TRACE-CS: A Hybrid Logic-LLM System for Explainable Course Scheduling
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866912564383842304 |
|---|---|
| author | Vasileiou, Stylianos Loukas Yeoh, William |
| author_facet | Vasileiou, Stylianos Loukas Yeoh, William |
| contents | We present TRACE-CS, a novel hybrid system that combines symbolic reasoning with large language models (LLMs)to address contrastive queries in course scheduling problems. TRACE-CS leverages logic-based techniques to encode scheduling constraints and generate provably correct explanations, while utilizing an LLM to process natural language queries and refine logical explanations into user friendly responses. This system showcases how combining symbolic KR methods with LLMs creates explainable AI agents that balance logical correctness with natural language accessibility, addressing a fundamental challenge in deployed scheduling systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_03671 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | TRACE-CS: A Hybrid Logic-LLM System for Explainable Course Scheduling Vasileiou, Stylianos Loukas Yeoh, William Artificial Intelligence We present TRACE-CS, a novel hybrid system that combines symbolic reasoning with large language models (LLMs)to address contrastive queries in course scheduling problems. TRACE-CS leverages logic-based techniques to encode scheduling constraints and generate provably correct explanations, while utilizing an LLM to process natural language queries and refine logical explanations into user friendly responses. This system showcases how combining symbolic KR methods with LLMs creates explainable AI agents that balance logical correctness with natural language accessibility, addressing a fundamental challenge in deployed scheduling systems. |
| title | TRACE-CS: A Hybrid Logic-LLM System for Explainable Course Scheduling |
| topic | Artificial Intelligence |
| url | https://arxiv.org/abs/2409.03671 |