5 citations · 8 across the 17 of their papers we have counts for
6 papers · 1 filter
OpenRFT: Adapting Reasoning Foundation Model for Domain-specific Tasks with Reinforcement Fine-Tuning
Yuxiang Zhang, Yuqi Yang, Jiangming Shu +3
OpenAI's recent introduction of Reinforcement Fine-Tuning (RFT) showcases the potential of reasoning foundation model and offers a new paradigm for fine-tuning beyond simple patter…
Enhancing Cluster Resilience: LLM-agent Based Autonomous Intelligent Cluster Diagnosis System and Evaluation Framework
Honghao Shi, Longkai Cheng, Wenli Wu +7
Recent advancements in Large Language Models (LLMs) and related technologies such as Retrieval-Augmented Generation (RAG) and Diagram of Thought (DoT) have enabled the creation of…
Don't Command, Cultivate: An Exploratory Study of System-2 Alignment
Yuhang Wang, Yuxiang Zhang, Yanxu Zhu +2
The o1 system card identifies the o1 models as the most robust within OpenAI, with their defining characteristic being the progression from rapid, intuitive thinking to slower, mor…
KG-FPQ: Evaluating Factuality Hallucination in LLMs with Knowledge Graph-based False Premise Questions
Yanxu Zhu, Jinlin Xiao, Yuhang Wang +1
Recent studies have demonstrated that large language models (LLMs) are susceptible to being misled by false premise questions (FPQs), leading to errors in factual knowledge, know a…
Development of a Reliable and Accessible Caregiving Language Model (CaLM)
Bambang Parmanto, Bayu Aryoyudanta, Wilbert Soekinto +5
Unlike professional caregivers, family caregivers often assume this role without formal preparation or training. Because of this, there is an urgent need to enhance the capacity of…
Improving Weak-to-Strong Generalization with Scalable Oversight and Ensemble Learning
Jitao Sang, Yuhang Wang, Jing Zhang +5
This paper presents a follow-up study to OpenAI's recent superalignment work on Weak-to-Strong Generalization (W2SG). Superalignment focuses on ensuring that high-level AI systems…