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First-Order In-Context Shapley: Scalable Data Auditing for LLM Alignment and Evaluation
Post-training alignment of Large Language Models is increasingly bottlenecked by data quality: preference and instruction-tuning corpora accumulate label noise, safety inversions, and inter-annotator contradictions that deduplication misses and full-corpus LLM judging cannot afford. While Data Shapl
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