2 citations · 7 across the 7 of their papers we have counts for
5 papers · 1 filter
Light-IF: Endowing LLMs with Generalizable Reasoning via Preview and Self-Checking for Complex Instruction Following
Chenyang Wang, Liang Wen, Shousheng Jia +2
While advancements in the reasoning abilities of LLMs have significantly enhanced their performance in solving mathematical problems, coding tasks, and general puzzles, their effec…
GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning
Liangyu Xu, Yingxiu Zhao, Jingyun Wang +9
Geometry problem-solving (GPS), a challenging task requiring both visual comprehension and symbolic reasoning, effectively measures the reasoning capabilities of multimodal large l…
SuperCLUE-Fin: Graded Fine-Grained Analysis of Chinese LLMs on Diverse Financial Tasks and Applications
Liang Xu, Lei Zhu, Yaotong Wu +1
The SuperCLUE-Fin (SC-Fin) benchmark is a pioneering evaluation framework tailored for Chinese-native financial large language models (FLMs). It assesses FLMs across six financial…
SuperCLUE-Math6: Graded Multi-Step Math Reasoning Benchmark for LLMs in Chinese
Liang Xu, Hang Xue, Lei Zhu +1
We introduce SuperCLUE-Math6(SC-Math6), a new benchmark dataset to evaluate the mathematical reasoning abilities of Chinese language models. SC-Math6 is designed as an upgraded Chi…
SC-Safety: A Multi-round Open-ended Question Adversarial Safety Benchmark for Large Language Models in Chinese
Liang Xu, Kangkang Zhao, Lei Zhu +1
Large language models (LLMs), like ChatGPT and GPT-4, have demonstrated remarkable abilities in natural language understanding and generation. However, alongside their positive imp…