12 papers
Davinci-Tool: Scaling Agentic Tool-Use Supervision with Verifiable Executable Environments
Xiaoyang Yuan, Ji Zhao, Xingyu Hu +7
Reliable agentic tool use requires training data that pair diverse multi-step workflows with executable evidence that the requested outcomes were achieved. Scaling either trajector…
OmniTraffic: A Controllable Generation Pipeline and Benchmark for Spatio-Temporal Traffic Reasoning
Maonan Wang, Zhengyan Huang, Kemou Jiang +13
Traffic scene understanding requires models to reason beyond object recognition, including lane topology, multi-view geometry, temporal evolution, and signal-phase semantics. Howev…
InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain
Tiancheng Han, Yong Li, Wuzhou Yu +2
Long-context tasks require LLMs to identify and preserve answer-relevant information from large contexts. Chunk-wise memory agents address this issue by sequentially reading docume…
SetCon: Towards Open-Ended Referring Segmentation via Set-Level Concept Prediction
Zhixiong Zhang, Yizhuo Li, Shuangrui Ding +6
Referring segmentation grounds natural-language queries to pixel-level masks, but extending it to complex scenarios with multiple instances, cross-category groups, or open-ended ta…
Design First, Code Later: Aesthetically Pleasing Template-Free Slides Generation
Zhiyao Cui, Chenxu Wang, Shuyue Hu +4
Producing presentation slides automatically entails coordinating narrative structure with page-level graphic design under strict spatial constraints. For such structured multimodal…
CiQi-Agent: Aligning Vision, Tools and Aesthetics in Multimodal Agent for Cultural Reasoning on Chinese Porcelains
Wenhan Wang, Zhixiang Zhou, Zhongtian Ma +8
The connoisseurship of antique Chinese porcelain demands extensive historical expertise, material understanding, and aesthetic sensitivity, making it difficult for non-specialists…
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…
From Diagnosis to Improvement: Probing Spatio-Physical Reasoning in Vision Language Models
Tiancheng Han, Yunfei Gao, Yong Li +3
Spatio-physical reasoning, a foundation capability for understanding the real physics world, is a critical step towards building robust world models. While recent vision language m…
SafeWork-R1: Coevolving Safety and Intelligence under the AI-45 Law
Shanghai AI Lab, :, Yicheng Bao +115
We introduce SafeWork-R1, a cutting-edge multimodal reasoning model that demonstrates the coevolution of capabilities and safety. It is developed by our proposed SafeLadder framewo…
MM-PRM: Enhancing Multimodal Mathematical Reasoning with Scalable Step-Level Supervision
Lingxiao Du, Fanqing Meng, Zongkai Liu +4
While Multimodal Large Language Models (MLLMs) have achieved impressive progress in vision-language understanding, they still struggle with complex multi-step reasoning, often prod…
CPGD: Toward Stable Rule-based Reinforcement Learning for Language Models
Zongkai Liu, Fanqing Meng, Lingxiao Du +4
Recent advances in rule-based reinforcement learning (RL) have significantly improved the reasoning capability of language models (LMs) with rule-based rewards. However, existing R…
MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning
Fanqing Meng, Lingxiao Du, Zongkai Liu +12
DeepSeek R1, and o1 have demonstrated powerful reasoning capabilities in the text domain through stable large-scale reinforcement learning. To enable broader applications, some wor…