Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.
On SWE-Bench Verified, the model achieved a score of 70.6%. This performance is notably competitive when placed alongside significantly larger models; it outpaces DeepSeek-V3.2, which scores 70.2%, ...
New benchmark shows top LLMs achieve only 29% pass rate on OpenTelemetry instrumentation, exposing the gap between ...
The suite was initially authored in Crystal and then translated to other languages using AI-assisted tools (DeepSeek). This approach ensures functional and algorithmic parity, though the resulting ...
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Large language models (LLMs) have driven rapid progress in natural language processing (NLP), including AI translation. Yet most benchmarks used to evaluate these systems remain heavily ...
Newer languages might soak up all the glory, but these die-hard languages have their place. Here are eight languages developers still use daily, and what they’re good for. The computer revolution has ...
New York, NY, Dec. 09, 2025 (GLOBE NEWSWIRE) -- Sword Health, the world’s leading AI Health company, today unveiled MindEval, the industry’s first benchmark designed to evaluate how large language ...
The R language for statistical computing has creeped back into the top 10 in Tiobe’s monthly index of programming language popularity. “Programming language R is known for fitting statisticians and ...
This study introduces MathEval, a comprehensive benchmarking framework designed to systematically evaluate the mathematical reasoning capabilities of large language models (LLMs). Addressing key ...
Over the last decade, artificial intelligence (AI) has been largely built around large language models (LLMs). These systems are based on a language and guess words in a chain in the form of tokens.
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