Papers by Rémy Cazabet
ATOM: AdapTive and OptiMized dynamic temporal knowledge graph construction using LLMs (2026.findings-eacl)
Copied to clipboard
| Challenge: | Unstructured data is expanding at an unprecedented rate, and static knowledge graphs are often overlooked due to their dynamic nature and lack of time-sensitive features. |
| Approach: | They propose a few-shot approach that builds and continuously updates Temporal Knowledge Graphs (TKGs) from unstructured texts. |
| Outcome: | Empirical results show that ATOM achieves 18% higher exhaustivity, 33% better stability, and over 90% latency reduction compared to baseline methods. |