4 citations · 12 across the 9 of their papers we have counts for
9 papers
Intern-S2-Preview: Scientific Agentic Foundation Model
Lei Bai, Jiaqi Cao, Chiyu Chen +121
Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sus…
Group Entropy-Controlled Policy Optimization
Guangran Cheng, Chengqi Lyu, Songyang Gao +2
Entropy control has become an effective tool in reinforcement learning (RL) of large language models (LLMs), helping balance exploration-exploitation trade-off during alignment pro…
ThoughtFold: Folding Reasoning Chains via Introspective Preference Learning
Ziyan Liu, Xueda Shen, Yuzhe Gu +7
Large Reasoning Models (LRMs) have achieved remarkable progress thanks to Reinforcement Learning with Verifiable Rewards (RLVR) on Chain-of-Thoughts (CoTs). However, since long CoT…
Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale
Yicheng Zou, Dongsheng Zhu, Lin Zhu +174
We introduce Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model. Scaling to this unprecedented size, the model delivers a comprehensive enhancem…
Empowering Large Language Models on Robotic Manipulation with Affordance Prompting
Guangran Cheng, Chuheng Zhang, Wenzhe Cai +3
While large language models (LLMs) are successful in completing various language processing tasks, they easily fail to interact with the physical world by generating control sequen…
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
Wenzhang Liu, Wenzhe Cai, Kun Jiang +7
In this paper, we present XuanCe, a comprehensive and unified deep reinforcement learning (DRL) library designed to be compatible with PyTorch, TensorFlow, and MindSpore. XuanCe of…
DGMem: Learning Visual Navigation Policy without Any Labels by Dynamic Graph Memory
Wenzhe Cai, Teng Wang, Guangran Cheng +2
In recent years, learning-based approaches have demonstrated significant promise in addressing intricate navigation tasks. Traditional methods for training deep neural network navi…
Robust Navigation with Cross-Modal Fusion and Knowledge Transfer
Wenzhe Cai, Guangran Cheng, Lingyue Kong +2
Recently, learning-based approaches show promising results in navigation tasks. However, the poor generalization capability and the simulation-reality gap prevent a wide range of a…
Bridging Zero-shot Object Navigation and Foundation Models through Pixel-Guided Navigation Skill
Wenzhe Cai, Siyuan Huang, Guangran Cheng +4
Zero-shot object navigation is a challenging task for home-assistance robots. This task emphasizes visual grounding, commonsense inference and locomotion abilities, where the first…