most citedLongCat-Flash Technical Report

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cs.AI2026

LongCat-Flash-Thinking-2601 Technical Report

Meituan LongCat Team, Anchun Gui, Bei Li +162

We introduce LongCat-Flash-Thinking-2601, a 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model with superior agentic reasoning capability. LongCat-Flash-Thi…

cs.CL2026

Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from Text

Zhihao Xu, Rumei Li, Jiahuan Li +4

Enabling Large Language Models (LLMs) to effectively utilize tools in multi-turn interactions is essential for building capable autonomous agents. However, acquiring diverse and re…

cs.CL2025

A Survey on LLM Mid-Training

Chengying Tu, Xuemiao Zhang, Rongxiang Weng +6

Recent advances in foundation models have highlighted the significant benefits of multi-stage training, with a particular emphasis on the emergence of mid-training as a vital stage…

cs.CL20251 cited

LongCat-Flash Technical Report

Meituan LongCat Team, Bayan, Bei Li +179

We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…

cs.AI2025

Introducing LongCat-Flash-Thinking: A Technical Report

Meituan LongCat Team, Anchun Gui, Bei Li +122

We present LongCat-Flash-Thinking, an efficient 560-billion-parameter open-source Mixture-of-Experts (MoE) reasoning model. Its advanced capabilities are cultivated through a metic…

cs.AI2025

XBOUND: Exploring Capability Boundaries of Device-Control Agents at the State Level

Shaoqing Zhang, Kehai Chen, Zhuosheng Zhang +4

Recent advancements in vision-language models have increased interest in Device-Control Agents (DC agents) for managing graphical user interfaces (GUIs). With the growing complexit…