheng Yuan +7
Large language models often struggle with complex long-horizon analytical tasks over unstructured tables, which typically feature hierarchical and bidirectional headers and non-can…
Neuro-Symbolic Entity Alignment via Variational Inference
Shengyuan Chen, Zheng Yuan, Qinggang Zhang +3
Entity alignment (EA) aims to merge two knowledge graphs (KGs) by identifying equivalent entity pairs. Existing methods can be categorized into symbolic and neural models. Symbolic…
CLR-Bench: Evaluating Large Language Models in College-level Reasoning
Junnan Dong, Zijin Hong, Yuanchen Bei +3
Large language models (LLMs) have demonstrated their remarkable performance across various language understanding tasks. While emerging benchmarks have been proposed to evaluate LL…
Logical Reasoning with Relation Network for Inductive Knowledge Graph Completion
Qinggang Zhang, Keyu Duan, Junnan Dong +2
Inductive knowledge graph completion (KGC) aims to infer the missing relation for a set of newly-coming entities that never appeared in the training set. Such a setting is more in…