Tenth International Workshop on Symbolic-Neural Learning (SNL2026)

Symbolic–neural learning explores how continuous learning systems and discrete structure can be integrated to enable more reliable, interpretable, and generalizable intelligence. At its core, this area brings together gradient-based learning over high-dimensional representations with symbolic abstractions such as language, programs, knowledge graphs, and structured world models.
Recent advances in large-scale foundation models have dramatically expanded the scope of symbolic–neural systems. Modern architectures—ranging from transformers to multimodal models and agentic systems—routinely operate over structured inputs and outputs, including text, code, formal logic, and embodied state representations. At the same time, longstanding challenges remain: how to incorporate compositional structure, enforce constraints, support reasoning and planning, and ground learning in interaction with the real world.

The 2026 SNL Workshop invites contributions at the intersection of learning and structure, broadly construed. Relevant topics include, but are not limited to:

• Language, vision, and multimodal reasoning with structured outputs
• Program synthesis, code generation, and neuro-symbolic reasoning
• Knowledge representation, retrieval, and integration with learned models
• Embodied agents and robotics with language and symbolic interaction
• Planning, decision making, and tool use in learned systems
• Learning with constraints, structure, or formal guarantees
• Interpretability, compositionality, and generalization
• Human–AI interaction involving language and symbolic communication

The workshop, which features invited oral presentations ans contributed poster presentations, aims to bring together researchers from machine learning, natural language processing, robotics, cognitive science, and related fields to explore how structure and learning can be combined to build more capable and trustworthy AI systems.

SNL Website: https://snl2026.ttic.edu

We will have a poster session on the first day of the workshop (June 25, 2026). If you are interested in presenting your work, please submit your poster information using the following Google Form:

https://forms.gle/MxnfDrpLL2FcVLpJ8

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Host or Publisher the Toyota Technological Institute at Chicago