AwarenessBench: Assessing Cognitive Capabilities of Language Models
Xiaojian Li, Rongwu Xu, Tianyun Zhang, Yue Wang, Shuo Chen, Qiner Lyu, Briana Zhang, Peiran Yang, Kyle Xue Chen, Haoyuan Shi, Yu Wang, Wei Xu
摘要
As language models (LMs) exhibit increasingly consciousness-like behaviors, evaluating their cognitive abilities becomes essential. We introduce AwarenessBench, the first comprehensive benchmark for assessing the cognitive abilities of LMs in four dimensions: metacognition, selfawareness, social awareness, and situational awareness, covering 15 cognitive functions and 14,381 samples. Evaluating 18 state-of-the-art LMs, we find that all consistently surpass random baselines, with more advanced models performing better. We further compare LMs with human performance across three demographic groups, where the best-performing model surpasses human averages overall, but most still fall markedly short in metacognition and selfawareness. Finally, we show that awareness is a distinct capability: progress in language modeling or reasoning does not necessarily translate into improved cognition.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
它引用的顶会 Paper7
- Large Language Models as Commonsense Knowledge for Large-Scale Task PlanningZirui Zhao, Wee Sun Lee, David HsuNeurIPS 2023 · 被引用 423 次
- Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?Haoang Chi, He Li, Wenjing Yang, Feng Liu 等NeurIPS 2024 · 被引用 124 次
- PlanGenLLMs: A Modern Survey of LLM Planning CapabilitiesHui Wei, Zihao Zhang, Shenghua He, Tian Xia 等ACL 2025 · 被引用 78 次
- Tell me about yourself: LLMs are aware of their learned behaviorsJan Betley, Xuchan Bao, Martín Soto, Anna Sztyber-Betley 等ICLR 2025 · 被引用 2 次
- How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled BenchmarkMinglai Yang, Ethan Huang, Liang Zhang, Mihai Surdeanu 等EMNLP 2025 · 被引用 2 次
相关 Paper
- ToMBench: Benchmarking Theory of Mind in Large Language ModelsZhuang Chen, Jincenzi Wu, Jinfeng Zhou, Bosi Wen 等ACL 2024 · 被引用 6 次
- LawBench: Benchmarking Legal Knowledge of Large Language ModelsZhiwei Fei, Xiaoyu Shen, Dawei Zhu, Fengzhe Zhou 等EMNLP 2024 · 被引用 59 次
- SafetyBench: Evaluating the Safety of Large Language ModelsZhexin Zhang, Leqi Lei, Lindong Wu, Rui Sun 等ACL 2024
- EvolveBench: A Comprehensive Benchmark for Assessing Temporal Awareness in LLMs on Evolving KnowledgeZhiyuan Zhu, Yusheng Liao, Zhe Chen, Yuhao Wang 等ACL 2025 · 被引用 10 次
- CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science MasteryXiaoshuai Song, Muxi Diao, Guanting Dong, Zhengyang Wang 等ICLR 2025
