1 citations · 1 across the 3 of their papers we have counts for
6 papers
Semi-Supervised Conformal Prediction With Unlabeled Nonconformity Score
Xuanning Zhou, Zihao Shi, Hao Zeng +3
Conformal prediction (CP) is a powerful framework for uncertainty quantification, generating prediction sets with coverage guarantees. Split conformal prediction relies on labeled…
Knowledge Fusion of Large Language Models Via Modular SkillPacks
Guodong Du, Zhuo Li, Xuanning Zhou +9
Cross-capability transfer is a key challenge in large language model (LLM) research, with applications in multi-task integration, model compression, and continual learning. Recent…
TorchCP: A Python Library for Conformal Prediction
Jianguo Huang, Jianqing Song, Xuanning Zhou +2
Conformal prediction (CP) is a powerful statistical framework that generates prediction intervals or sets with guaranteed coverage probability. While CP algorithms have evolved bey…
TCC-Bench: Benchmarking the Traditional Chinese Culture Understanding Capabilities of MLLMs
Pengju Xu, Yan Wang, Shuyuan Zhang +8
Recent progress in Multimodal Large Language Models (MLLMs) have significantly enhanced the ability of artificial intelligence systems to understand and generate multimodal content…
WideSearch: Benchmarking Agentic Broad Info-Seeking
Ryan Wong, Jiawei Wang, Junjie Zhao +10
From professional research to everyday planning, many tasks are bottlenecked by wide-scale information seeking, which is more repetitive than cognitively complex. With the rapid de…
Response-Level Rewards Are All You Need for Online Reinforcement Learning in LLMs: A Mathematical Perspective
Shenghua He, Tian Xia, Xuan Zhou +1
We study a common challenge in reinforcement learning for large language models (LLMs): the Zero-Reward Assumption, where non-terminal actions (i.e., intermediate token generations…