Apple’s New LLM Benchmark, GSM-Symbolic
Welcome to this exploration of LLM reasoning skills, the place we’ll sort out a giant query: can fashions like GPT, Llama, Mistral, and Gemma really purpose, or are they only intelligent sample matchers? With every new launch, we’re seeing these fashions hitting increased benchmark scores, typically giving the impression they’re on the verge of real problem-solving skills. However a brand new research from Apple, “GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Giant Language Fashions”, presents a actuality verify — and its findings may shift how we take into consideration these capabilities.
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As an LLM Engineer for nearly two years, I’m gonna share my perspective on this subject, together with why it’s important for LLMs to maneuver past memorized patterns and ship actual reasoning. We’ll additionally break down the important thing findings from the GSM-Symbolic research, which reveals the gaps in mathematical reasoning these fashions nonetheless face. Lastly, I’ll replicate on what this implies for making use of LLMs in real-world settings, the place true reasoning — not simply an impressive-looking response — is what we actually want.