3 papers
cs.AI2026
Do MLLMs Really Understand Space? A Mathematical Reasoning Evaluation
Shuo Lu, Jianjie Cheng, Yinuo Xu +16
Multimodal large language models (MLLMs) have achieved strong performance on perception-oriented tasks, yet their ability to perform mathematical spatial reasoning, defined as the…
cs.CL2025
SagaScale: A Realistic, Scalable, and High-Quality Long-Context Benchmark Built from Full-Length Novels
Guancheng Du, Yong Hu, Wenqing Wang +2
Large Language Models (LLMs) have shown significant progress, but understanding long and complex documents remains challenging. Many long-context benchmarks have been proposed, but…
cs.LG2025
Encouraging Good Processes Without the Need for Good Answers: Reinforcement Learning for LLM Agent Planning
Zhiwei Li, Yong Hu, Wenqing Wang
The functionality of Large Language Model (LLM) agents is primarily determined by two capabilities: action planning and answer summarization. The former, action planning, is the co…