8 papers · 1 filter
Image2Sim: Scaling Embodied Navigation via Generative Neural Simulator
Zihan Wang, Seungjun Lee, Yinghao Xu +1
Embodied navigation aims to build agents that interpret multimodal goals, reason in 3D space, and reach target destinations reliably in the real world. However, progress remains co…
CLORE: Content-Level Optimization for Reasoning Efficiency
Yuyang Wu, Qiyao Xue, Guanxing Lu +4
Reinforcement learning post-training has improved the reasoning ability of large language models, but often produces unnecessarily long, repetitive, or semantically opaque reasonin…
GA-VLN: Geometry-Aware BEV Representation for Efficient Vision-Language Navigation
Jiahao Yang, Zihan Wang, Xiangyang Li +4
Despite significant progress in Vision-Language Navigation (VLN), existing approaches still rely on dense RGB videos that produce excessive patch tokens and lack explicit spatial s…
WorldReasonBench: Human-Aligned Stress Testing of Video Generators as Future World-State Predictors
Keming Wu, Yijing Cui, Wenhan Xue +11
Commercial video generation systems such as Seedance2.0 and Veo3.1 have rapidly improved, strengthening the view that video generators may be evolving into "world simulators." Yet…
How Many Visual Tokens Do Multimodal Language Models Need? Scaling Visual Token Pruning with F^3A
YiJie Huang, Yiqun Zhang, Zhuoyue Jia +7
Vision-language models improve perception by feeding increasingly long visual token sequences into language backbones, but the resulting inference cost raises a basic scaling quest…
Learning Actionable Manipulation Recovery via Counterfactual Failure Synthesis
Dayou Li, Jiuzhou Lei, Hao Wang +6
While recent foundation models have significantly advanced robotic manipulation, these systems still struggle to autonomously recover from execution errors. Current failure-learnin…
HiMemVLN: Enhancing Reliability of Open-Source Zero-Shot Vision-and-Language Navigation with Hierarchical Memory System
Kailin Lyu, Kangyi Wu, Pengna Li +9
LLM-based agents have demonstrated impressive zero-shot performance in vision-language navigation (VLN) tasks. However, most zero-shot methods primarily rely on closed-source LLMs…
Wild-Drive: Off-Road Scene Captioning and Path Planning via Robust Multi-modal Routing and Efficient Large Language Model
Zihang Wang, Xu Li, Benwu Wang +7
Explainability and transparent decision-making are essential for the safe deployment of autonomous driving systems. Scene captioning summarizes environmental conditions and risk fa…