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20242026
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cs.CL2026

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…

cs.CL2026

Switch Attention: Towards Dynamic and Fine-grained Hybrid Transformers

Yusheng Zhao, Hourun Li, Bohan Wu +5

The attention mechanism has been the core component in modern transformer architectures. However, the computation of standard full attention scales quadratically with the sequence…

cs.CL2025

A Survey on Efficient Large Language Model Training: From Data-centric Perspectives

Junyu Luo, Bohan Wu, Xiao Luo +8

Post-training of Large Language Models (LLMs) is crucial for unlocking their task generalization potential and domain-specific capabilities. However, the current LLM post-training…

cs.CL2025

Large Language Model Agent: A Survey on Methodology, Applications and Challenges

Junyu Luo, Weizhi Zhang, Ye Yuan +23

The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic a…

cs.CL2024

RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response

Junyu Luo, Xiao Luo, Kaize Ding +3

Supervised fine-tuning (SFT) plays a crucial role in adapting large language models (LLMs) to specific domains or tasks. However, as demonstrated by empirical experiments, the coll…