3 papers
cs.LG2026
Looped World Models
Hongyuan Adam Lu, Z. L. Victor Wei, Qun Zhang +28
Current world models face a fundamental tension: faithful long-horizon simulation demands deep computation, but deeper models are expensive to deploy and prone to compounding error…
cs.CL2025
FEANEL: A Benchmark for Fine-Grained Error Analysis in K-12 English Writing
Jingheng Ye, Shen Wang, Jiaqi Chen +9
Large Language Models (LLMs) have transformed artificial intelligence, offering profound opportunities for educational applications. However, their ability to provide fine-grained…
cs.CL2024
Exploring the Implicit Semantic Ability of Multimodal Large Language Models: A Pilot Study on Entity Set Expansion
Hebin Wang, Yangning Li, Yinghui Li +3
The rapid development of multimodal large language models (MLLMs) has brought significant improvements to a wide range of tasks in real-world applications. However, LLMs still exhi…