9 citations · 10 across the 15 of their papers we have counts for
6 papers · 1 filter
From Parameters to Behaviors: A Survey of Model Fusion for Large Language Models
Shuo Cai, Yanggan Gu, Zihao Wang +8
Model fusion integrates the capabilities from source models into a single target model. As of June 2026, Hugging Face hosts more than 2M models. This growing pool provides a rich b…
DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
DeepSeek-AI, Anyi Xu, Bangcai Lin +315
We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSe…
The Illusion of Role Separation: Hidden Shortcuts in LLM Role Learning (and How to Fix Them)
Zihao Wang, Yibo Jiang, Jiahao Yu +1
Large language models (LLMs) that integrate multiple input roles (e.g., system instructions, user queries, external tool outputs) are increasingly prevalent in practice. Ensuring t…
RePPL: Recalibrating Perplexity by Uncertainty in Semantic Propagation and Language Generation for Explainable QA Hallucination Detection
Yiming Huang, Junyan Zhang, Zihao Wang +5
Large Language Models (LLMs) have become powerful, but hallucinations remain a vital obstacle to their trustworthy use. Previous works improved the capability of hallucination dete…
Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models
Wenting Tan, Dongxiao Chen, Jieting Xue +2
Large Language Models (LLMs) exhibit impressive performance across various domains but still struggle with arithmetic reasoning tasks. Recent work shows the effectiveness of prompt…
Transforming and Combining Rewards for Aligning Large Language Models
Zihao Wang, Chirag Nagpal, Jonathan Berant +4
A common approach for aligning language models to human preferences is to first learn a reward model from preference data, and then use this reward model to update the language mod…