1 citations · 1 across the 12 of their papers we have counts for
13 papers
NoiseGate: Learning Per-Latent Timestep Schedules as Information Gating in World Action Models
Wen Huang, Haoran Sun, Yongjian Guo +8
World Action Models (WAMs) are an emerging family of policies that tie robot action generation to future-observation modeling. In this work, we focus on the joint video--action mod…
Sword: Style-Robust World Models as Simulators via Dynamic Latent Bootstrapping for VLA Policy Post-Training
Jiaxuan Gao, Yongjian Guo, Zhong Guan +5
The integration of Vision-Language-Action (VLA) models with World Models has gained increasing attention. One representative approach treats learned World Models as generative simu…
AblateCell: A Reproduce-then-Ablate Agent for Virtual Cell Repositories
Xue Xia, Chengkai Yao, Mingyu Tsoi +10
Systematic ablations are essential to attribute performance gains in AI Virtual Cells, yet they are rarely performed because biological repositories are under-standardized and tigh…
SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents
Ziao Zhang, Kou Shi, Shiting Huang +13
As the capability frontier of autonomous agents continues to expand, they are increasingly able to complete specialized tasks through plug-and-play external skills. Yet current ben…
Unify-Agent: A Unified Multimodal Agent for World-Grounded Image Synthesis
Shuang Chen, Quanxin Shou, Hangting Chen +16
Unified multimodal models provide a natural and promising architecture for understanding diverse and complex real-world knowledge while generating high-quality images. However, the…
Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models
Yu Zeng, Wenxuan Huang, Zhen Fang +14
Multimodal Large Language Models (MLLMs) have advanced VQA and now support Vision-DeepResearch systems that use search engines for complex visual-textual fact-finding. However, eva…
VimRAG: Navigating Massive Visual Context in Retrieval-Augmented Generation via Multimodal Memory Graph
Qiuchen Wang, Shihang Wang, Yu Zeng +9
Effectively retrieving, reasoning, and understanding multimodal information remains a critical challenge for agentic systems. Traditional Retrieval-augmented Generation (RAG) metho…
UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision
Ruiyan Han, Zhen Fang, XinYu Sun +9
While Unified Multimodal Models (UMMs) have achieved remarkable success in cross-modal comprehension, a significant gap persists in their ability to leverage such internal knowledg…
Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models
Wenxuan Huang, Yu Zeng, Qiuchen Wang +14
Multimodal large language models (MLLMs) have achieved remarkable success across a broad range of vision tasks. However, constrained by the capacity of their internal world knowled…
Actial: Activate Spatial Reasoning Ability of Multimodal Large Language Models
Xiaoyu Zhan, Wenxuan Huang, Hao Sun +11
Recent advances in Multimodal Large Language Models (MLLMs) have significantly improved 2D visual understanding, prompting interest in their application to complex 3D reasoning tas…
Unifying Tree Search Algorithm and Reward Design for LLM Reasoning: A Survey
Jiaqi Wei, Xiang Zhang, Yuejin Yang +10
Deliberative tree search is a cornerstone of modern Large Language Model (LLM) research, driving the pivot from brute-force scaling toward algorithmic efficiency. This single parad…
Agentic Jigsaw Interaction Learning for Enhancing Visual Perception and Reasoning in Vision-Language Models
Yu Zeng, Wenxuan Huang, Shiting Huang +9
Although current large Vision-Language Models (VLMs) have advanced in multimodal understanding and reasoning, their fundamental perceptual and reasoning abilities remain limited. S…
AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
Zhouhong Gu, Xiaoxuan Zhu, Yin Cai +12
Large language model based multi-agent systems have demonstrated significant potential in social simulation and complex task resolution domains. However, current frameworks face cr…