2 citations · 2 across the 11 of their papers we have counts for
11 papers
HSD: Hybrid Hindsight Self-Distillation
Qiye Cai, Yichuan Ma, Peiji Li +7
Reinforcement learning with verifiable rewards (RLVR) provides reliable outcome supervision for language model reasoning, but scalar trajectory rewards offer limited guidance for t…
Beyond Mode Collapse: Distribution Matching for Diverse Reasoning
Xiaozhe Li, Yang Li, Xinyu Fang +10
On-policy reinforcement learning methods like GRPO suffer from mode collapse: they exhibit reduced solution diversity, concentrating probability mass on a single solution once disc…
COSMO-Agent: Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration
Liyuan Deng, Shujian Deng, Yongkang Chen +6
Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric edits under diverse, coupled c…
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…
Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration
Liyuan Deng, Shujian Deng, Yongkang Chen +6
Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric edits under diverse, coupled c…
DataFactory: Collaborative Multi-Agent Framework for Advanced Table Question Answering
Tong Wang, Chi Jin, Yongkang Chen +3
Table Question Answering (TableQA) enables natural language interaction with structured tabular data. However, existing large language model (LLM) approaches face critical limitati…
Timely Machine: Awareness of Time Makes Test-Time Scaling Agentic
Yichuan Ma, Linyang Li, Yongkang chen +5
As large language models (LLMs) increasingly tackle complex reasoning tasks, test-time scaling has become critical for enhancing capabilities. However, in agentic scenarios with fr…
TL-GRPO: Turn-Level RL for Reasoning-Guided Iterative Optimization
Peiji Li, Linyang Li, Handa Sun +15
Large language models have demonstrated strong reasoning capabilities in complex tasks through tool integration, which is typically framed as a Markov Decision Process and optimize…
Mixing Expert Knowledge: Bring Human Thoughts Back To the Game of Go
Yichuan Ma, Linyang Li, Yongkang Chen +5
Large language models (LLMs) have demonstrated exceptional performance in reasoning tasks such as mathematics and coding, matching or surpassing human capabilities. However, these…
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…