45 citations · 48 across the 11 of their papers we have counts for
12 papers
ReFormBench: Benchmarking the Stability of Response-Conditioned Format Correction in Large Language Models
Tianxiang Gao, Yahan Li, Chenlu Guo +3
Reliable use of large language models requires responses to satisfy formatting requirements across changing instructions. Standard compliance scores do not distinguish preserving a…
Riemann-1.0: An Embodied World Action Model for Physical AI
Haofeng Sun, Jiangbo Pei, Fei Kang +13
We introduce Riemann-1.0, a fully causal autoregressive World Action Model for embodied intelligence. Riemann-1.0 jointly models multi-view visual observations, robot states, and e…
Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory
Zile Wang, Zexiang Liu, Jiaxing Li +20
With the advancement of interactive video generation, diffusion models have increasingly demonstrated their potential as world models. However, existing approaches still struggle t…
TRUST-SQL: Tool-Integrated Multi-Turn Reinforcement Learning for Text-to-SQL over Unknown Schemas
Ai Jian, Xiaoyun Zhang, Eryu Guo +6
Text-to-SQL parsing has achieved remarkable progress under the Full Schema Assumption. However, this premise fails in real-world enterprise environments where databases contain hun…
Skywork-R1V4: Toward Agentic Multimodal Intelligence through Interleaved Thinking with Images and DeepResearch
Yifan Zhang, Liang Hu, Haofeng Sun +12
Despite recent progress in multimodal agentic systems, existing approaches often treat image manipulation and web search as disjoint capabilities, rely heavily on costly reinforcem…
Skywork-R1V3 Technical Report
Wei Shen, Jiangbo Pei, Yi Peng +8
We introduce Skywork-R1V3, an advanced, open-source vision-language model (VLM) that pioneers a new approach to visual reasoning. Its key innovation lies in effectively transferrin…
CSVQA: A Chinese Multimodal Benchmark for Evaluating STEM Reasoning Capabilities of VLMs
Ai Jian, Weijie Qiu, Xiaokun Wang +6
Vision-Language Models (VLMs) have demonstrated remarkable progress in multimodal understanding, yet their capabilities for scientific reasoning remain inadequately assessed. Curre…
Skywork-VL Reward: An Effective Reward Model for Multimodal Understanding and Reasoning
Xiaokun Wang, Peiyu Wang, Jiangbo Pei +9
We propose Skywork-VL Reward, a multimodal reward model that provides reward signals for both multimodal understanding and reasoning tasks. Our technical approach comprises two key…
Skywork R1V2: Multimodal Hybrid Reinforcement Learning for Reasoning
Peiyu Wang, Yichen Wei, Yi Peng +10
We present Skywork R1V2, a next-generation multimodal reasoning model and a major leap forward from its predecessor, Skywork R1V. At its core, R1V2 introduces a hybrid reinforcemen…
Skywork R1V: Pioneering Multimodal Reasoning with Chain-of-Thought
Yi Peng, Peiyu Wang, Xiaokun Wang +12
We introduce Skywork R1V, a multimodal reasoning model extending the an R1-series Large language models (LLM) to visual modalities via an efficient multimodal transfer method. Leve…
Selection, Ensemble, and Adaptation: Advancing Multi-Source-Free Domain Adaptation via Architecture Zoo
Jiangbo Pei, Ruizhe Li, Aidong Men +3
Conventional Multi-Source Free Domain Adaptation (MSFDA) assumes that each source domain provides a single source model, and all source models adopt a uniform architecture. This pa…
Uncertainty-Induced Transferability Representation for Source-Free Unsupervised Domain Adaptation
Jiangbo Pei, Zhuqing Jiang, Aidong Men +3
Source-free unsupervised domain adaptation (SFUDA) aims to learn a target domain model using unlabeled target data and the knowledge of a well-trained source domain model. Most pre…