Reasoning Core: A Scalable RL Environment for LLM Symbolic Reasoning
We introduce Reasoning Core, a new scalable environment for Reinforcement
Learning with Verifiable Rewards (RLVR), designed to advance foundational
symbolic reasoning in Large Language Models (LLMs). Unlike existing benchmarks
that focus on games or isolated puzzles, Reasoning Core procedurally generates
problems across core formal domains, including PDDL planning, first-order
logic, context-free grammar parsing, causal reasoning, and system equation
solving. The environment is built on key design principles of high-generality
problem distributions, verification via external tools, and continuous
difficulty control, which together provide a virtually infinite supply of novel
training instances. Initial zero-shot evaluations with frontier LLMs confirm
the difficulty of Reasoning Core's tasks, positioning it as a promising
resource to improve the reasoning capabilities of future models.
68d24adf1ca7156988a8ee94
Valentin Lacombe
68d24adf1ca7156988a8ee95
Valentin Quesnel
68d24adf1ca7156988a8ee96
Damien Sileo
Reasoning Core: A Scalable RL Environment for LLM Symbolic Reasoning
We introduce Reasoning Core, a new scalable environment for Reinforcement
Learning with Verifiable Rewards (RLVR), designed to advance foundational
symbolic reasoning in Large Language Models (LLMs). Unlike existing benchmarks
that focus on games or isolated puzzles, Reasoning Core procedurally generates
problems across core formal domains, including PDDL planning, first-order
logic, context-free grammar parsing, causal reasoning, and system equation
solving. The environment is built on key design principles of high-generality
problem distributions, verification via external tools, and continuous
difficulty control, which together provide a virtually infinite supply of novel
training instances. Initial zero-shot evaluations with frontier LLMs confirm
the difficulty of Reasoning Core's tasks, positioning it as a promising
resource to improve the reasoning capabilities of future models.
Reasoning Core is a scalable RLVR environment that generates diverse symbolic reasoning problems to enhance LLM capabilities.
Reinforcement Learning with Verifiable Rewards (RLVR) Large Language Models (LLMs) PDDL planning first-order logic context-free grammar parsing causal reasoning system equation solving high-generality problem distributions verification via external tools continuous difficulty control