4 citations · 4 across the 7 of their papers we have counts for
5 papers · 1 filter
Toward Effective and Reliable LLM Agents via Dynamic Ontology
Xiaohui Zhang, Zequn Sun, Chengyuan Yang +3
Large language model (LLM) agents rely heavily on knowledge encoded in model parameters or presented as unstructured context. In domain-specific tasks, this leaves important semant…
Intelligent Multimodal Retrieval and Reasoning for Geospatial Knowledge Discovery on the I-GUIDE Platform
Yunfan Kang, Erick Li, Furqan Baig +4
Geospatial knowledge discovery increasingly requires search across heterogeneous artifacts: datasets, maps, notebooks, software, publications, and the provenance links among them.…
EIBench: A Simulator-Based Benchmark and Turn-Credit RL for Emotion Management
Rongzhi Zhu, Xiang Huang, Yuchuan Wu +8
Emotional intelligence (EI) in Large Language Models (LLMs) is often evaluated through static understanding tasks or single-response dialogue generation. However, emotion managemen…
Harnessing Structural Context for Entity Alignment Foundation Models
Xingyu Chen, Yuanning Cui, Zequn Sun +1
Entity alignment (EA) aims to identify equivalent entities across heterogeneous knowledge graphs (KGs) and is a key component of knowledge fusion and cross-KG reasoning. The recent…
Breaking the Reasoning Horizon in Entity Alignment Foundation Models
Yuanning Cui, Zequn Sun, Wei Hu +2
Entity alignment (EA) is critical for knowledge graph (KG) fusion. Existing EA models lack transferability and are incapable of aligning unseen KGs without retraining. While using…