4 papers
NebulaExp-8B: An Empirical Post-Training Pipeline via Full-Scale Ablation Research
Qiaobo Hao, Yangqian Wu, Shunyi Wang +5
Post-training alignment determines the reasoning and human preference following capabilities of large language models, yet most existing works withhold detailed data construction,…
TeleCom-Bench: How Far Are Large Language Models from Industrial Telecommunication Applications?
Jieting Xiao, Yun Lin, Huizhen Qiu +10
While Large Language Models have achieved remarkable integration in various vertical scenarios, their deployment in the telecommunications domain remains exploratory due to the lac…
KALE-LM-Chem: Vision and Practice Toward an AI Brain for Chemistry
Weichen Dai, Yezeng Chen, Zijie Dai +9
Recent advancements in large language models (LLMs) have demonstrated strong potential for enabling domain-specific intelligence. In this work, we present our vision for building a…
KELPS: A Framework for Verified Multi-Language Autoformalization via Semantic-Syntactic Alignment
Jiyao Zhang, Chengli Zhong, Hui Xu +2
Modern large language models (LLMs) show promising progress in formalizing informal mathematics into machine-verifiable theorems. However, these methods still face bottlenecks due…