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Software development and technology teams in studio environments often need to support a complex matrix of applications, versions and dependencies. Existing management tools are not always up to this task, but offer a variety of battle-tested ideas that ...

This paper explores how Netflix has enhanced its animation production reporting using a dynamic data transformation framework. As collaborations with animation studios around the globe grow, it’s essential to adeptly manage varied reports to ensure ...

Welcome to the The 4th International Workshop on Software Engineering and AI for Data Quality (SEA4DQ 2024), held in Brazil, on 16 July, 2024, co-located with the 32nd ACM International Conference on the Foundations of Software Engineering (FSE 2024). ...

In recent years, the data-driven optimization area has seen a shift in the research focus from static batched data environment to dynamic streaming data environment. However, this field is hindered by the lack of a comprehensive and standardized test ...

Genetic programming (GP) is a popular problem-solving and optimization technique. However, generating effective test cases for training and evaluating GP programs requires strong domain knowledge. Furthermore, GP programs often prematurely converge on ...

With the rapid development of online services and web applications, recommender systems (RS) have become increasingly indispensable for mitigating information overload and matching users’ information needs by providing personalized suggestions over items. ...

The application of contrastive learning (CL) to collaborative filtering (CF) in recommender systems has achieved remarkable success. CL-based recommendation models mainly focus on creating multiple augmented views by employing different graph augmentation ...

In Conversational Recommender Systems (CRSs), conversations usually involve a set of items and item-related entities or attributes, e.g., director is a related entity of a movie. These items and item-related entities are often mentioned along the ...

Large-scale pretrained language models have achieved compelling performance in a wide range of language understanding and information retrieval tasks. While their large scales ensure capacity, they also hinder deployment. Knowledge distillation offers an ...

The iterative character of work in machine learning (ML) and artificial intelligence (AI) and reliance on comparisons against benchmark datasets emphasize the importance of reproducibility in that literature. Yet, resource constraints and inadequate ...

Reproducibility is a fundamental part of scientific progress. Compared to other scientific fields, computational sciences are privileged as experimental setups can be preserved with ease, and regression experiments allow the validation of computational ...

Tables contain a significant portion of the world's structured information. The ability to efficiently and accurately understand, process, reason about, analyze, and generate tabular data is critical for achieving Artificial General Intelligence (AGI) ...

Large language models (LLMs) have significantly influenced recommender systems, spurring interest across academia and industry in leveraging LLMs for recommendation tasks. This includes using LLMs for generative item retrieval and ranking, and developing ...

Understanding how people interact with search interfaces is core to the field of Interactive Information Retrieval (IIR). While various models have been proposed (e.g., Belkin's ASK, Berry picking, Everyday-life information seeking, Information foraging ...

Beyond effectiveness, the robustness of an information retrieval (IR) system is increasingly attracting attention. When deployed, a critical technology such as IR should not only deliver strong performance on average but also have the ability to handle a ...

Generative retrieval (GR) has witnessed significant growth recently in the area of information retrieval. Compared to the traditional "index-retrieve-then-rank'' pipeline, the GR paradigm aims to consolidate all information within a corpus into a single ...

The field of Quantum Computing (QC) has gained significant popularity in recent years, due to its potential to provide benefits in terms of efficiency and effectiveness when employed to solve certain computationally intensive tasks. In both Information ...

High Recall Retrieval (HRR) tasks, including eDiscovery in the law, systematic literature reviews, and sunshine law requests focus on efficiently prioritizing relevant documents for human review.Technology-assisted review (TAR) refers to iterative human-...

Buy It Again (BIA) recommendations are a crucial component in enhancing the customer experience and site engagement for retailers. In this paper, we build a short (S) and long (L) term Hawkes (H) process for each item and use it to obtain BIA ...