13 papers · 1 filter
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…
Socratic-Zero : Bootstrapping Reasoning via Data-Free Agent Co-evolution
Shaobo Wang, Zhengbo Jiao, Zifan Zhang +6
Recent breakthroughs in large language models (LLMs) on reasoning tasks rely heavily on massive, high-quality datasets-typically human-annotated and thus difficult to scale. While…
Skywork UniPic 2.0: Building Kontext Model with Online RL for Unified Multimodal Model
Hongyang Wei, Baixin Xu, Hongbo Liu +18
Recent advances in multimodal models have demonstrated impressive capabilities in unified image generation and editing. However, many prominent open-source models prioritize scalin…
Cross-Learning Fine-Tuning Strategy for Dysarthric Speech Recognition Via CDSD database
Qing Xiao, Yingshan Peng, PeiPei Zhang
Dysarthric speech recognition faces challenges from severity variations and disparities relative to normal speech. Conventional approaches individually fine-tune ASR models pre-tra…
Skywork UniPic: Unified Autoregressive Modeling for Visual Understanding and Generation
Peiyu Wang, Yi Peng, Yimeng Gan +12
We introduce Skywork UniPic, a 1.5 billion-parameter autoregressive model that unifies image understanding, text-to-image generation, and image editing within a single architecture…
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…
MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning
Peng Xia, Jinglu Wang, Yibo Peng +10
Medical Large Vision-Language Models (Med-LVLMs) have shown strong potential in multimodal diagnostic tasks. However, existing single-agent models struggle to generalize across div…
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…
ChatMol: A Versatile Molecule Designer Based on the Numerically Enhanced Large Language Model
Chuanliu Fan, Ziqiang Cao, Zicheng Ma +5
Goal-oriented de novo molecule design, namely generating molecules with specific property or substructure constraints, is a crucial yet challenging task in drug discovery. Existing…
Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis
Zhen Ye, Xinfa Zhu, Chi-Min Chan +17
Recent advances in text-based large language models (LLMs), particularly in the GPT series and the o1 model, have demonstrated the effectiveness of scaling both training-time and i…