3 papers
cs.HC2026
Why Machines Misread Pedagogical Quality: Human-Machine Alignment in LLM-Based Pretest Question Evaluation
Pei-Yu Tseng, Mahir Akgun, Peng Liu
Designing effective pretest questions is challenging at scale: high-quality questions require careful calibration of openness, cognitive depth, and alignment with learning objectiv…
cs.CL2023
Just Ask One More Time! Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios
Lei Lin, Jiayi Fu, Pengli Liu +7
Although chain-of-thought (CoT) prompting combined with language models has achieved encouraging results on complex reasoning tasks, the naive greedy decoding used in CoT prompting…
cs.CL2023
KwaiYiiMath: Technical Report
Jiayi Fu, Lei Lin, Xiaoyang Gao +18
Recent advancements in large language models (LLMs) have demonstrated remarkable abilities in handling a variety of natural language processing (NLP) downstream tasks, even on math…