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cs.CL2025
Assessing LLMs for Serendipity Discovery in Knowledge Graphs: A Case for Drug Repurposing
Mengying Wang, Chenhui Ma, Ao Jiao +6
Large Language Models (LLMs) have greatly advanced knowledge graph question answering (KGQA), yet existing systems are typically optimized for returning highly relevant but predict…
cs.RO2025★ 1 cited
NEBULA: Do We Evaluate Vision-Language-Action Agents Correctly?
Jierui Peng, Yanyan Zhang, Yicheng Duan +3
The evaluation of Vision-Language-Action (VLA) agents is hindered by the coarse, end-task success metric that fails to provide precise skill diagnosis or measure robustness to real…
cs.CL2025
ERC-SVD: Error-Controlled SVD for Large Language Model Compression
Haolei Bai, Siyong Jian, Tuo Liang +2
Large language models (LLMs) have demonstrated impressive capabilities in a wide range of downstream natural language processing tasks. Nevertheless, their considerable sizes and m…