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We introduce WAM-Flow, a vision-language-action (VLA) model that casts ego-trajectory planning as discrete flow matching over a structured token space. In contrast to autoregressive decoders, WAM-Flow performs fully parallel, bidirectional…

Robotics · Computer Science 2025-12-17 Yifang Xu , Jiahao Cui , Feipeng Cai , Zhihao Zhu , Hanlin Shang , Shan Luan , Mingwang Xu , Neng Zhang , Yaoyi Li , Jia Cai , Siyu Zhu

ReScript is a strongly typed language that targets JavaScript, as an alternative to gradually typed languages, such as TypeScript. In this paper, we present a sound type system for data-flow analysis for a subset of the ReScript language,…

Logic in Computer Science · Computer Science 2024-11-01 Nicky Ask Lund , Hans Hüttel

Computing precise (fully flow-sensitive and context-sensitive) and exhaustive points-to information is computationally expensive. Many practical tools approximate the points-to information trading precision for efficiency. This has adverse…

Programming Languages · Computer Science 2016-08-08 Pritam M. Gharat , Uday P. Khedker , Alan Mycroft

Understanding how data moves, transforms, and persists, known as data flow, is fundamental to reasoning in procedural tasks. Despite their fluency in natural and programming languages, large language models (LLMs), although increasingly…

Artificial Intelligence · Computer Science 2025-06-02 Vishal Pallagani , Nitin Gupta , John Aydin , Biplav Srivastava

Incorporating pre-collected offline data can substantially improve the sample efficiency of reinforcement learning (RL), but its benefits can break down when the transition dynamics in the offline dataset differ from those encountered…

Machine Learning · Computer Science 2026-01-22 Lingkai Kong , Haichuan Wang , Tonghan Wang , Guojun Xiong , Milind Tambe

Flow matching has recently emerged as a powerful alternative to diffusion models, providing a continuous-time formulation for generative modeling and representation learning. Yet, we show that this framework suffers from a fundamental…

Machine Learning · Computer Science 2025-09-26 Weili Zeng , Yichao Yan

Passage reranking is a critical task in various applications, particularly when dealing with large volumes of documents. Existing neural architectures have limitations in retrieving the most relevant passage for a given question because the…

Computation and Language · Computer Science 2024-03-22 Hongyin Zhu

We consider flow rounding: finding an integral flow from a fractional flow. Costed flow rounding asks that we find an integral flow with no worse cost. Randomized flow rounding requires we randomly find an integral flow such that the…

Data Structures and Algorithms · Computer Science 2015-07-30 Donggu Kang , James Payor

Optical flow is inherently a 2D search problem, and thus the computational complexity grows quadratically with respect to the search window, making large displacements matching infeasible for high-resolution images. In this paper, we take…

Computer Vision and Pattern Recognition · Computer Science 2021-08-31 Haofei Xu , Jiaolong Yang , Jianfei Cai , Juyong Zhang , Xin Tong

Asynchrony has become an inherent element of JavaScript, as an effort to improve the scalability and performance of modern web applications. To this end, JavaScript provides programmers with a wide range of constructs and features for…

Programming Languages · Computer Science 2019-01-14 Thodoris Sotiropoulos , Benjamin Livshits

We give an exact characterization of the computational complexity of the $k$CFA hierarchy. For any $k > 0$, we prove that the control flow decision problem is complete for deterministic exponential time. This theorem validates empirical…

Programming Languages · Computer Science 2013-11-25 David Van Horn , Harry G. Mairson

Most existing methods in vision-language retrieval match two modalities by either comparing their global feature vectors which misses sufficient information and lacks interpretability, detecting objects in images or videos and aligning the…

Computer Vision and Pattern Recognition · Computer Science 2022-10-04 Xiaohan Zou , Changqiao Wu , Lele Cheng , Zhongyuan Wang

Statically reasoning in the presence of and about exceptions is challenging: exceptions worsen the well-known mutual recursion between data-flow and control-flow analysis. The recent development of pushdown control-flow analysis for the…

Programming Languages · Computer Science 2013-02-13 Shuying Liang , Matthew Might , Thomas Gilray , David Van Horn

High-dimensional count data arise in applications such as single-cell RNA sequencing and neural spike trains, where mapping between distributions across successive batches or time points form critical components of data analysis. The recent…

Machine Learning · Statistics 2026-05-11 Ganchao Wei , John Pearson

In the static analysis of functional programs, pushdown flow analysis and abstract garbage collection skirt just inside the boundaries of soundness and decidability. Alone, each method reduces analysis times and boosts precision by orders…

Programming Languages · Computer Science 2012-07-10 Christopher Earl , Ilya Sergey , Matthew Might , David Van Horn

Conditional flow matching (CFM) stands out as an efficient, simulation-free approach for training flow-based generative models, achieving remarkable performance for data generation. However, CFM is insufficient to ensure accuracy in…

Machine Learning · Computer Science 2026-02-03 Yuhao Huang , Taos Transue , Shih-Hsin Wang , William Feldman , Hong Zhang , Bao Wang

Combining local exceptions and first class continuations leads to programs with complex control flow, as well as the possibility of expressing powerful constructs such as resumable exceptions. We describe and compare games models for a…

Logic in Computer Science · Computer Science 2013-09-06 James Laird

Nondeterminism in scheduling is the cardinal reason for difficulty in proving correctness of concurrent programs. A powerful proof strategy was recently proposed [6] to show the correctness of such programs. The approach captured data-flow…

Programming Languages · Computer Science 2016-04-29 Chinmay Narayan , Subodh Sharma , Shibashis Guha , S. Arun-Kumar

We introduce DeCaFlow, a deconfounding causal generative model. Training once per dataset using just observational data and the underlying causal graph, DeCaFlow enables accurate causal inference on continuous variables under the presence…

Machine Learning · Computer Science 2025-10-27 Alejandro Almodóvar , Adrián Javaloy , Juan Parras , Santiago Zazo , Isabel Valera

Driving planning is a critical component of end-to-end (E2E) autonomous driving. However, prevailing Imitative E2E Planners often suffer from multimodal trajectory mode collapse, failing to produce diverse trajectory proposals. Meanwhile,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Lin Liu , Caiyan Jia , Guanyi Yu , Ziying Song , JunQiao Li , Feiyang Jia , Peiliang Wu , Xiaoshuai Hao , Yadan Luo