First-Order In-Context Shapley: Scalable Data Auditing for LLM Alignment and Evaluation

arXiv:2607.22766 · cs.LG, cs.AI · Submitted 2026-07-24 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-07-24

Updated: 2026-10-08

Terminology

• Alignment — 4× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes

Sources

• SemDeDup: Data-efficient learning at web-scale through semantic deduplication
• Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
• M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation
• AlpaGasus: Training A Better Alpaca with Fewer Data
• Textbooks Are All You Need
• Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms
• WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles
• Shapley-based Data Valuation for LLM Alignment via Sequential Preference Optimization
• Gemini: A Family of Highly Capable Multimodal Models
• Gemma 3 Technical Report
• Qwen3.5-Omni Technical Report
• Fair Document Valuation in LLM Summaries via Shapley Values
• Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

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