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cs.CL2026
Target-Aware Calibration Data Selection for Preserving Uncertainty in Quantized Language Models
Zhen Yang, Sizai Hou, Kaiwen Zheng +4
Quantization is widely used to deploy large language models, but its effect on uncertainty behavior, such as confidence, margins, and abstention, is rarely treated as a primary obj…
cs.AI2026
PyraMathBench: Evaluating and Improving Mathematical Capability in Large Language Models
Zetian Ouyang, Linlin Wang, Gerard de Melo +1
Despite the pivotal role of numerical reasoning as the cornerstone of mathematical capabilities in large language models (LLMs) across applications, few benchmarks evaluate LLMs by…
cs.CL2026
Disentangling Language Roles in Multilingual LLM Task Execution
Qishi Zhan, Minxuan Hu, Seoyeon Jang +7
Multilingual LLMs are increasingly used when instruction, source content, and required response languages do not coincide. Existing benchmarks have expanded multilingual instructio…