2 citations · 2 across the 13 of their papers we have counts for
14 papers
Building Presentation Intelligence for High-Quality Slide Generation
Yuhang Xie, Cheng Li, Chenliang Li +6
PowerPoint presentations (PPTs) are a dominant medium for communication across diverse domains, yet high-quality PPT generation still depends heavily on labor-intensive human effor…
HappyWorld-Bench
Zhiqi Bai, Junai Cai, Yixin Chen +33
Evaluating world models requires assessing both the quality of the worlds they generate and their consistency and responsiveness under exploration, interaction, and modification. W…
One to More, More to One: Category-Aware Iterative Expert Training for Software Engineering Agents
Jie Zhao, Ziyu Jiang, Suhang Zheng +3
Repository-level software engineering (SWE) comprises heterogeneous task categories, whose progress under pooled agentic reinforcement learning can be uneven: gains in some categor…
RubricRM: Generative Reward Modeling via Dynamic Rubrics for Image Generation and Editing
Zijian Kan, Wei Wang, Long Luo +6
Reward models play an essential role in aligning visual generative models, yet most existing visual reward models use a single scalar score or rely on fixed criteria that cannot ad…
OmniJudge or OmniBias? Diagnosing Multimodal Judges through Balanced, Decoupled Lenses
Guangzheng Hu, Ziyue Jiang, Weixu Qiao +14
Multimodal understanding models that can jointly judge text-to-image (T2I), text-to-video (T2V) and text-to-speech (TTS) generation are increasingly used as "OmniJudges" for evalua…
DLawBench: Evaluating LLMs Through Multi-Turn Legal Consultation
Li Zhang, Yuzhen Shi, Yiran Hu +15
Lawyer-client consultation is a critical starting point for legal services. Effective legal assistance hinges on eliciting sufficient and truthful information from clients in order…
DMC-CF: Dynamic Multimodal CounterFactual QA benchmark for Causal Reasoning
Junzhe Zhang, Huixuan Zhang, Guirong Wang +5
With the rapid advancement of multimodal large language models (MLLMs), models have demonstrated increasingly powerful multimodal capabilities. However, whether MLLMs trained throu…
Qwen-Image-VAE-2.0 Technical Report
Zekai Zhang, Deqing Li, Kuan Cao +27
We present Qwen-Image-VAE-2.0, a suite of high-compression Variational Autoencoders (VAEs) that achieve significant advances in both reconstruction fidelity and diffusability. To a…
Qwen-Image-2.0 Technical Report
Bing Zhao, Chenfei Wu, Deqing Li +72
We present Qwen-Image-2.0, an omni-capable image generation foundation model that unifies high-fidelity generation and precise image editing within a single framework. Despite rece…
UserGPT Technical Report
Yunyi Xuan, Hao Yi, Fengling Mao +9
Personalized user understanding from large-scale digital traces remains a fundamental challenge. Traditional user profiling methods rely on discriminative models and manual feature…
Logics-Parsing-Omni Technical Report
Xin An, Jingyi Cai, Xiangyang Chen +22
Addressing the challenges of fragmented task definitions and the heterogeneity of unstructured data in multimodal parsing, this paper proposes the Omni Parsing framework. This fram…
Logics-STEM: Empowering LLM Reasoning via Failure-Driven Post-Training and Document Knowledge Enhancement
Mingyu Xu, Cheng Fang, Keyue Jiang +16
We present Logics-STEM, a state-of-the-art reasoning model fine-tuned on Logics-STEM-SFT-Dataset, a high-quality and diverse dataset at 10M scale that represents one of the largest…
Logics-Parsing Technical Report
Xiangyang Chen, Shuzhao Li, Xiuwen Zhu +7
Recent advances in Large Vision-Language models (LVLM) have spurred significant progress in document parsing task. Compared to traditional pipeline-based methods, end-to-end paradi…
Qwen-Image Technical Report
Chenfei Wu, Jiahao Li, Jingren Zhou +36
We present Qwen-Image, an image generation foundation model in the Qwen series that achieves significant advances in complex text rendering and precise image editing. To address th…