6 papers · 1 filter
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…
Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning
Wenkai Yang, Shuming Ma, Yankai Lin +1
Recent studies have shown that making a model spend more time thinking through longer Chain of Thoughts (CoTs) enables it to gain significant improvements in complex reasoning task…
DeepCritic: Deliberate Critique with Large Language Models
Wenkai Yang, Jingwen Chen, Yankai Lin +1
As Large Language Models (LLMs) are rapidly evolving, providing accurate feedback and scalable oversight on their outputs becomes an urgent and critical problem. Leveraging LLMs as…
Super(ficial)-alignment: Strong Models May Deceive Weak Models in Weak-to-Strong Generalization
Wenkai Yang, Shiqi Shen, Guangyao Shen +5
Superalignment, where humans act as weak supervisors for superhuman models, has become a crucial problem with the rapid development of Large Language Models (LLMs). Recent work has…
Distilling Rule-based Knowledge into Large Language Models
Wenkai Yang, Yankai Lin, Jie Zhou +1
Large language models (LLMs) have shown incredible performance in completing various real-world tasks. The current paradigm of knowledge learning for LLMs is mainly based on learni…
Towards Codable Watermarking for Injecting Multi-bits Information to LLMs
Lean Wang, Wenkai Yang, Deli Chen +5
As large language models (LLMs) generate texts with increasing fluency and realism, there is a growing need to identify the source of texts to prevent the abuse of LLMs. Text water…