Computer Science > Artificial Intelligence
[Submitted on 5 Sep 2024
(v1)
, last revised 1 Sep 2025 (this version, v3)]
Title: TRACE-CS: A Hybrid Logic-LLM System for Explainable Course Scheduling
Title: TRACE-CS:一种可解释课程调度的混合逻辑-大语言模型系统
Abstract: 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.
Submission history
From: Stylianos Loukas Vasileiou [view email][v1] Thu, 5 Sep 2024 16:24:42 UTC (730 KB)
[v2] Tue, 8 Oct 2024 14:12:00 UTC (730 KB)
[v3] Mon, 1 Sep 2025 16:10:22 UTC (841 KB)
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