Papers with in-line citations

2 papers
Learning Fine-Grained Grounded Citations for Attributed Large Language Models (2024.findings-acl)

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Challenge: despite impressive performance, large language models still struggle with hallucinations . current approaches suffer from suboptimal citation quality due to reliance on in-context learning .
Approach: They propose a framework that teaches large language models to generate fine-grained citations.
Outcome: The proposed framework outperforms all baselines on the ALCE benchmark and achieves an average improvement of 14.21% in citation quality.
Media Source Matters More Than Content: Unveiling Political Bias in LLM-Generated Citations (2025.emnlp-main)

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Challenge: generative search engines rely on in-line citations as the key gateway to original webpages . a recent study shows that LLMs tend to cite left-leaning sources at higher rates compared to traditional retrieval systems .
Approach: They construct a dataset of news articles labeled with left- or right-leaning stances . they find that LLMs tend to cite left-leansing sources at higher rates than traditional retrieval systems .
Outcome: The proposed dataset shows that LLMs tend to cite left-leaning sources at higher rates than traditional retrieval systems.

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