3 citations · 5 across the 13 of their papers we have counts for
8 papers · 1 filter
Earth AI: Unlocking Geospatial Insights with Foundation Models and Cross-Modal Reasoning
Aaron Bell, Amit Aides, Amr Helmy +57
Geospatial data offers immense potential for understanding our planet. However, the sheer volume and diversity of this data along with its varied resolutions, timescales, and spars…
MemMamba: Rethinking Memory Patterns in State Space Model
Youjin Wang, Yangjingyi Chen, Jiahao Yan +2
With the explosive growth of data, long-sequence modeling has become increasingly important in tasks such as natural language processing and bioinformatics. However, existing metho…
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…
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…
Contrastive clustering based on regular equivalence for influential node identification in complex networks
Yanmei Hu, Yihang Wu, Bing Sun +4
Identifying influential nodes in complex networks is a fundamental task in network analysis with wide-ranging applications across domains. While deep learning has advanced node inf…
Scalable Complexity Control Facilitates Reasoning Ability of LLMs
Liangkai Hang, Junjie Yao, Zhiwei Bai +17
The reasoning ability of large language models (LLMs) has been rapidly advancing in recent years, attracting interest in more fundamental approaches that can reliably enhance their…
DTVM: Revolutionizing Smart Contract Execution with Determinism and Compatibility
Wei Zhou, Xiong Xu, Changzheng Wei +22
We introduce the DeTerministic Virtual Machine (DTVM) Stack, a next-generation smart contract execution framework designed to address critical performance, determinism, and ecosyst…
Earlier Tokens Contribute More: Learning Direct Preference Optimization From Temporal Decay Perspective
Ruichen Shao, Bei Li, Gangao Liu +5
Direct Preference Optimization (DPO) has gained attention as an efficient alternative to reinforcement learning from human feedback (RLHF) for aligning large language models (LLMs)…