11 papers
What Generation Knows: Unlocking Fine-Grained Understanding in Unified Multimodal Models
Tengju Ru, Weitong Lian, Zecong Tang +6
Fine-grained visual understanding requires distinguishing subtle differences in local attributes and spatial relations, yet remains challenging for existing vision-language models.…
Kimi K3: Open Frontier Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +398
We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…
RxBrain: Embodied Cognition Foundation Model with Joint Language-Visual Reasoning and Imagination
Haotian Liang, Mingkang Chen, Yufei Huang +27
Embodied cognition requires agents to connect high-level task reasoning with the physical states to be achieved. We introduce Hy-Embodied-RxBrain, an embodied cognition foundation…
Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation
Zhiheng Liu, Weiming Ren, Xiaoke Huang +12
Unified multimodal models typically rely on pretrained vision encoders and use separate visual representations for understanding and generation, creating misalignment between the t…
See, Plan, Rewind: Progress-Aware Vision-Language-Action Models for Robust Robotic Manipulation
Tingjun Dai, Mingfei Han, Tingwen Du +6
Measurement of task progress through explicit, actionable milestones is critical for robust robotic manipulation. This progress awareness enables a model to ground its current task…
TUNA: Taming Unified Visual Representations for Native Unified Multimodal Models
Zhiheng Liu, Weiming Ren, Haozhe Liu +22
Unified multimodal models (UMMs) aim to jointly perform multimodal understanding and generation within a single framework. We present TUNA, a native UMM that builds a unified conti…
INT v.s. FP: A Comprehensive Study of Fine-Grained Low-bit Quantization Formats
Mengzhao Chen, Meng Wu, Hui Jin +10
Modern AI hardware, such as Nvidia's Blackwell architecture, is increasingly embracing low-precision floating-point (FP) formats to handle the pervasive activation outliers in Larg…
From Denoising to Refining: A Corrective Framework for Vision-Language Diffusion Model
Yatai Ji, Teng Wang, Yuying Ge +4
Discrete diffusion models have emerged as a promising direction for vision-language tasks, offering bidirectional context modeling and theoretical parallelization. However, their p…
WorldWeaver: Generating Long-Horizon Video Worlds via Rich Perception
Zhiheng Liu, Xueqing Deng, Shoufa Chen +7
Generative video modeling has made significant strides, yet ensuring structural and temporal consistency over long sequences remains a challenge. Current methods predominantly rely…
Scaling Law for Quantization-Aware Training
Mengzhao Chen, Chaoyi Zhang, Jing Liu +8
Large language models (LLMs) demand substantial computational and memory resources, creating deployment challenges. Quantization-aware training (QAT) addresses these challenges by…
DanceGRPO: Unleashing GRPO on Visual Generation
Zeyue Xue, Jie Wu, Yu Gao +8
Recent advances in generative AI have revolutionized visual content creation, yet aligning model outputs with human preferences remains a critical challenge. While Reinforcement Le…