9 papers
MIND-V: Hierarchical World Model for Long-Horizon Robotic Manipulation with RL-based Physical Alignment
Ruicheng Zhang, Mingyang Zhang, Jun Zhou +6
Scalable embodied intelligence is constrained by the scarcity of diverse, long-horizon robotic manipulation data. Existing video world models in this domain are limited to synthesi…
RynnVLA-002: A Unified Vision-Language-Action and World Model
Jun Cen, Siteng Huang, Yuqian Yuan +11
We introduce RynnVLA-002, a unified Vision-Language-Action (VLA) and world model. The world model leverages action and visual inputs to predict future image states, learning the un…
Frequency Autoregressive Image Generation with Continuous Tokens
Hu Yu, Hao Luo, Hangjie Yuan +3
Autoregressive (AR) models for image generation typically adopt a two-stage paradigm of vector quantization and raster-scan ``next-token prediction", inspired by its great success…
Lumos-1: On Autoregressive Video Generation with Discrete Diffusion from a Unified Model Perspective
Hangjie Yuan, Weihua Chen, Jun Cen +11
Autoregressive large language models (LLMs) have unified a vast range of language tasks, inspiring preliminary efforts in autoregressive (AR) video generation. Existing AR video ge…
BayesRAG: Probabilistic Mutual Evidence Corroboration for Multimodal Retrieval-Augmented Generation
Xuan Li, Yining Wang, Haocai Luo +6
Retrieval-Augmented Generation (RAG) has become a pivotal paradigm for Large Language Models (LLMs), yet current approaches struggle with visually rich documents by treating text a…
DualOptim: Enhancing Efficacy and Stability in Machine Unlearning with Dual Optimizers
Xuyang Zhong, Haochen Luo, Chen Liu
Existing machine unlearning (MU) approaches exhibit significant sensitivity to hyperparameters, requiring meticulous tuning that limits practical deployment. In this work, we first…