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Neural-Free ARC Solver FairlySymbolic Achieves High Benchmark Accuracy

By PulseAugur Editorial · [1 sources] ·

A new AI solver named FairlySymbolic has been developed that does not rely on neural networks or extensive pre-training. This system co-evolves a parser, a rule-based program, and a projector for each task it addresses. FairlySymbolic demonstrates high accuracy on several ARC benchmarks, including 99.4% on ConceptARC and 54.4% on ARGA-160, though it faces challenges with ARC-AGI-2. AI

IMPACT Offers an alternative to LLMs for specific reasoning tasks, potentially reducing computational requirements.

RANK_REASON The cluster describes a new AI solver that is not a frontier model release, but rather a novel approach to a specific AI problem (ARC solving) presented in a paper. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Mastodon — sigmoid.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Neural-Free ARC Solver FairlySymbolic Achieves High Benchmark Accuracy

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The cluster describes a new AI solver that is not a frontier model release, but rather a novel approach to a specific AI problem (ARC solving) presented in a paper. [lever_c_demoted from research: …
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COVERAGE [1]

  1. Mastodon — sigmoid.social TIER_1 English(EN) · squillero ·

    Stop misusing LLMs and meet FairlySymbolic, a neural-free # ARC solver. For each task it co-evolves: 🔍 A parser that decides what an “object” is (and the DSL) 🛠

    Stop misusing LLMs and meet FairlySymbolic, a neural-free # ARC solver. For each task it co-evolves: 🔍 A parser that decides what an “object” is (and the DSL) 🛠️ A program of rules in that DSL 📽️ A projector to draw the output No pretraining, no GPUs, no black box: ✅ 99.4% Concep…

    LINKS arxiv.org/…/2611.13831

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