3 papers
cs.LG2026
Understanding Curriculum Learning in Large Language Models via Cross-Difficulty Optimization Dynamics
Zhikai Ding, Ziyi Ye
Curriculum learning has been widely adopted in the post-training of large language models by organizing training data from easy to hard. However, its effectiveness varies substanti…
cs.CL2026
Evaluating and Calibrating LLM Confidence on Questions with Multiple Correct Answers
Yuhan Wang, Shiyu Ni, Zhikai Ding +3
Confidence calibration is essential for making large language models (LLMs) reliable, yet existing training-free methods have been primarily studied under single-answer question an…
cs.CL2025
Do LVLMs Know What They Know? A Systematic Study of Knowledge Boundary Perception in LVLMs
Zhikai Ding, Shiyu Ni, Keping Bi
Large vision-language models (LVLMs) demonstrate strong visual question answering (VQA) capabilities but are shown to hallucinate. A reliable model should perceive its knowledge bo…