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20232026
most citedCoupled Mamba: Enhanced Multi-modal Fusion with Coupled State Space Model

5 citations · 16 across the 34 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

Semiotic logical hexagon theory for LLM logical reasoning

Yunyao Zhang, Xinglang Zhang, Zeliang Chen +2

Large language models (LLMs) have become powerful tools for language understanding and logical reasoning. However, they still make mistakes when a problem requires both understandi…

cs.AI2026

HotComment: A Benchmark for Evaluating Popularity of Online Comments

Yafeng Wu, Yunyao Zhang, Liliang Ye +4

Online comments play a crucial role in shaping public sentiment and opinion dynamics on social media. However, evaluating their popularity remains challenging, not only because it…

cs.AI2026★ 1 cited

Logical Phase Transitions: Understanding Collapse in LLM Logical Reasoning

Xinglang Zhang, Yunyao Zhang, ZeLiang Chen +3

Symbolic logical reasoning is a critical yet underexplored capability of large language models (LLMs), providing reliable and verifiable decision-making in high-stakes domains such…

cs.AI2025★ 1 cited

Semantic-Aware Logical Reasoning via a Semiotic Framework

Yunyao Zhang, Xinglang Zhang, Junxi Sheng +5

Logical reasoning is a fundamental capability of large language models. However, existing studies often overlook the interaction between logical complexity and semantic complexity,…

cs.AI2024★ 5 cited

Coupled Mamba: Enhanced Multi-modal Fusion with Coupled State Space Model

Wenbing Li, Hang Zhou, Junqing Yu +2

The essence of multi-modal fusion lies in exploiting the complementary information inherent in diverse modalities. However, prevalent fusion methods rely on traditional neural arch…