WWW 2026 Tutorial
📅 April 13, 2026 | 📍 Dubai, UAE
This tutorial provides a comprehensive introduction to Temporal Information Retrieval (TIR) and Temporal Question Answering (TQA) in the context of modern Large Language Models (LLMs). As information on the Web continuously evolves, understanding temporal dynamics in retrieval and QA systems is crucial for building effective AI applications.
Visit our complete tutorial website: https://datascienceuibk.github.io/temporal-ir-qa-tutorial-www2026/
- Fundamentals of Temporal Information Retrieval (TIR)
- Temporal Question Answering (TQA) systems and architectures
- Evolution from rule-based to probabilistic approaches
- Modern transformer and LLM architectures for temporal reasoning
- Temporal modeling and Retrieval-Augmented Generation (RAG)
- Temporal reasoning over evolving knowledge
- Recent advances and benchmarks in temporal IR/QA
- Open challenges and future research directions
University of Innsbruck, Austria
PhD Researcher in Data Science, specializing in temporal information retrieval and question answering.
Delft University of Technology, Netherlands
Associate Professor, expert in Retrieval-Augmented AI systems and temporal IR with over a decade of experience.
University of Innsbruck, Austria
Professor and Deputy Head of the Digital Science Center, with 300+ publications in temporal IR and NLP.
Duration: Half-day tutorial (3 hours including breaks)
- Introduction and Motivation
- Core Concepts and Temporal IR Tasks
- Foundations: Pre-LLM Temporal IR Models
- Neural and Transformer-based Temporal Models
- Quick Q&A
- ☕ Coffee Break
- Temporal RAG and Reasoning
- Temporal Web and Evaluation Ecosystem
- Emerging Topics and Open Challenges
- Concluding Discussion and Q&A
- Survey Paper: It's High Time: A Survey of Temporal Question Answering
- Video Teaser: Watch on YouTube
- Related Research: TemporalQA-Survey Repository
All tutorial materials including slides, code examples, and additional resources will be made available on the tutorial website before and after the tutorial.
This tutorial is designed for:
- Researchers in information retrieval and natural language processing
- PhD students working on temporal reasoning and QA systems
- Practitioners building LLM-based applications
- Anyone interested in time-aware information access
Prerequisites: Basic knowledge of NLP and machine learning concepts.
For questions or inquiries about this tutorial, please contact:
- 📧 Bhawna Piryani: bhawna.piryani@uibk.ac.at
- 📧 Avishek Anand: avishek.anand@tudelft.nl
- 📧 Adam Jatowt: adam.jatowt@uibk.ac.at
If you find this tutorial useful, please cite our survey paper:
@article{piryani2025temporal,
title={It's High Time: A Survey of Temporal Question Answering},
author={Piryani, Bhawna and Abdallah, Abdelrahman and Mozafari, Jamshid and Anand, Avishek and Jatowt, Adam},
journal={arXiv preprint arXiv:2505.20243},
year={2025}
}Conference: The Web Conference 2026 (WWW 2026)
Location: Dubai, UAE
Date: April 13, 2026