1 citations · 1 across the 12 of their papers we have counts for
13 papers
WorldCast: Exploring Intelligent Visual Generation in World State Prediction
Wenhao Yan, Haodong Li, Xiaotong Li +9
Humans interpret multimodal observations of the world and forecast how it will evolve. Recent multimodal generative systems have demonstrated similar capabilities: they can integra…
Seeing Is No Longer Believing: Frontier Image Generation Models, Synthetic Visual Evidence, and Real-World Risk
Shuai Wu, Xue Li, Yanna Feng +6
Image generation systems can produce plausible photographs, readable documents, and consistent depictions of people and places. When these artifacts are presented as records of rea…
Verbal tics in frontier language models: A critical review of current releases, research evidence, and public discussion
Shuai Wu, Xue Li, Yanna Feng +6
Repeated praise, canned reassurance, familiar contrasts, and conspicuous vocabulary are recurring subjects in discussions of large language models. Their interpretation depends on…
An Inspectable LLM Council for Multi-Model Research Answer Aggregation
Shuai Wu, Xue Li, Yanna Feng +3
Long-form research questions often require answers that combine complementary details, reconcile conflicting estimates, and retain qualifications across several large language mode…
OpenSubject: Leveraging Video-Derived Identity and Diversity Priors for Subject-driven Image Generation and Manipulation
Yexin Liu, Manyuan Zhang, Yueze Wang +8
Despite the promising progress in subject-driven image generation, current models often deviate from the reference identities and struggle in complex scenes with multiple subjects.…
EditThinker: Unlocking Iterative Reasoning for Any Image Editor
Hongyu Li, Manyuan Zhang, Dian Zheng +11
Instruction-based image editing has emerged as a prominent research area, which, benefiting from image generation foundation models, have achieved high aesthetic quality, making in…
OneThinker: All-in-one Reasoning Model for Image and Video
Kaituo Feng, Manyuan Zhang, Hongyu Li +11
Reinforcement learning (RL) has recently achieved remarkable success in eliciting visual reasoning within Multimodal Large Language Models (MLLMs). However, existing approaches typ…
Thinking-while-Generating: Interleaving Textual Reasoning throughout Visual Generation
Ziyu Guo, Renrui Zhang, Hongyu Li +6
Recent advances in visual generation have increasingly explored the integration of reasoning capabilities. They incorporate textual reasoning, i.e., think, either before (as pre-pl…
AIA: Rethinking Architecture Decoupling Strategy In Unified Multimodal Model
Dian Zheng, Manyuan Zhang, Hongyu Li +7
Unified multimodal models for image generation and understanding represent a significant step toward AGI and have attracted widespread attention from researchers. The main challeng…
CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images
Chengqi Duan, Kaiyue Sun, Rongyao Fang +10
Recent advances in Large Language Models (LLMs) and Vision Language Models (VLMs) have shown significant progress in mathematical reasoning, yet they still face a critical bottlene…
Think with 3D: Geometric Imagination Grounded Spatial Reasoning from Limited Views
Zhangquan Chen, Manyuan Zhang, Xinlei Yu +8
Though recent advances in vision-language models (VLMs) have achieved remarkable progress across a wide range of multimodal tasks, understanding 3D spatial relationships from limit…
LongCat-Flash Technical Report
Meituan LongCat Team, Bayan, Bei Li +179
We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…
MoTE: Mixture of Ternary Experts for Memory-efficient Large Multimodal Models
Hongyu Wang, Jiayu Xu, Ruiping Wang +5
Large multimodal Mixture-of-Experts (MoEs) effectively scale the model size to boost performance while maintaining fixed active parameters. However, previous works primarily utiliz…