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20242026
most citedBridging Dual Knowledge Graphs for Multi-Hop Question Answering in Construction Safety

7 citations · 7 across the 2 of their papers we have counts for

collaborators

7 papers

cs.AI20267 cited

Bridging Dual Knowledge Graphs for Multi-Hop Question Answering in Construction Safety

Yuxin Zhang, Xi Wang, Mo Hu +1

Information retrieval and question answering from safety regulations are essential for automated construction compliance checking but are hindered by the linguistic and structural…

cs.CL2026

PORTool: Importance-Aware Policy Optimization with Rewarded Tree for Multi-Tool-Integrated Reasoning

Feijie Wu, Weiwu Zhu, Yuxiang Zhang +5

Multi-tool-integrated reasoning enables LLM-empowered tool-use agents to solve complex tasks by interleaving natural-language reasoning with calls to external tools. However, train…

cs.LG2025

TokenSqueeze: Performance-Preserving Compression for Reasoning LLMs

Yuxiang Zhang, Zhengxu Yu, Weihang Pan +5

Emerging reasoning LLMs such as OpenAI-o1 and DeepSeek-R1 have achieved strong performance on complex reasoning tasks by generating long chain-of-thought (CoT) traces. However, the…

cs.CV2025

R2GenKG: Hierarchical Multi-modal Knowledge Graph for LLM-based Radiology Report Generation

Futian Wang, Yuhan Qiao, Xiao Wang +3

X-ray medical report generation is one of the important applications of artificial intelligence in healthcare. With the support of large foundation models, the quality of medical r…

cs.LG2025

A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models

Zihao Lin, Samyadeep Basu, Mohammad Beigi +18

The rise of foundation models has transformed machine learning research, prompting efforts to uncover their inner workings and develop more efficient and reliable applications for…

cs.CL2024

MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series

Ge Zhang, Scott Qu, Jiaheng Liu +42

Large Language Models (LLMs) have made great strides in recent years to achieve unprecedented performance across different tasks. However, due to commercial interest, the most comp…