5 papers · 1 filter
Intern-S1: A Scientific Multimodal Foundation Model
Lei Bai, Zhongrui Cai, Yuhang Cao +173
In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…
InternBootcamp: Boosting LLM Reasoning with Verifiable Task Scaling
Peiji Li, Jiasheng Ye, Yongkang Chen +12
Large language models (LLMs) have revolutionized artificial intelligence by enabling complex reasoning capabilities. While recent advancements in reinforcement learning (RL) have p…
Implicit Reward as the Bridge: A Unified View of SFT and DPO Connections
Bo Wang, Qinyuan Cheng, Runyu Peng +7
Post-training processes are essential phases in grounding pre-trained language models to real-world tasks, with learning from demonstrations or preference signals playing a crucial…
UnitCoder: Scalable Iterative Code Synthesis with Unit Test Guidance
Yichuan Ma, Yunfan Shao, Peiji Li +5
Large Language Models (LLMs) have demonstrated remarkable capabilities in various tasks, yet code generation remains a major challenge. Current approaches for obtaining high-qualit…
FastMCTS: A Simple Sampling Strategy for Data Synthesis
Peiji Li, Kai Lv, Yunfan Shao +5
Synthetic high-quality multi-step reasoning data can significantly enhance the performance of large language models on various tasks. However, most existing methods rely on rejecti…