:PROPERTIES:
:CREATED:  [2026-05-27 Wed]
:ID:       ee8f3b2a-4c7d-4e1b-9b0a-6d8f2e3c1a5b
:END:
#+title: Neurosymbolic AI
#+filetags: :resources:neurosymbolic:papers:survey:

Local library of recent neurosymbolic AI papers, updated monthly from arXiv. Papers are downloaded in PDF format and cataloged below.

See also the companion note [[id:be9bccc7-5adf-4d0d-8ee4-8855892189bf][Neurosymbolic Loop Architectures]] for a design taxonomy that positions these papers relative to Passepartout.

* 2026 Papers

| arXiv ID | Title | Date | Keywords | File |
|----------|-------|------|----------|------|
| 2605.22885 | ImProver 2: Iteratively Self-Improving LMs for Neurosymbolic Proof Optimization | May 2026 | LLM, theorem proving, proof optimization, self-improvement | [[file:papers/2605.22885.pdf]] |
| 2605.22874 | NeuroNL2LTL: Neurosymbolic Framework for NL Translation of LTL | May 2026 | NL translation, LTL, formal logic | [[file:papers/2605.22874.pdf]] |
| 2605.10327 | SCALAR: Symbolic Conjecture and LLM-Assisted Reasoning | May 2026 | Conjecture generation, theorem proving, LLM | [[file:papers/2605.10327.pdf]] |
| 2605.10279 | DeepLog: Neurosymbolic Framework Unifying Logic and Deep Learning in PyTorch | May 2026 | Logic, deep learning, PyTorch, neurosymbolic | [[file:papers/2605.10279.pdf]] |
| 2605.08011 | LLM + Formal Logic Integration for Neurosymbolic Reasoning | May 2026 | Survey, formal logic, LLM, neurosymbolic reasoning | [[file:papers/2605.08011.pdf]] |
| 2605.01430 | Measuring Understanding in Artificial Cognitive Systems | May 2026 | Verification, cognitive systems, neurosymbolic | [[file:papers/2605.01430.pdf]] |
| 2605.26169 | ESBMC: Survey of Formal Software Verification | May 2026 | Formal verification, bounded model checking, SMT | [[file:papers/2605.26169.pdf]] |
| 2604.05427 | LLM Verification Gates for Robot Task Planning | Apr 2026 | Gates, verification, robotics, LLM | [[file:papers/2604.05427.pdf]] |
| 2604.04177 | Formal Logic in LLM Fact-Checking Pipelines | Apr 2026 | Fact-checking, logic, verification | [[file:papers/2604.04177.pdf]] |
| 2604.23377 | The Alignment Problem in Neurosymbolic Systems | Apr 2026 | Alignment, concept-label correspondence, neurosymbolic | [[file:papers/2604.23377.pdf]] |
| 2603.14628 | LLM Neurosymbolic Reasoning in Theorem Proving | Mar 2026 | Theorem proving, LLM, neurosymbolic | [[file:papers/2603.14628.pdf]] |
| 2603.04019 | Fluid Logic: Neurosymbolic Modal Reasoning | Mar 2026 | Modal logic, neurosymbolic, reasoning | [[file:papers/2603.04019.pdf]] |

* Related Neuromorphic Architecture Papers

| arXiv ID | Title | Date | Keywords | File |
|----------|-------|------|----------|------|
| 2604.04605 | Benchmarking Neuromorphic AI Processors | Apr 2026 | Neuromorphic, benchmarking, hardware | (not yet downloaded) |
| 2604.21924 | Spiking Neural Network Optimization | Apr 2026 | SNN, optimization, neuromorphic | (not yet downloaded) |

* How the Monthly Update Works

A monthly cron job (set on 2026-05-27) runs on the 1st of each month:

1. Queries arXiv API for new papers with keywords: neurosymbolic, neural+symbolic+reasoning, LLM+verification, neural+theorem+proving
2. Filters by the current month's submissions
3. Downloads PDFs of relevant papers
4. Updates this index
5. Commits and pushes the brain repo
