arXiv:2606.23238v2 Announce Type: replace Abstract: Logical reasoning is essential for reliable AI, yet existing benchmarks are largely first-order-logic-centric, focusing on object-level deduction over fixed predicates. This misses many realistic scenarios where models must reason over rules, predicates, functions, constraints, and decision procedures themselves. We introduce HOLMES (Higher-Order Logic Meets real-world Explainable Symbolic reasoning), the first real-world benchmark for higher-order symbolic reasoning in LLMs, containing 1379 instances. Built on higher-order logic, HOLMES pair
The continuous evolution of LLMs necessitates robust evaluation methods for increasingly complex reasoning capabilities, pushing the frontier beyond first-order logic.
Higher-order logical reasoning is crucial for AI reliability and enables LLMs to tackle more sophisticated, real-world problems that require understanding rules and constraints.
The introduction of HOLMES provides a new benchmark, shifting the focus of LLM development and evaluation towards more advanced symbolic reasoning, impacting future AI capabilities.
- · AI research institutions
- · LLM developers
- · Developers of AI safety tools
- · LLMs with poor higher-order reasoning
- · AI applications requiring complex logic without robust foundational models
This benchmark will drive significant improvements in LLM capacity for higher-order logical reasoning.
Improved logical reasoning in LLMs will unlock new applications in fields requiring complex decision-making and rule-based systems.
Enhanced AI reasoning capabilities could accelerate automation in white-collar sectors and potentially lead to more reliable autonomous agents.
This signal links to a primary source. Continuum Brief monitors and indexes it as part of the live intelligence stream — we do not republish source content.
Read at arXiv cs.AI