48 citations · 81 across the 10 of their papers we have counts for
11 papers
BYOKG-RAG: Multi-Strategy Graph Retrieval for Knowledge Graph Question Answering
Costas Mavromatis, Soji Adeshina, Vassilis N. Ioannidis +6
Knowledge graph question answering (KGQA) presents significant challenges due to the structural and semantic variations across input graphs. Existing works rely on Large Language M…
GNN-RAG: Graph Neural Retrieval for Large Language Model Reasoning
Costas Mavromatis, George Karypis
Knowledge Graphs (KGs) represent human-crafted factual knowledge in the form of triplets (head, relation, tail), which collectively form a graph. Question Answering over KGs (KGQA)…
Pack of LLMs: Model Fusion at Test-Time via Perplexity Optimization
Costas Mavromatis, Petros Karypis, George Karypis
Fusing knowledge from multiple Large Language Models (LLMs) can combine their diverse strengths to achieve improved performance on a given task. However, current fusion approaches…
SemPool: Simple, robust, and interpretable KG pooling for enhancing language models
Costas Mavromatis, Petros Karypis, George Karypis
Knowledge Graph (KG) powered question answering (QA) performs complex reasoning over language semantics as well as knowledge facts. Graph Neural Networks (GNNs) learn to aggregate…
Which Examples to Annotate for In-Context Learning? Towards Effective and Efficient Selection
Costas Mavromatis, Balasubramaniam Srinivasan, Zhengyuan Shen +4
Large Language Models (LLMs) can adapt to new tasks via in-context learning (ICL). ICL is efficient as it does not require any parameter updates to the trained LLM, but only few an…
Train Your Own GNN Teacher: Graph-Aware Distillation on Textual Graphs
Costas Mavromatis, Vassilis N. Ioannidis, Shen Wang +6
How can we learn effective node representations on textual graphs? Graph Neural Networks (GNNs) that use Language Models (LMs) to encode textual information of graphs achieve state…
ReaRev: Adaptive Reasoning for Question Answering over Knowledge Graphs
Costas Mavromatis, George Karypis
Knowledge Graph Question Answering (KGQA) involves retrieving entities as answers from a Knowledge Graph (KG) using natural language queries. The challenge is to learn to reason ov…
TempoQR: Temporal Question Reasoning over Knowledge Graphs
Costas Mavromatis, Prasanna Lakkur Subramanyam, Vassilis N. Ioannidis +5
Knowledge Graph Question Answering (KGQA) involves retrieving facts from a Knowledge Graph (KG) using natural language queries. A KG is a curated set of facts consisting of entitie…
HeMI: Multi-view Embedding in Heterogeneous Graphs
Costas Mavromatis, George Karypis
Many real-world graphs involve different types of nodes and relations between nodes, being heterogeneous by nature. The representation learning of heterogeneous graphs (HGs) embeds…
Unveiling Anomalous Edges and Nominal Connectivity of Attributed Networks
Konstantinos D. Polyzos, Costas Mavromatis, Vassilis N. Ioannidis +1
Uncovering anomalies in attributed networks has recently gained popularity due to its importance in unveiling outliers and flagging adversarial behavior in a gamut of data and netw…
Graph InfoClust: Leveraging cluster-level node information for unsupervised graph representation learning
Costas Mavromatis, George Karypis
Unsupervised (or self-supervised) graph representation learning is essential to facilitate various graph data mining tasks when external supervision is unavailable. The challenge i…