Stop benchmarking in the lab: Inclusion Arena shows how LLMs perform in production

Stop benchmarking in the lab: Inclusion Arena shows how LLMs perform in production

Benchmark testing models are increasingly important for enterprises to assess performance aligned with their needs. However, many existing benchmarks rely on static datasets or fixed testing environments, which may not accurately reflect real-world applications. Researchers from Inclusion AI, affiliated with Alibaba’s Ant Group, have introduced a new model leaderboard called Inclusion Arena. This initiative aims

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Viral TikToks documenting sorority recruitment see millions of views, intense backlash 

Viral TikToks documenting sorority recruitment see millions of views, intense backlash 

Recent TikTok videos documenting college freshmen’s experiences during sorority recruitment have gained millions of views. However, these viral clips have drawn significant backlash for portraying the recruitment process as overly competitive and superficial. The trend reflects how social media has influenced traditional recruitment processes within sororities, raising concerns about the authenticity of these depictions. NBC

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Netanyahu accuses Australian PM Albanese of 'betraying' Israel

Netanyahu accuses Australian PM Albanese of ‘betraying’ Israel

Diplomatic tensions have escalated between Israel and Australia, as Israeli Prime Minister Benjamin Netanyahu accused Australian Prime Minister Anthony Albanese of “betraying Israel” and “abandoning” the Australian Jewish community. This exchange follows Australia’s recent decision to recognize a Palestinian state, joining the UK, France, and Canada in such a stance. Netanyahu, in a statement on

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LLMs generate 'fluent nonsense' when reasoning outside their training zone

LLMs generate ‘fluent nonsense’ when reasoning outside their training zone

A recent study from researchers at Arizona State University (ASU) raises questions about the effectiveness of Chain-of-Thought (CoT) reasoning in Large Language Models (LLMs). The research provides a novel perspective on where CoT may fail, suggesting it could be more accurately described as “structured pattern matching” influenced by training data rather than genuine reasoning. This

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