most citedSeed-Coder: Let the Code Model Curate Data for Itself

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cs.DC2025

AsyncHZP: Hierarchical ZeRO Parallelism with Asynchronous Scheduling for Scalable LLM Training

Huawei Bai, Yifan Huang, Wenqi Shi +4

The training efficiency and scalability of language models on massive clusters currently remain a critical bottleneck. Mainstream approaches like ND parallelism are often cumbersom…

cs.CL2025★ 1 cited

Seed-Coder: Let the Code Model Curate Data for Itself

ByteDance Seed, Yuyu Zhang, Jing Su +24

Code data in large language model (LLM) pretraining is recognized crucial not only for code-related tasks but also for enhancing general intelligence of LLMs. Current open-source L…

cs.SE2025

A Vulnerability Code Intent Summary Dataset

Yifan Huang, Weisong Sun, Yubin Qu

In the era of Large Language Models (LLMs), the code summarization technique boosts a lot, along with the emergence of many new significant works. However, the potential of code su…