Papers with reasoning of large language models

2 papers
Extending First-Order Logic for Factual Reasoning over Knowledge Graphs (2026.acl-long)

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Challenge: Existing methods for factual reasoning over knowledge graphs lack support for multiple quantifiers and connectives.
Approach: They propose an extended FOL -structure over knowledge graphs that incorporates comparison predicates and counting quantifiers.
Outcome: The proposed method achieves state-of-the-art on Fact-FOLX-KG, while previous methods experience performance drop on claims requiring comparison and counting.
Reinforced Efficient Reasoning via Semantically Diverse Exploration (2026.acl-long)

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Challenge: Existing methods for reinforcement learning with verifiable rewards suffer from limited exploration diversity and inefficient reasoning.
Approach: They propose a method that rewards concise and correct reasoning while penalizing unnecessarily long reasoning chains.
Outcome: Extensive experiments on Qwen and Llama models validate the effectiveness and efficiency of ROSE.

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