Papers with reasoning of large language models
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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Ziqi Zhao, Zhaochun Ren, Jiahong Zou, Liu Yang, Zhiwei Xu, Xuri Ge, Zhumin Chen, Xinyu Ma, Daiting Shi, Shuaiqiang Wang, Dawei Yin, Xin Xin
| 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. |