ARCANA: A Benchmark for Abstraction and Analogical Reasoning
In this work, we introduce an analogical reasoning benchmark called Abstraction and Reasoning Corpus of ANAlogy (ARCANA).
ProofPaper ↗
Key points
- Analogical reasoning is widely considered a fundamental component of human intelligence.
- Few benchmarks are designed to explicitly test far analogical reasoning - reasoning between domains that are superficially dissimilar yet share deep relational or structural similarities.
- The tasks of ARCANA require performing far analogical mappings from real-world objects or physical phenomena to abstract grid-based transformations, different from the well-known ARC-AGI benchmark which primarily emphasized innate human priors.
- To address this gap, we propose ConceptSIR, a reasoning framework based on concept slippage, introspection, and reflection.
Sources (1)
- [1]ARCANA: A Benchmark for Abstraction and Analogical ReasoningarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 21, 06:18 AM
In this work, we introduce an analogical reasoning benchmark called Abstraction and Reasoning Corpus of ANAlogy (ARCANA).
Analogical reasoning is widely considered a fundamental component of human intelligence.
Extractive summary: sentences quoted from the sources.
Before this
- Oct 20, 2026BitMTP: When Multi-Token Prediction Meets Low-Bit Large Language Models
- Oct 20, 2026MAS-Guard: Unified Guardrails from Individual Agents to Multi-Agent LLM Systems
- Oct 20, 2026SliMOO: Interpretable Multi-Objective Evolutionary Search for LLM Depth Pruning
- Oct 20, 2026Tracing Recurrent and Emergent Hallucination Patterns in Decomposed Text-to-SQL Generation
- Oct 19, 2026Introducing Clairic, a new System One class of extraction models
- Oct 19, 2026MoveBench: A Rubric-Based Benchmark for Evaluating Large Language Models in Sports and Health Coaching