Dive into the cutting-edge world of information retrieval theory with this comprehensive conference recording from Washington D.C. Explore 26 original research papers and a keynote presentation by Google DeepMind's Minmin Chen on exploration measurements and systems. Gain insights into topics such as temporal changes in IR test collections, query performance measures for dense retrieval, hierarchical navigable small worlds, and experimental consistency. Discover advancements in learning to rank models, document manipulations, adaptive knowledge distillation, and cross-lingual math information retrieval. Delve into personalized recommendations, harmful content detection, search result explanations, and the application of large language models for serendipitous recommendations. Examine innovative approaches in sponsored question answering, automatic rubric-based evaluation, and quantum annealing for transformer fine-tuning. Conclude with discussions on social media conflict classification and biased interactions in whole-session search on debated topics.
Theory of Information Retrieval - ACM ICTIR 2024 Conference Presentations
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
- Conference Opening Session
- Keynote by Minmin Chen: Exploration: Measurements and Systems
- First Paper Session
- Evaluation of Temporal Change in IR Test Collections - Jüri Keller
- Coherence-based Query Performance Measures for Dense Retrieval -Maria Vlachou
- The Impacts of Data, Ordering, and Intrinsic Dimensionality on Recall in Hierarchical Navigable Small Worlds - Owen Pendrigh Elliott
- Query Variability and Experimental Consistency: A Concerning Case Study - Alistair Moffat
- Normalised Precision at Fixed Recall for Evaluating TAR - Moritz Staudinger
- Second Paper Session
- Distillation vs. Sampling for Efficient Training of Learning to Rank Models - Pooya Khandel
- Ranking-Incentivized Document Manipulations for Multiple Queries - Haya Nachimovsky
- Learning to Rank for Non Independent and Identically Distributed Datasets - Jacopo Cecchetti
- On Adaptive Knowledge Distillation with Generalized KL-Divergence Loss for Ranking Model Refinement - Yingrui Yang
- Scalable Range Search over Temporal and Numerical Expressions - Dhruv Gupta
- CrossMath: Towards Cross-lingual Math Information Retrieval - Behrooz Mansouri
- Personalized Beyond-accuracy Calibration in Recommendation - Mohammadmehdi Naghiaei
- Target Span Detection for Implicit Harmful Content - Nazanin Jafari
- Towards Group-aware Search Success - Haolun Wu
- Which Neurons Matter in IR? Applying Integrated Gradients-based Methods to Understand Cross-Encoders - Mathias Vast
- CFE2: Counterfactual Editing for Search Result Explanation - Zhichao Xu
- Third Paper Session
- The Art of Asking: Prompting Large Language Models for Serendipity Recommendations - Zhe Fu
- Sponsored Question Answering - Tommy Mordo
- Pencils Down! Automatic Rubric-based Evaluation of Retrieve/Generate Systems - Naghmeh Farzi
- Towards a Formal Characterization of User Simulation Objectives in Conversational Information Access - Nolwenn Bernard
- Retrieval Augmented Zero-Shot Text Classification - Tassallah Abdullahi
- A Quantum Annealing Instance Selection Approach for Efficient and Effective Transformer Fine-Tuning - Andrea Pasin
- Capturing the Spectrum of Social Media Conflict: A Novel Multi-objective Classification Model - Oliver Warke
- Cognitively Biased Users Interacting with Algorithmically Biased Results in Whole-Session Search on Debated Topics - Ben Wang
- Online Paper Session
- Pb-Hash: Partitioned b-bit Hashing - Ping Li
- An Analysis of Stopping Strategies in Conversational Search Systems - Xiao Fu
- Conference Closing Session
Taught by
Association for Computing Machinery (ACM)
