10 citations · 13 across the 14 of their papers we have counts for
8 papers · 1 filter
Self-Evolving 3D Scene Generation from a Single Image
Kaizhi Zheng, Yue Fan, Jing Gu +3
Generating high-quality, textured 3D scenes from a single image remains a fundamental challenge in vision and graphics. Recent image-to-3D generators recover reasonable geometry fr…
Reasoning Within the Mind: Dynamic Multimodal Interleaving in Latent Space
Chengzhi Liu, Yuzhe Yang, Yue Fan +3
Recent advancements in Multimodal Large Language Models (MLLMs) have significantly enhanced cross-modal understanding and reasoning by incorporating Chain-of-Thought (CoT) reasonin…
Presenting a Paper is an Art: Self-Improvement Aesthetic Agents for Academic Presentations
Chengzhi Liu, Yuzhe Yang, Kaiwen Zhou +5
The promotion of academic papers has become an important means of enhancing research visibility. However, existing automated methods struggle limited storytelling, insufficient aes…
SAFER: Risk-Constrained Sample-then-Filter in Large Language Models
Qingni Wang, Yue Fan, Xin Eric Wang
As large language models (LLMs) are increasingly deployed in risk-sensitive applications such as real-world open-ended question answering (QA), ensuring the trustworthiness of thei…
"PhyWorldBench": A Comprehensive Evaluation of Physical Realism in Text-to-Video Models
Jing Gu, Xian Liu, Yu Zeng +8
Video generation models have achieved remarkable progress in creating high-quality, photorealistic content. However, their ability to accurately simulate physical phenomena remains…
GRIT: Teaching MLLMs to Think with Images
Yue Fan, Xuehai He, Diji Yang +6
Recent studies have demonstrated the efficacy of using Reinforcement Learning (RL) in building reasoning models that articulate chains of thoughts prior to producing final answers.…
Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Models
Qianqi Yan, Yue Fan, Hongquan Li +5
Existing Multimodal Large Language Models (MLLMs) are predominantly trained and tested on consistent visual-textual inputs, leaving open the question of whether they can handle inc…
GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration
Yue Fan, Handong Zhao, Ruiyi Zhang +3
Graphical User Interface (GUI) action grounding is a critical step in GUI automation that maps language instructions to actionable elements on GUI screens. Most recent works of GUI…