Dive into the cutting-edge world of information retrieval at this 4-hour conference recording from Washington D.C. Explore 26 original research papers covering theoretical aspects of IR, including evaluation methods, query performance, learning to rank, and more. Gain insights from Google DeepMind's Minmin Chen in the keynote on exploration measurements and systems. Discover advancements in areas like temporal IR, dense retrieval, hierarchical navigable small worlds, and conversational search. Learn about novel approaches in cross-lingual math retrieval, personalized recommendations, harmful content detection, and quantum annealing for transformer fine-tuning. Engage with discussions on user simulation, social media conflict classification, and the interplay between cognitive and algorithmic biases in search.
ACM ICTIR 2024 - Theoretical Aspects of Information Retrieval
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)
