208 citations · 479 across the 92 of their papers we have counts for
85 papers · 1 filter
BlenderWorld: Benchmarking Visual Agents for 3D Creation from Real-World References
Xinyu Fang, Yuchi Wang, Weihao Yu +12
Recent advances in multimodal large language models (MLLMs) have enabled them to act as autonomous agents, creating and editing 3D models via code or direct software manipulation.…
Intern Lumina U2: A Multi-Codebook Diffusion Large Language Model for Omni-Visual Understanding and Image Generation
Qian Yu, Zongyang Qiu, Juncheng Yan +40
Unified multimodal generation covers discrete, continuous, and hybrid paradigms. Discrete approaches with single-codebook visual tokenizers align naturally with text modeling but h…
CapField-OPD: Learning Continuous Capability Fields via Joint-Anchored Multi-Teacher On-Policy Distillation for Flow Models
Pengyang Ling, Yujie Zhou, Jiazi Bu +6
Reward-specialized post-training produces strong experts for flow-based generative models, while multi-teacher on-policy distillation (OPD) consolidates their capabilities into a s…
WorldReward: Reward Modeling for Camera-Conditioned World Models
Yibin Wang, Zehan Wang, Junshu Tang +13
Camera-conditioned world models generate interactive videos in which commanded actions should induce the expected scene changes while appearance, geometry, and temporal dynamics re…
HPSD: Hybrid-Policy Self-Distillation for Text-Image-to-Video Diffusion Models
Jiazi Bu, Pengyang Ling, Yujie Zhou +10
Text-Image-to-Video (TI2V) models are an emerging unified architecture, where a single model simultaneously supports text-to-video (T2V) and image-to-video (I2V) generation. Given…
Beyond the Current Observation: Evaluating Multimodal Large Language Models in Controllable Non-Markov Games
Shengyuan Ding, Xilin Wei, Xinyu Fang +4
Deploying multimodal foundation models as closed-loop policies increasingly requires conditioning actions on observations that are no longer visible. However, existing benchmarks e…
CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning
Penghui Yang, Long Xing, Xiaoyi Dong +10
Image and video captioning are fundamental tasks that bridge the visual and linguistic domains, playing a critical role in pre-training Large Vision-Language Models (LVLMs). Curren…
AdaGRPO: A Capability-Aware Adaptive Enhancement for Flow-based GRPO
Jiazi Bu, Pengyang Ling, Yujie Zhou +8
Group Relative Policy Optimization (GRPO) has demonstrated remarkable success in aligning text-to-image (T2I) flow models with human preferences. However, we have identified that t…
OVO-S-Bench: A Hierarchical Benchmark for Streaming Spatial Intelligence in Multimodal LLMs
Yifei Li, Pengyiang Liu, Yuhang Zang +4
Multimodal agents in robotics, AR, and autonomous driving must reason about places and layouts from continuous egocentric streams, often using evidence outside the current view. Ex…
Pave-GRPO: Beyond Instantaneous Guidance through Principled Average Velocity Decomposition
Pengyang Ling, Jiazi Bu, Yujie Zhou +6
Group Relative Policy Optimization(GRPO) has emerged as an effective paradigm for aligning flow-based generative models with human preferences. However, the high cost of group roll…
ETCHR: Editing To Clarify and Harness Reasoning
Beichen Zhang, Yuhong Liu, Jinsong Li +3
Multimodal Large Language Models have advanced visual reasoning, yet a purely textual chain of thought remains a bottleneck for questions that require fine-grained focus or view tr…
SetCon: Towards Open-Ended Referring Segmentation via Set-Level Concept Prediction
Zhixiong Zhang, Yizhuo Li, Shuangrui Ding +6
Referring segmentation grounds natural-language queries to pixel-level masks, but extending it to complex scenarios with multiple instances, cross-category groups, or open-ended ta…
From Sparse to Dense: Multi-View GRPO for Flow Models via Augmented Condition Space
Jiazi Bu, Pengyang Ling, Yujie Zhou +8
Group Relative Policy Optimization (GRPO) has emerged as a powerful framework for preference alignment in text-to-image (T2I) flow models. However, we observe that the standard par…
Trust Your Critic: Robust Reward Modeling and Reinforcement Learning for Faithful Image Editing and Generation
Xiangyu Zhao, Peiyuan Zhang, Junming Lin +7
Reinforcement learning (RL) has emerged as a promising paradigm for enhancing image editing and text-to-image (T2I) generation. However, current reward models, which act as critics…
Visual-ERM: Reward Modeling for Visual Equivalence
Ziyu Liu, Shengyuan Ding, Xinyu Fang +7
Vision-to-code tasks require models to reconstruct structured visual inputs, such as charts, tables, and SVGs, into executable or structured representations with high visual fideli…
EndoCoT: Scaling Endogenous Chain-of-Thought Reasoning in Diffusion Models
Xuanlang Dai, Yujie Zhou, Long Xing +6
Recently, Multimodal Large Language Models (MLLMs) have been widely integrated into diffusion frameworks primarily as text encoders to tackle complex tasks such as spatial reasonin…
Visual Self-Refine: A Pixel-Guided Paradigm for Accurate Chart Parsing
Jinsong Li, Xiaoyi Dong, Yuhang Zang +3
While Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities for reasoning and self-correction at the textual level, these strengths provide minimal benefit…
Unified Personalized Reward Model for Vision Generation
Yibin Wang, Yuhang Zang, Feng Han +4
Recent advancements in multimodal reward models (RMs) have significantly propelled the development of visual generation. Existing frameworks typically adopt Bradley-Terry-style pre…
Demo-ICL: In-Context Learning for Procedural Video Knowledge Acquisition
Yuhao Dong, Shulin Tian, Shuai Liu +6
Despite the growing video understanding capabilities of recent Multimodal Large Language Models (MLLMs), existing video benchmarks primarily assess understanding based on models' s…
GraphThinker: Reinforcing Temporally Grounded Video Reasoning with Event Graph Thinking
Zixu Cheng, Da Li, Jian Hu +4
Video reasoning requires a fine-grained understanding of the temporal dependencies and event-level relations between objects and events in videos. Current Multimodal Large Language…
ARM-Thinker: Reinforcing Multimodal Generative Reward Models with Agentic Tool Use and Visual Reasoning
Shengyuan Ding, Xinyu Fang, Ziyu Liu +10
Reward models are critical for aligning vision-language systems with human preferences, yet current approaches suffer from hallucination, weak visual grounding, and an inability to…
TRivia: Self-supervised Fine-tuning of Vision-Language Models for Table Recognition
Junyuan Zhang, Bin Wang, Qintong Zhang +13
Table recognition (TR) aims to transform table images into semi-structured representations such as HTML or Markdown. As a core component of document parsing, TR has long relied on…
Think Visually, Reason Textually: Vision-Language Synergy in ARC
Beichen Zhang, Yuhang Zang, Xiaoyi Dong +4
Abstract reasoning from minimal examples remains a core unsolved problem for frontier foundation models such as GPT-5 and Grok 4. These models still fail to infer structured transf…
Spatial-SSRL: Enhancing Spatial Understanding via Self-Supervised Reinforcement Learning
Yuhong Liu, Beichen Zhang, Yuhang Zang +6
Spatial understanding remains a weakness of Large Vision-Language Models (LVLMs). Existing supervised fine-tuning (SFT) and recent reinforcement learning with verifiable rewards (R…