4 papers
Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow
Yangyang Zhong, Yanmei Gu, Zhengqing Zang +14
Masked Diffusion Language Models (MDLMs) promise parallel token generation and arbitrary-order decoding, yet it remains unclear to what extent current models truly realize these ca…
FinEval-KR: A Financial Domain Evaluation Framework for Large Language Models' Knowledge and Reasoning
Shaoyu Dou, Yutian Shen, Mofan Chen +9
Large Language Models (LLMs) demonstrate significant potential but face challenges in complex financial reasoning tasks requiring both domain knowledge and sophisticated reasoning.…
Mitigating Cross-Modal Distraction and Ensuring Geometric Feasibility via Affordance-Guided and Self-Consistent MLLMs for Task Planning in Instruction-Following Manipulation
Yu-Hong Shen, Chuan-Yu Wu, Yi-Ru Yang +2
We investigate the use of Multimodal Large Language Models (MLLMs) with in-context learning for closed-loop task planning in instruction-following manipulation. We identify four es…
Evaluation of LLMs for mathematical problem solving
Ruonan Wang, Runxi Wang, Yunwen Shen +3
Large Language Models (LLMs) have shown impressive performance on a range of educational tasks, but are still understudied for their potential to solve mathematical problems. In th…