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Related papers: Linear Encodings of Bounded LTL Model Checking

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In-Context Learning (ICL) is an emergent capability of Large Language Models (LLMs). Only a few demonstrations enable LLMs to be used as blackbox for new tasks. Previous studies have shown that using LLMs' outputs as labels is effective in…

Computation and Language · Computer Science 2024-04-04 Kazuma Hashimoto , Karthik Raman , Michael Bendersky

When adapting Large Language Models for Recommendation (LLMRec), it is crucial to integrate collaborative information. Existing methods achieve this by learning collaborative embeddings in LLMs' latent space from scratch or by mapping from…

Information Retrieval · Computer Science 2024-06-06 Yang Zhang , Keqin Bao , Ming Yan , Wenjie Wang , Fuli Feng , Xiangnan He

Behavior Trees (BTs) provide designers an intuitive graphical interface to construct long-horizon plans for autonomous systems. To ensure their correctness and safety, rigorous formal models and verification techniques are essential.…

Robotics · Computer Science 2026-04-15 Ryan Matheu , John S. Baras , Calin Belta

Large language models (LLMs) frequently generate factually incorrect or unsupported content, commonly referred to as hallucinations. Prior work has explored decoding strategies, retrieval augmentation, and supervised fine-tuning for…

Machine Learning · Computer Science 2026-01-22 Bodla Krishna Vamshi , Rohan Bhatnagar , Haizhao Yang

We present a sample-based Learning Model Predictive Controller (LMPC) for constrained uncertain linear systems subject to bounded additive disturbances. The proposed controller builds on earlier work on LMPC for deterministic systems.…

Systems and Control · Computer Science 2021-01-22 Ugo Rosolia , Francesco Borrelli

This paper revisits the classical notion of sampling in the setting of real-time temporal logics for the modeling and analysis of systems. The relationship between the satisfiability of Metric Temporal Logic (MTL) formulas over…

Logic in Computer Science · Computer Science 2015-03-13 Carlo A. Furia , Matteo Rossi

Implementations of artificial neural networks (ANNs) might lead to failures, which are hardly predicted in the design phase since ANNs are highly parallel and their parameters are barely interpretable. Here, we develop and evaluate a novel…

Logic in Computer Science · Computer Science 2020-12-22 Luiz Sena , Erickson Alves , Iury Bessa , Eddie Filho , Lucas Cordeiro

Logics and model-checking have been successfully used in the last decades for modeling and verification of various types of hardware (and software) systems. While most languages and techniques emerged in a context of monolithic systems with…

Software Engineering · Computer Science 2016-07-14 Manuel Mazzara

Slot and van Emde Boas' weak invariance thesis states that reasonable machines can simulate each other within a polynomially overhead in time. Is lambda-calculus a reasonable machine? Is there a way to measure the computational complexity…

Programming Languages · Computer Science 2017-01-11 Beniamino Accattoli , Ugo Dal Lago

We present a framework for verifying Memoryful Neural Multi-Agent Systems (MN-MAS) against full Linear Temporal Logic (LTL) specifications. In MN-MAS, agents interact with a non-deterministic, partially observable environment. Examples of…

Logic in Computer Science · Computer Science 2025-03-05 Mehran Hosseini , Alessio Lomuscio , Nicola Paoletti

We propose ControlMLLM++, a novel test-time adaptation framework that injects learnable visual prompts into frozen multimodal large language models (MLLMs) to enable fine-grained region-based visual reasoning without any model retraining or…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Mingrui Wu , Hao Chen , Jiayi Ji , Xiaoshuai Sun , Zhiyuan Liu , Liujuan Cao , Ming-Ming Cheng , Rongrong Ji

Ability to count number of occurrences of events within a specified time interval is very useful in specification of resource bounded real time computation. In this paper, we study an extension of Metric Temporal Logic ($\mathsf{MTL}$) with…

Logic in Computer Science · Computer Science 2015-12-31 Khushraj Madnani , Shankara Narayanan Krishna , Paritosh Pandya

This paper studies Linear Temporal Logic over Finite Traces (LTLf) where proposition letters are replaced with first-order formulas interpreted over arbitrary theories, in the spirit of Satisfiability Modulo Theories. The resulting logic,…

Logic in Computer Science · Computer Science 2022-05-25 Luca Geatti , Alessandro Gianola , Nicola Gigante

Context: Linear temporal logic (LTL) model checking faces a significant challenge known as the state-explosion problem. The on-the-fly method is a solution that constructs and checks the state space simultaneously, avoiding generating all…

Logic in Computer Science · Computer Science 2024-06-13 Shuo Li , Liao Zheng , Ru Yang , Zhijun Ding

Continuous representations of logic formulae allow us to integrate symbolic knowledge into data-driven learning algorithms. If such embeddings are semantically consistent, i.e. if similar specifications are mapped into nearby vectors, they…

Computation and Language · Computer Science 2025-09-17 Sara Candussio , Gaia Saveri , Gabriele Sarti , Luca Bortolussi

We present a logic that extends CTL (Computation Tree Logic) with operators that express synchronization properties. A property is synchronized in a system if it holds in all paths of a certain length. The new logic is obtained by using the…

Logic in Computer Science · Computer Science 2016-05-25 Krishnendu Chatterjee , Laurent Doyen

Linear temporal logic (LTL) is a powerful language for task specification in reinforcement learning, as it allows describing objectives beyond the expressivity of conventional discounted return formulations. Nonetheless, recent works have…

Machine Learning · Computer Science 2025-06-11 Marco Bagatella , Andreas Krause , Georg Martius

In the era of large language models (LLMs), the Chinese Spelling Check (CSC) task has seen various LLM methods developed, yet their performance remains unsatisfactory. In contrast, fine-tuned BERT-based models, relying on high-quality…

Computation and Language · Computer Science 2025-06-10 Ziheng Qiao , Houquan Zhou , Zhenghua Li

This paper presents an efficient suboptimal model predictive control (MPC) algorithm for nonlinear switched systems subject to minimum dwell time constraints (MTC). While MTC are required for most physical systems due to stability, power…

Optimization and Control · Mathematics 2022-02-16 Yutao Chen , Mircea Lazar

Time series data from the Intensive Care Unit (ICU) provides critical information for patient monitoring. While recent advancements in applying Large Language Models (LLMs) to time series modeling (TSM) have shown great promise, their…

Machine Learning · Computer Science 2026-01-27 Feixiang Zheng , Yu Wu , Cecilia Mascolo , Ting Dang
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