13 citations · 22 across the 46 of their papers we have counts for
16 papers · 1 filter
HM3D-M3: A Benchmark for Multi-Agent, Multi-Modal, Multi-Object Goal Navigation
Hongyu Ding, Kanyu Xu, Mingjia Chen +5
Rapid progress in AI agents and robotics makes it a matter of the near future that humans are served by a team of robots. Such a team will receive several goals at once, each speci…
AD-WM: Action-Discriminative World Models for Counterfactual Model Predictive Control
Jiabin Qiu, Zixuan Chen, Hongye Cao +3
Latent world models are typically trained to predict factual transitions, whereas model predictive control (MPC) must compare alternative actions from the same state. A model can t…
Learning from Hard Prompts: Difficulty-aware Advantage Amplification in Dynamic Sampling
Siyuan Gan, Yuhan Li, Xiran Wang +6
Decoupled Clip and Dynamic Sampling Policy Optimization (DAPO) is a prominent variant of Group Relative Policy Optimization (GRPO). DAPO introduces several improvements over GRPO.…
When Teacher Guidance Misleads: Reward-Aligned On-Policy Distillation
Siyuan Gan, Yuhan Li, Xiran Wang +5
On-policy distillation (OPD) has recently emerged as a popular post-training paradigm for large language models (LLMs), providing an efficient way to transfer the knowledge and cap…
Wh0: Generative World Models as Scalable Sources of Egocentric Human Hand Manipulation Data
Yangtao Chen, Zixuan Chen, Peiyang Wang +4
Scaling dexterous manipulation requires generalization across objects, scenes, and tasks, yet existing data sources face a trade-off between scale and scene/embodiment alignment: t…
Tool-Aware Optimization with Entropy Guidance for Efficient Agentic Reinforcement Learning
Hongye Cao, Nuo Yan, Haoyuan Deng +5
Agentic reinforcement learning (RL) equips large language models (LLMs) with tool-use capabilities that substantially improve reasoning on complex tasks. However, integrating exter…
Uni-LaViRA: Language-Vision-Robot Actions Translation for Unified Embodied Navigation
Hongyu Ding, Sizhuo Zhang, Ziming Xu +13
Embodied navigation requires an agent to map language and visual observations to a stream of spatial actions that drive a real robot through environments it has never seen. The dom…
FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation
Dian Shao, Zhengzheng Xu, Peiyang Wang +4
UAV vision-language navigation (VLN) requires an agent to navigate complex 3D environments from an egocentric perspective while following ambiguous multi-step instructions over lon…
V-Dreamer: Automating Robotic Simulation and Trajectory Synthesis via Video Generation Priors
Songjia He, Zixuan Chen, Hongyu Ding +5
Training generalist robots demands large-scale, diverse manipulation data, yet real-world collection is prohibitively expensive, and existing simulators are often constrained by fi…
ST-VLA: Enabling 4D-Aware Spatiotemporal Understanding for General Robot Manipulation
You Wu, Zixuan Chen, Cunxu Ou +9
Robotic manipulation in open-world environments requires reasoning across semantics, geometry, and long-horizon action dynamics. Existing hierarchical Vision-Language-Action (VLA)…
AdaClearGrasp: Learning Adaptive Clearing for Zero-Shot Robust Dexterous Grasping in Densely Cluttered Environments
Zixuan Chen, Wenquan Zhang, Jing Fang +7
In densely cluttered environments, physical interference, visual occlusions, and unstable contacts often cause direct dexterous grasping to fail, while aggressive singulation strat…
RoTri-Diff: A Spatial Robot-Object Triadic Interaction-Guided Diffusion Model for Bimanual Manipulation
Zixuan Chen, Nga Teng Chan, Yiwen Hou +8
Bimanual manipulation is a fundamental robotic skill that requires continuous and precise coordination between two arms. While imitation learning (IL) is the dominant paradigm for…
MoMaStage: Skill-State Graph Guided Planning and Closed-Loop Execution for Long-Horizon Indoor Mobile Manipulation
Chenxu Li, Zixuan Chen, Yetao Li +5
Long-horizon indoor mobile manipulation (MoMa) requires robots to execute extended navigation-manipulation sequences whose feasibility depends on state changes induced by preceding…
INHerit-SG: Incremental Hierarchical Semantic Scene Graphs for Complex Embodied Retrieval
YukTungSamuel Fang, Zhikang Shi, Jiabin Qiu +5
Object retrieval in 3D scenes remains difficult when queries combine hierarchical context, attributes, negation, and chained spatial relations. Existing semantic maps, scene graphs…
Efficient Reinforcement Learning with Semantic and Token Entropy for LLM Reasoning
Hongye Cao, Zhixin Bai, Ziyue Peng +5
Reinforcement learning with verifiable rewards (RLVR) has demonstrated superior performance in enhancing the reasoning capability of large language models (LLMs). However, this acc…
Thinking-Based Non-Thinking: Solving the Reward Hacking Problem in Training Hybrid Reasoning Models via Reinforcement Learning
Siyuan Gan, Jiaheng Liu, Boyan Wang +8
Large reasoning models (LRMs) have attracted much attention due to their exceptional performance. However, their performance mainly stems from thinking, a long Chain of Thought (Co…