29 citations · 70 across the 33 of their papers we have counts for
7 papers · 1 filter
WorldGuide: Learning Success-Failure Boundaries in Latent World Models for Vision-Language-Action Policies
Lin Liu, Lu Zhang, Ziying Song +6
Latent world models offer a promising way to improve Vision-Language-Action policies by capturing the consequences of actions. However, models trained primarily on expert demonstra…
STORM-Bench: Evaluating Online Video QA under Evolving and Incomplete Evidence
Siru Zhong, Shenghan Tan, Rihong Yan +6
Reliable online video question answering requires tracking state transitions while selectively abstaining when visual evidence is insufficient. Existing benchmarks focus on static…
PREM: Prefix-Steered Recurrent Memory for Long-Video Understanding
Siru Zhong, Qiongyan Wang, Xiaohui Lv +5
Long-video understanding must capture transient visual evidence under strict token budgets, yet existing methods compress frames, append memory tokens, or alter internal key-value…
EVLP:Learning Unified Embodied Vision-Language Planner with Reinforced Supervised Fine-Tuning
Xinyan Cai, Shiguang Wu, Dafeng Chi +4
In complex embodied long-horizon manipulation tasks, effective task decomposition and execution require synergistic integration of textual logical reasoning and visual-spatial imag…
ActionSink: Toward Precise Robot Manipulation with Dynamic Integration of Action Flow
Shanshan Guo, Xiwen Liang, Junfan Lin +3
Language-instructed robot manipulation has garnered significant interest due to the potential of learning from collected data. While the challenges in high-level perception and pla…
Structured Preference Optimization for Vision-Language Long-Horizon Task Planning
Xiwen Liang, Min Lin, Weiqi Ruan +6
Existing methods for vision-language task planning excel in short-horizon tasks but often fall short in complex, long-horizon planning within dynamic environments. These challenges…
Graph Attention Memory for Visual Navigation
Dong Li, Qichao Zhang, Dongbin Zhao +5
Visual navigation in complex environments is inefficient with traditional reactive policy or general-purposed recurrent policy. To address the long-term memory issue, this paper pr…