Temporal Logic

Latest papers

19 papers4 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Neurosymbolic Learning of Interpretable World Models
Oct 14, 2026Riccardo Andreoni, Massimiliano Ronzani, Chiara Ghidini +2Temporal Logic World Model Learning
Fondazione Bruno Kessler · Free University of Bozen-Bolzano · Vrije Universiteit Amsterdam
TL;QR: Querying Temporal Discursive Patterns in Textual Corpora
Oct 11, 2026François Hublet, Vladimir Krsmanovic, Jesus Solano +2Temporal Logic Temporal IR
ETH Zürich · CISPA Helmholtz Center for Information Security · IST Austria
Explainable Rule Mining of IPv6 Extension-Header Presence Patterns from Paired-Vantage Captures
Oct 6, 2026Priyanka Sinha, Nikolaos Kekatos, Stylianos Basagiannis +5Temporal Reasoning Temporal Logic
IIT Kharagpur, India · Clone Systems, CY · IHU, GR +1
Differentiable Ternary Temporal Logic Semantics with Polynomial Surrogate Networks
Oct 3, 2026Ryan Matheu, Sai Sandeep Damera, John S. Baras +1Temporal Logic Differentiable Logic
Institute for Systems Research, University of Maryland, College Park, USA
A Geometric Decision Procedure for STL Feasibility and Repair
Sep 19, 2026Avinash MalikReachability Analysis Signal Temporal Logic
Department of Electrical, Computer, and Software Engineering, University of Auckland, Auckland, New Zealand
Backward through Time, Algebraically
Aug 17, 2026Konstantinos KogkalidisDifferentiable Logic Temporal Logic
Infinite Trace Objectives with Finite Trace Techniques: Translating LTL to LTLf+
Aug 3, 2026Christoph Weinhuber, Maximilian Prokop, Giuseppe De Giacomo +1Temporal Reasoning Formal Verification
University of Oxford · 2Technical University of Munich · 3Masaryk University Brno +1
Learning Linear Temporal Specifications from Demonstrations with Uncertainty
Jul 12, 2026Parastou Fahim, Constantino Lagoa, Rômulo Meira-G'oesFormal Verification Learning from Demonstration
School of Electrical Engineering and Computer Science at The Pennsylvania State University, State College, USA
Incentivizing Vision Language Models to Search for Long Video Question Answering
Jul 3, 2026Harsh Goel, S P Sharan, Sahil Shah +4Tool Use in VLMs Temporal Logic
The University of Texas at Austin, Austin, TX, USA
First-Order Temporal Logic Tensor Networks
Jun 29, 2026Luca Boscarato, Ivan Donadello, Alessandro Artale +2Tensor Networks Logic Tensor Networks
Free University of Bozen-Bolzano
An Algebraic Framework for Quantitative Semantics of Spatio-Temporal Logic with Graph Operators
Jun 25, 2026Sheryl Paul, Vidisha Kudalkar, Anand Balakrishnan +3Signal Temporal Logic Multi-Agent Systems
University of Southern California, Los Angeles, CA, USA · University of Texas at Austin, Austin, TX, USA · ETH Zürich, Zürich, Switzerland
TLG: Temporal-Logic Grounding for Video Question Answering via Source-Annotation Reconstruction and Category-Targeted Reasoning
Jun 1, 2026Ali AlaviTemporal Video Grounding Logical Reasoning
The Ohio State University
Temporal Evidence Routing with Structured Visual Evidence for TimeLogicQA
May 31, 2026Yuyang Sun, Yongliang Wu, Xingyu Zhu +8Video QA Structured Reasoning
Southeast University · National University of Singapore · Independent Researcher +2
Value Functions for Temporal Logic: Optimal Policies and Safety Filters
May 1, 2026Oswin So, William Sharpless, Sylvia Herbert +1Sequential Decision Making Safe RL
Massachusetts Institute of Technology, Cambridge, MA 02139, USA · University of California, San Diego, CA 92093, USA
Logic of Fuzzy Paths
Apr 27, 2026Kush Grover, Pratham Gupta, Jan KřetínskýTemporal Reasoning Signal Temporal Logic
Fondazione Bruno Kessler · Indian Institute of Science · Masaryk University
Logic-Based Verification of Task Allocation for LLM-Enabled Multi-Agent Manufacturing Systems
Apr 18, 2026Jonghan Lim, Mostafa Tavakkoli Anbarani, Rômulo Meira-Góes +1Multi-Agent Control Formal Verification
Department of Industrial and Manufacturing Engineering, Pennsylvania State University, State College, USA · Department of Mechanical Engineering, Pennsylvania State University, State College, USA · Department of Electrical Engineering, Pennsylvania State University, State College, USA
Vibe-Coding: Feedback-Based Automated Verification with no Human Code Inspection, a Feasibility Study
Apr 16, 2026Michal Töpfer, František Plášil, Tomáš Bureš +1LLM Self-Correction Formal Verification
Charles University Prague, Czech Republic
Applications of Intuitionistic Temporal Logic to Temporal Answer Set Programming
Mar 16, 2026Pedro Cabalar, Martín Diéguez, David Fernández-Duque +3Answer Set Programming Temporal Reasoning
University of Corunna, Spain · University of Angers, France · University of Barcelona, Spain +2
Feedback-based Automated Verification in Vibe Coding of CAS Adaptation Built on Constraint Logic
Feb 20, 2026Michal Töpfer, František Plášil, Tomáš Bureš +1Temporal Logic LLM-Based Program Synthesis
Charles University, Czech Republic

Oct 14, 2026J/K move · Enter open · S save

Neurosymbolic Learning of Interpretable World Models

Riccardo Andreoni, Massimiliano Ronzani, Chiara Ghidini, Alessandro Daniele+1

Fondazione Bruno Kessler · Free University of Bozen-Bolzano · Vrije Universiteit Amsterdam

Temporal Logic World Model Learning World Models World Model-Based Planning Neurosymbolic Learning Neuro-Symbolic Planning

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World models aim to learn compact representations of an environment from observations, enabling agents to predict future states and plan their behaviour. However, most existing approaches learn black-box representations, with limited ability to incorporate prior knowledge about the world. We introduce Concept-Grounded World Models (CGWMs), a neurosymbolic world model design that instead learns interpretable concept representations. We learn these concepts from observations using explicit and complete knowledge, expressed in temporal logic, that specifies the valid world states and the temporal relations governing their dynamics. Furthermore, we directly use this knowledge by formulating planning as differentiable reasoning, optimising the agent's actions by gradient ascent to satisfy a goal. We experimentally compare CGWM with a purely neural baseline and a neurosymbolic baseline on two game environments. We find that CGWMs ground concepts much more accurately, even over long horizons, resulting in significantly more robust planning both in and out of distribution.