CORE Recommender
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction
Announce Type: replace Abstract: Click-Through Rate (CTR) prediction, a core task in recommendation systems, estimates user click likelihood using historical behavioral data. Modeling user behavior sequences as text to leverage Language Models (LMs) for this task has gained traction, owing to LMs' strong semantic understanding and contextual modeling capabilities. However, a critical structural gap exists: user behavior sequences consist of discrete actions connected by semantically empty...
CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction
arXiv:2508.03668v2 Announce Type: replace Abstract: Click-Through Rate (CTR) prediction, a core task in recommendation systems, estimates user click likelihood using historical behavioral data. Modeling user behavior sequences as text to leverage Language Models (LMs) for this task has gained traction, owing to LMs' strong semantic understanding and contextual modeling capabilities. However, a critical structural gap exists: user behavior sequences consist of discrete actions connected by...
Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors
Computer Science > Machine Learning [Submitted on 31 May 2026] Title:Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors View PDF HTML (experimental)Abstract:We ask: when do Bayesian model averaging (BMA) weights over decision trees carry sufficient epistemic information to justify committed exploitation of the averaging distribution?
Do Transformers Need Three Projections? Systematic Study of QKV Variants
Computer Science > Machine Learning [Submitted on 1 Jun 2026] Title:Do Transformers Need Three Projections? Systematic Study of QKV Variants View PDF HTML (experimental)Abstract:Transformers have become the standard solution for various AI tasks, with the query, key, and value (QKV) attention formulation playing a central role.
Can LLMs Beat Classical Hyperparameter Optimization Algorithms?
Computer Science > Machine Learning [Submitted on 25 Mar 2026 (v1), last revised 17 Apr 2026 (this version, v5)] Title:Can LLMs Beat Classical Hyperparameter Optimization Algorithms?
Generative Models and Statistical Validation
High Energy Physics - Phenomenology [Submitted on 28 May 2026] Title:Generative Models and Statistical Validation View PDF HTML (experimental)Abstract:Generative machine learning has become an essential tool in theoretical and experimental physics, especially in the context of fast surrogates and density estimators. In this work, we first introduce the underlying framework of modern generative networks and then discuss challenges in quantifying their accuracy, precision, and statistical power.
Using Optical Aberrations to Distinguish Real Astronomical Transients
Astrophysics > Instrumentation and Methods for Astrophysics [Submitted on 6 Jun 2026] Title:Fast Astronomical Transients in Archival Photographic Plates: Using optical aberrations as a tool for discerning real images, from plate artifacts View PDF HTML (experimental)Abstract:The detection of fast astronomical transients in photographic plates from the Palomar sky surveys conducted in the 1950s, was subject to the criticism that such transients could be just the effect of otherwise...
Generative Models and Statistical Validation
High Energy Physics - Phenomenology [Submitted on 28 May 2026] Title:Generative Models and Statistical Validation View PDF HTML (experimental)Abstract:Generative machine learning has become an essential tool in theoretical and experimental physics, especially in the context of fast surrogates and density estimators. In this work, we first introduce the underlying framework of modern generative networks and then discuss challenges in quantifying their accuracy, precision, and statistical power.
Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors
Computer Science > Machine Learning [Submitted on 31 May 2026 (v1), last revised 2 Jun 2026 (this version, v2)] Title:Sample Complexity and Decision-Theoretic Guarantees for Bayesian Model Averaging over Decision Trees with Catalan-Exponential Priors View PDF HTML (experimental)Abstract:We ask: when do Bayesian model averaging (BMA) weights over decision trees carry sufficient epistemic information to justify committed exploitation of the averaging distribution?
Trees to Flows and Back: Unifying Decision Trees and Diffusion Models
Computer Science > Machine Learning [Submitted on 1 May 2026 (v1), last revised 21 May 2026 (this version, v2)] Title:Trees to Flows and Back: Unifying Decision Trees and Diffusion Models View PDFAbstract:Decision trees and diffusion models are ostensibly disparate model classes, one discrete and hierarchical, the other continuous and dynamic. This work unifies the two by establishing a crisp mathematical correspondence between hierarchical decision trees and diffusion processes in...