Q-REAL: Towards Naturalness and Distortion Evaluation for AI-Generated Content
Shushi Wang · Zicheng Zhang · Chunyi Li · Wei Wang · Liya Ma · Xiaoyu Li · Fengjiao Chen · Xuezhi Cao · Guangtao Zhai · Xiaohong Liu
首次获取该候选人的完整档案及 StartLux 评估共 20 积分;每位用户单独解锁,之后查看免费。主动刷新 20 积分。
实时查找电子邮箱,费用不超过20积分;未找到邮箱不扣费。
Shushi Wang · Zicheng Zhang · Chunyi Li · Wei Wang · Liya Ma · Xiaoyu Li · Fengjiao Chen · Xuezhi Cao · Guangtao Zhai · Xiaohong Liu
Dujun Nie · Fengjiao Chen · Jun Kuang · Qi Lv · Xiaoyu Li · Xuezhi Cao
Junlin Liu · Shengnan An · Shuang Zhou · Dan Ma · Yehao Lin · Xinxuan Lv · Xuanlin Wang · Xiaoyu Li · Ziwen Wang · Xuezhi Cao · Xunliang Cai
We present AMO-Bench , an A dvanced M athematical reasoning benchmark with O lympiad level or even higher difficulty, comprising 50 human-crafted problems. Existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large language...
Jiaming Wang · Zhe Tang · Zehao Jin · Hefei Chen · Yilin Jin · Peng Ding · Xiaoyu Li · Xuezhi Cao
As large language models (LLMs) are widely deployed as domain-specific agents, many benchmarks have been proposed to evaluate their ability to follow instructions and make decisions in real-world scenarios. However, business scenarios often involve complex standard operating procedures (SOPs), an...
Jiaming Wang · Yunke Zhao · Peng Ding · Jun Kuang · Yibin Shen · Zhe Tang · Yilin Jin · ZongYu Wang · Xiaoyu Li · Xuezhi Cao
The capability to precisely adhere to instructions is a cornerstone for Large Language Models (LLMs) to function as dependable agents in real-world scenarios. However, confronted with complex prompts, LLMs frequently encounter difficulties in fulfilling all specified requirements within a single...