11 citations · 15 across the 5 of their papers we have counts for
5 papers
Beyond Direct Answering: Aligning Educational LLMs as Socratic Guides via Heuristic Reinforcement Learning
Xiaokun Wang, Siyu Song, Wentao Liu +1
Large language models (LLMs) deployed in educational settings often behave as direct answerers: they disclose target concepts in the opening turn instead of guiding students throug…
Toward Anthropomorphic Dialogue: A Closed-Loop Framework for Human-Like Chat Generation, Evaluation, and Preference Alignment
Wentao Liu, Siyu Song, Xi Chen +4
Human-like private chat requires more than fluent response generation: a system must preserve persona, relationship, memory, bounded knowledge, medium-specific timing, and a cohere…
Application-Driven Pedagogical Knowledge Optimization of Open-Source LLMs via Reinforcement Learning and Supervised Fine-Tuning
Navan Preet Singh, Xiaokun Wang, Anurag Garikipati +3
We present an innovative multi-stage optimization strategy combining reinforcement learning (RL) and supervised fine-tuning (SFT) to enhance the pedagogical knowledge of large lang…
Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models
Tianwen Wei, Bo Zhu, Liang Zhao +13
In this technical report, we introduce the training methodologies implemented in the development of Skywork-MoE, a high-performance mixture-of-experts (MoE) large language model (L…
Skywork: A More Open Bilingual Foundation Model
Tianwen Wei, Liang Zhao, Lichang Zhang +27
In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3.2 trillion tokens drawn from both English and Chinese texts…