Attribution Bias in Large Language Models

arXiv:2604.05224 · cs.AI · Submitted 2026-04-06 · Read on arXiv

cs.AI

Submitted: 2026-04-06

Updated: 2026-09-24

Terminology

• Accuracy — 57× in this paper · explained in 1 episode
• Benchmark — 14× in this paper · explained in 2 episodes
• RAG — 13× in this paper · explained in 3 episodes
• Perplexity — 7× in this paper · explained in 3 episodes
• Adam — 5× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Pruning — 3× in this paper · explained in 4 episodes
• Accountability — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Who Gets Cited? Gender- and Majority-Bias in LLM-Driven Reference Selection
• Kimi K2.5: Visual Agentic Intelligence
• LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions
• StereoSet: Measuring stereotypical bias in pretrained language models
• GPT-4o System Card
• BBQ: A Hand-Built Bias Benchmark for Question Answering
• CiteME: Can Language Models Accurately Cite Scientific Claims?
• Measuring Attribution in Natural Language Generation Models
• Large Language Models for Education: A Survey and Outlook

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