Symbolic Reasoning

If AI is going to understand people, it first has to understand relationships. But when it comes to parsing character connections from narrative texts — whether news articles, biographies, or novels — even state-of-the-art language models stumble. They hallucinate links, miss cross-sentence cues, and often forget what they’ve just read. Enter SymbolicThought, a hybrid framework that gives LLMs a logic-boosted sidekick: symbolic reasoning. Developed by researchers at King’s College London and CUHK, the system doesn’t just extract character relationships from text; it builds editable graphs, detects logical contradictions, and guides users through verification with a smart, interactive interface. ...

Rules of Engagement: Why LLMs Need Logic to Plan When it comes to language generation, large language models (LLMs) like GPT-4o are top of the class. But ask them to reason through a complex plan — such as reorganizing a logistics network or optimizing staff scheduling — and their performance becomes unreliable. That’s the central finding from ACPBench Hard (Kokel et al., 2025), a new benchmark from IBM Research that tests unrestrained reasoning about action, change, and planning. ...