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The Mirage of Emergent Capabilities in LLMs: A Case Study in Data Contamination

This post dissects the phenomenon of 'emergent capabilities' in large language models, arguing that many observed phenomena are artifacts of training data contamination rather than genuine algorithmic breakthroughs. It will explore the technical mechanisms by which contamination occurs, present evidence from community benchmarks and academic critiques, and discuss the implications for AI safety and future research.
9 min read
The Mirage of Emergent Capabilities in LLMs: A Case Study in Data Contamination