42 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Meta (United States)US9 papers
- University of GroningenNL3 papers
- Case Western Reserve UniversityUS2 papers
- Google (United States)US2 papers
- Snap (United States)US2 papers
- University of Southern CaliforniaUS2 papers
- Bellevue Hospital CenterUS1 paper
- California Southern UniversityUS1 paper
- Centre de Recherche en Économie et StatistiqueFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- Dokkyo Medical UniversityJP1 paper
- ENSAE ParisFR1 paper
14 papers
LO-FAR: A Cost-Aware Local Filter for Sparse Feature Ranking in Industrial Ad Recommendation
Egemen Erbayat, Luis Duque, Sohini Roychowdhury +2
Industrial ad recommendation models rely heavily on sparse, high-cardinality ID-list features that encode user histories and contextual identifiers. Each is backed by a dedicated e…
Morphology-Specific Closed-Loop Control of Logarithmic-Spiral Continuum Arms via Online Jacobian Error Compensation
Partha Datta, Yi Jin, Wei Lin +1
Logarithmic spirals are ubiquitous in biological appendages and provide an attractive morphology for continuum manipulators capable of reaching, wrapping, and grasping. Recently re…
A General Framework for Multimodal LLM-Based Multimedia Understanding in Large-Scale Recommendation Systems
Yiming Zhu, Xu Liu, Ziyun Xu +9
Conventional recommendation systems frequently fail to fully exploit the high-dimensional semantic signals inherent in multimedia content, thereby limiting the fidelity of user pre…
Design, Locomotion, and Control of Amphibious Robots: Recent Advances
Yi Jin, Chang Liu, Roger D. Quinn +2
Amphibious robots, operating seamlessly across land and water, are advancing applications in conservation, disaster response, and defense. Their performance depends on locomotion m…
Optimizing Recall or Relevance? A Multi-Task Multi-Head Approach for Item-to-Item Retrieval in Recommendation
Jiang Zhang, Sumit Kumar, Wei Chang +7
The task of item-to-item (I2I) retrieval is to identify a set of relevant and highly engaging items based on a given trigger item. It is a crucial component in modern recommendatio…
Exact-WKB Analysis of Two-level Floquet Systems
Toshiaki Fujimori, Syo Kamata, Tatsuhiro Misumi +2
We explore the application of the exact Wentzel-Kramers-Brillouin (WKB) analysis to two-level Floquet systems and establish a systematic procedure to calculate the quasi-energy and…
Global Inequalities in the Production of Artificial Intelligence: A Four-Country Study on Data Work
Antonio A. Casilli, Paola Tubaro, Maxime Cornet +3
Labor plays a major, albeit largely unrecognized role in the development of artificial intelligence. Machine learning algorithms are predicated on data-intensive processes that rel…
Designing an AI-Powered Mentorship Platform for Professional Development: Opportunities and Challenges
Rahul Bagai, Vaishali Mane
This article examines the promising prospects and potential hurdles associated with the development of MentorAI, a conceptual AI-driven mentorship platform for professional growth…
User Welfare Optimization in Recommender Systems with Competing Content Creators
Fan Yao, Yiming Liao, Mingzhe Wu +6
Driven by the new economic opportunities created by the creator economy, an increasing number of content creators rely on and compete for revenue generated from online content reco…
Bitrate Ladder Construction using Visual Information Fidelity
Krishna Srikar Durbha, Hassene Tmar, Cosmin Stejerean +2
Recently proposed perceptually optimized per-title video encoding methods provide better BD-rate savings than fixed bitrate-ladder approaches that have been employed in the past. H…
Active Learning for Non-Parametric Choice Models
Fransisca Susan, Negin Golrezaei, Ehsan Emamjomeh-Zadeh +1
We study the problem of actively learning a non-parametric choice model based on consumers' decisions. We present a negative result showing that such choice models may not be ident…
Mining Code Review Data to Understand Waiting Times Between Acceptance and Merging: An Empirical Analysis
Gunnar Kudrjavets, Aditya Kumar, Nachiappan Nagappan +1
Increasing code velocity (or the speed with which code changes are reviewed and merged) is integral to speeding up development and contributes to the work satisfaction of engineers…
Do Small Code Changes Merge Faster? A Multi-Language Empirical Investigation
Gunnar Kudrjavets, Nachiappan Nagappan, Ayushi Rastogi
Code velocity, or the speed with which code changes are integrated into a production environment, plays a crucial role in Continuous Integration and Continuous Deployment. Many stu…
Quantifying Daily Evolution of Mobile Software Based on Memory Allocator Churn
Gunnar Kudrjavets, Jeff Thomas, Aditya Kumar +2
The pace and volume of code churn necessary to evolve modern software systems present challenges for analyzing the performance impact of any set of code changes. Traditional method…