1 citations · 1 across the 11 of their papers we have counts for
12 papers
Benchmarking Behavioral Steerability in Behavior Foundation Models
Minghe Gao, Zhanxi Yan, Jiahui Liu +9
Behavior Foundation Models (BFMs) are emerging as a paradigm for translating human intentions into executable humanoid behaviors. As these models evolve beyond behavior generation…
Iron: Intent-Aligned and Retrospective Dual Learning Framework for Enhancing Generalist Virtual Agents
Jiahe Ying, Wendong Bu, Kaihang Pan +6
Achieving virtual agents capable of automating tasks across diverse digital environments remains a pivotal challenge in Embodied AI. While Multimodal Large Language Models (MLLMs)…
SCOPE: Evolving Symbolic World for Planning in Open-Ended Environments
Yundaichuan Zhan, Minghe Gao, Zhongqi Yue +7
Recent works have explored integrating Vision-Language Models (VLMs) with classical planners that rely on symbolic representations of planning problems to generate long-horizon pla…
Learning to Adapt: Self-Improving Web Agent via Cognitive-Aware Exploration
Weile Chen, Bingchen Miao, Qifan Yu +6
Recent advances in Multimodal Large Language Models (MLLMs) have led to promising progress in web agents. However, existing web agents often rely on handcrafted execution pipelines…
CORE: Code-based Inverse Self-Training Framework with Graph Expansion for Virtual Agents
Keyu Wang, Bingchen Miao, Wendong Bu +7
The development of Multimodal Virtual Agents has made significant progress through the integration of Multimodal Large Language Models. However, mainstream training paradigms face…
OmniMoGen: Unifying Human Motion Generation via Learning from Interleaved Text-Motion Instructions
Wendong Bu, Kaihang Pan, Yuze Lin +6
Large language models (LLMs) have unified diverse linguistic tasks within a single framework, yet such unification remains unexplored in human motion generation. Existing methods a…
WiseEdit: Benchmarking Cognition- and Creativity-Informed Image Editing
Kaihang Pan, Weile Chen, Haiyi Qiu +6
Recent image editing models boast next-level intelligent capabilities, facilitating cognition- and creativity-informed image editing. Yet, existing benchmarks provide too narrow a…
What Limits Virtual Agent Application? OmniBench: A Scalable Multi-Dimensional Benchmark for Essential Virtual Agent Capabilities
Wendong Bu, Yang Wu, Qifan Yu +10
As multimodal large language models (MLLMs) advance, MLLM-based virtual agents have demonstrated remarkable performance. However, existing benchmarks face significant limitations,…
FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL
Kaihang Pan, Wendong Bu, Yuruo Wu +7
Recent studies extend the autoregression paradigm to text-to-image generation, achieving performance comparable to diffusion models. However, our new PairComp benchmark -- featurin…
Janus-Pro-R1: Advancing Collaborative Visual Comprehension and Generation via Reinforcement Learning
Kaihang Pan, Yang Wu, Wendong Bu +9
Recent endeavors in Multimodal Large Language Models (MLLMs) aim to unify visual comprehension and generation. However, these two capabilities remain largely independent, as if the…
Boosting Virtual Agent Learning and Reasoning: A Step-Wise, Multi-Dimensional, and Generalist Reward Model with Benchmark
Bingchen Miao, Yang Wu, Minghe Gao +7
The development of Generalist Virtual Agents (GVAs) has shown significant promise in autonomous task execution. However, current training paradigms face critical limitations, inclu…
Generalist Virtual Agents: A Survey on Autonomous Agents Across Digital Platforms
Minghe Gao, Wendong Bu, Bingchen Miao +7
In this paper, we introduce the Generalist Virtual Agent (GVA), an autonomous entity engineered to function across diverse digital platforms and environments, assisting users by ex…