Tootfinder

Hierarchical Group-wise Ranking Framework for Recommendation Models
YaChen Yan, Liubo Li, Ravi Choudhary
https://arxiv.org/abs/2506.12756 https://

Hierarchical Group-wise Ranking Framework for Recommendation Models
In modern recommender systems, CTR/CVR models are increasingly trained with ranking objectives to improve item ranking quality. While this shift aligns training more closely with serving goals, most existing methods rely on in-batch negative sampling, which predominantly surfaces easy negatives. This limits the model's ability to capture fine-grained user preferences and weakens overall ranking performance. To address this, we propose a Hierarchical Group-wise Ranking Framework with two key com…

Supernova Event Dataset: Interpreting Large Language Model's Personality through Critical Event Analysis
Pranav Agarwal, Ioana Ciuc\u{a}
https://arxiv.org/abs/2506.12189

Supernova Event Dataset: Interpreting Large Language Model's Personality through Critical Event Analysis
Large Language Models (LLMs) are increasingly integrated into everyday applications. As their influence grows, understanding their decision making and underlying personality becomes essential. In this work, we interpret model personality using our proposed Supernova Event Dataset, a novel dataset with diverse articles spanning biographies, historical events, news, and scientific discoveries. We use this dataset to benchmark LLMs on extracting and ranking key events from text, a subjective and c…

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework
Dahang Wan, Rongsheng Lu, Yang Fang, Xianli Lang, Shuangbao Shu, Jingjing Chen, Siyuan Shen, Ting Xu, Zecong Ye
https://arxiv.org/abs/2506.14696

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework
Multispectral object detection, which integrates information from multiple bands, can enhance detection accuracy and environmental adaptability, holding great application potential across various fields. Although existing methods have made progress in cross-modal interaction, low-light conditions, and model lightweight, there are still challenges like the lack of a unified single-stage framework, difficulty in balancing performance and fusion strategy, and unreasonable modality weight allocatio…

A model of heat transfer from a cylinder in high-speed slip flow and determination of temperature jump coefficients using hot-wires
Diogo C. Barros, Lionel Larchev\^eque, Pierre Dupont
https://arxiv.org/abs/2506.14000

A model of heat transfer from a cylinder in high-speed slip flow and determination of temperature jump coefficients using hot-wires
In small-scale, low-density or high-speed flows, the mean free path of the gas and its molecular interaction with a solid interface are key properties for the analysis of heat transfer mechanisms occurring in many flow processes ranging from micro-scale to aerospace applications. Here, we specifically examine the effects of temperature jump at the gas-solid interface on the convection from a cylinder in the high-speed slip flow regime. By employing the classical Smoluchowski temperature jump co…

Particle Spectra in the Integrated HydroKinetic Model at RHIC BES Energies
Narendra Rathod, Yuri Sinyukov, Musfer Adzhymambetov, Hanna Zbroszczyk
https://arxiv.org/abs/2506.13944 …

Particle Spectra in the Integrated HydroKinetic Model at RHIC BES Energies
This paper focuses on the description and prediction of particle production in Au+Au collisions at various center-of-mass energies ($\sqrt{s_{\text{NN}}} = 7.7, 11.5, 14.5, 19.6, 27.0, \text{ and } 39.0$ GeV), using the Integrated HydroKinetic model (iHKM). The iHKM, initially created for the description of ultrarelativistic nucleus-nucleus collisions, has been extended to cover intermediate and low relativistic energies, ranging from 2.5 to 50 GeV per colliding nucleon pair, and in cases where…

MobileHolo: A Lightweight Complex-Valued Deformable CNN for High-Quality Computer-Generated Hologram
Xie Shuyang, Zhou Jie, Xu Bo, Wang Jun, Xu Renjing
https://arxiv.org/abs/2506.14542

MobileHolo: A Lightweight Complex-Valued Deformable CNN for High-Quality Computer-Generated Hologram
Holographic displays have significant potential in virtual reality and augmented reality owing to their ability to provide all the depth cues. Deep learning-based methods play an important role in computer-generated holograms (CGH). During the diffraction process, each pixel exerts an influence on the reconstructed image. However, previous works face challenges in capturing sufficient information to accurately model this process, primarily due to the inadequacy of their effective receptive fiel…

Reimagining Dance: Real-time Music Co-creation between Dancers and AI
Olga Vechtomova, Jeff Bos
https://arxiv.org/abs/2506.12008 https://

Reimagining Dance: Real-time Music Co-creation between Dancers and AI
Dance performance traditionally follows a unidirectional relationship where movement responds to music. While AI has advanced in various creative domains, its application in dance has primarily focused on generating choreography from musical input. We present a system that enables dancers to dynamically shape musical environments through their movements. Our multi-modal architecture creates a coherent musical composition by intelligently combining pre-recorded musical clips in response to dance…

LeanExplore: A search engine for Lean 4 declarations
Justin Asher (Independent Researcher)
https://arxiv.org/abs/2506.11085 https://a…

LeanExplore: A search engine for Lean 4 declarations
The expanding Lean 4 ecosystem poses challenges for navigating its vast libraries. This paper introduces LeanExplore, a search engine for Lean 4 declarations. LeanExplore enables users to semantically search for statements, both formally and informally, across select Lean 4 packages (including Batteries, Init, Lean, Mathlib, PhysLean, and Std). This search capability is powered by a hybrid ranking strategy, integrating scores from a multi-source semantic embedding model (capturing conceptual me…

RMIT-ADM S at the SIGIR 2025 LiveRAG Challenge
Kun Ran, Shuoqi Sun, Khoi Nguyen Dinh Anh, Damiano Spina, Oleg Zendel
https://arxiv.org/abs/2506.14516 https…

RMIT-ADM+S at the SIGIR 2025 LiveRAG Challenge
This paper presents the RMIT--ADM+S participation in the SIGIR 2025 LiveRAG Challenge. Our Generation-Retrieval-Augmented Generation (GRAG) approach relies on generating a hypothetical answer that is used in the retrieval phase, alongside the original question. GRAG also incorporates a pointwise large language model (LLM)-based re-ranking step prior to final answer generation. We describe the system architecture and the rationale behind our design choices. In particular, a systematic evaluation…

Israeli startup Zero Networks, which aims to prevent ransomware and other cyberattacks, raised $55M led by Highland Europe, taking its total funding to $100M (Steven Scheer/Reuters)
https://www.reuters.com/world/middle-east/