10 citations · 25 across the 12 of their papers we have counts for
12 papers
H-VLA: Hierarchical Vision-Language-Action Model with Key-Action Reasoning and Motion Planning in a Unified Action Space
Xiongfeng Peng, Lu Xu, Yandong Wang +10
Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but many existing methods still rely on direct mappings from language and visual observati…
Beyond Simplification: DFT-GEN for Fidelity-Preserving Visual Accessibility in Dyslexia-Friendly Educational Texts
Jiaqian Yu, Chen Jason Zhang, Haoyang Li +1
Dense educational texts impose avoidable reading friction on people with dyslexia, yet generic simplification can delete terminology, task constraints, or source evidence that read…
Co-VLA: Coordination-Aware Structured Action Modeling for Dual-Arm Vision-Language-Action Systems
Yandong Wang, Jiaqian Yu, Xiongfeng Peng +8
Vision-language-action (VLA) models show strong capabilities in single and dual-arm robotic manipulation. Prior works show coordinated bimanual behaviors can emerge from end-to-end…
Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation
Zirui Zheng, Jiaqian Yu, Xiongfeng Peng +7
Action-conditioned world models have emerged as a promising paradigm for robot learning, offering a scalable alternative to costly real-world experimentation by generating action-c…
Jigsaw-R1: A Study of Rule-based Visual Reinforcement Learning with Jigsaw Puzzles
Zifu Wang, Junyi Zhu, Bo Tang +4
The application of rule-based reinforcement learning (RL) to multimodal large language models (MLLMs) introduces unique challenges and potential deviations from findings in text-on…
BLADE: Benchmarking Language Model Agents for Data-Driven Science
Ken Gu, Ruoxi Shang, Ruien Jiang +13
Data-driven scientific discovery requires the iterative integration of scientific domain knowledge, statistical expertise, and an understanding of data semantics to make nuanced an…
HIMap: HybrId Representation Learning for End-to-end Vectorized HD Map Construction
Yi Zhou, Hui Zhang, Jiaqian Yu +4
Vectorized High-Definition (HD) map construction requires predictions of the category and point coordinates of map elements (e.g. road boundary, lane divider, pedestrian crossing,…
Revisiting Evaluation Metrics for Semantic Segmentation: Optimization and Evaluation of Fine-grained Intersection over Union
Zifu Wang, Maxim Berman, Amal Rannen-Triki +6
Semantic segmentation datasets often exhibit two types of imbalance: \textit{class imbalance}, where some classes appear more frequently than others and \textit{size imbalance}, wh…
Yes, IoU loss is submodular - as a function of the mispredictions
Maxim Berman, Matthew B. Blaschko, Amal Rannen Triki +1
This note is a response to [7] in which it is claimed that [13, Proposition 11] is false. We demonstrate here that this assertion in [7] is false, and is based on a misreading of t…
An Efficient Decomposition Framework for Discriminative Segmentation with Supermodular Losses
Jiaqian Yu, Matthew B. Blaschko
Several supermodular losses have been shown to improve the perceptual quality of image segmentation in a discriminative framework such as a structured output support vector machine…
A Convex Surrogate Operator for General Non-Modular Loss Functions
Jiaqian Yu, Matthew Blaschko
Empirical risk minimization frequently employs convex surrogates to underlying discrete loss functions in order to achieve computational tractability during optimization. However,…
The Lovász Hinge: A Novel Convex Surrogate for Submodular Losses
Jiaqian Yu, Matthew Blaschko
Learning with non-modular losses is an important problem when sets of predictions are made simultaneously. The main tools for constructing convex surrogate loss functions for set p…