September 25, 2025Open Access

Joint Enhancement of Relational Reasoning for Long-Context LLMs

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Novel framework improves accuracy and transparency in long-context LLMs using graph-based techniques.

The framework JERR significantly enhances long-context comprehension in llms, improving accuracy and interpretability.
Experimental results indicate that JERR outperformed all baselines on ROUGE and F1 metrics, demonstrating effectiveness.
Key components of JERR include synopsis extraction, directed acyclic graph construction, and relational reasoning.
The integrated monte carlo tree search method ensures logical consistency and clarity in complex reasoning tasks.

Chen et al. (2025) studied this question.

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