Tootfinder

Atomically thin silver films for enhanced nanoscale nonlinear optics
Philipp K. Jenke, Saad Abdullah, Andrew P. Weber, \'Alvaro Rodr\'iguez Echarri, Fadil Iyikanat, Vahagn Mkhitaryan, Frederik Schiller, J. Enrique Ortega, Philip Walther, F. Javier Garc\'ia de Abajo, Lee A. Rozema
https://arxiv.org/abs/2508.15417

Atomically thin silver films for enhanced nanoscale nonlinear optics
The inherently weak nonlinear optical response of bulk materials remains a fundamental limitation in advancing photonic technologies. Nanophotonics addresses this challenge by tailoring the size and morphology of nanostructures to manipulate the optical near field, thus modulating the nonlinear response. Here, we explore a complementary strategy based on engineering the electronic band structure in the mesoscopic regime to enhance optical nonlinearities. Specifically, we demonstrate an increase…

Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Making
Liuxin Bao, Zhihao Peng, Xiaofei Zhou, Runmin Cong, Jiyong Zhang, Yixuan Yuan
https://arxiv.org/abs/2508.13754

Expertise-aware Multi-LLM Recruitment and Collaboration for Medical Decision-Making
Medical Decision-Making (MDM) is a complex process requiring substantial domain-specific expertise to effectively synthesize heterogeneous and complicated clinical information. While recent advancements in Large Language Models (LLMs) show promise in supporting MDM, single-LLM approaches are limited by their parametric knowledge constraints and static training corpora, failing to robustly integrate the clinical information. To address this challenge, we propose the Expertise-aware Multi-LLM Rec…

Call Option Price using Pearson Diffusion Processes
Tapan Kar, Suprio Bhar, Barun Sarkar, Sesha Meka
https://arxiv.org/abs/2508.14577 https://arxiv.org/pdf…

Call Option Price using Pearson Diffusion Processes
Following the foundational work of the Black--Scholes model, extensive research has been developed to price the option by addressing its underlying assumptions and associated pricing biases. This study introduces a novel framework for pricing European call options by modeling the underlying asset's return dynamics using Pearson diffusion processes, characterized by a linear drift and a quadratic squared diffusion coefficient. This class of diffusion processes offers a key advantage in its abili…

In the latest act of retributIion targeting public servants in the federal government’s intelligence community
— the Trump administration moved Tuesday to revoke the security clearances of 37 current and former national security officials
A memo posted online by Tulsi Gabbard, the director of national intelligence,
accuses the targeted officials of having engaged in the “politicization or weaponization of intelligence” to advance partisan goals,
as well as failure to …

Trump administration revokes security clearances of 37 current and former government officials
The Trump administration says it's revoking the security clearances of 37 current and former national security officials. It's the latest act of retribution targeting public servants in the federal government’s intelligence community. A memo posted Tuesday by Director of National Intelligence Tulsi Gabbard accuses the targeted officials of having engaged in the “politicization or weaponization of intelligence” to advance partisan goals. It also accuses them of failing to safeguard classif…

Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning
Ankan Deria, Adinath Madhavrao Dukre, Feilong Tang, Sara Atito, Sudipta Roy, Muhammad Awais, Muhammad Haris Khan, Imran Razzak
https://arxiv.org/abs/2506.15649

Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning
Despite significant advances in inference-time search for vision-language models (VLMs), existing approaches remain both computationally expensive and prone to unpenalized, low-confidence generations which often lead to persistent hallucinations. We introduce \textbf{Value-guided Inference with Margin-based Reward (ViMaR)}, a two-stage inference framework that improves both efficiency and output fidelity by combining a temporal-difference value model with a margin-aware reward adjustment. In th…

⏱️ Researchers discover how the human brain organizes its visual memories through precise neural timing
https://medicalxpress.com/news/2025-07-human-brain-visual-memories-precise.html

Researchers discover how the human brain organizes its visual memories through precise neural timing
Researchers at the University of Southern California have made a significant breakthrough in understanding how the human brain forms, stores and recalls visual memories. A new study, published in Advanced Science, harnesses human patient brain recordings and a powerful machine learning model to shed new light on the brain's internal code that sorts memories of objects into categories—think of it as the brain's filing cabinet of imagery.

Happening right now in Gaza: Israel’s occupation force is expanding its ground offensive.
(Screenshot posted from private chat with permission.)
@…
#israel #genocide

Room-Temperature Surface Exciton Polaritons in Colloidal J-Aggregate Flakes
Carla Est\'evez-Varela, Jos\'e Nuno Gama, Miguel Castillo, Adelaide Miranda, Pieter De Beule, Jorge P\'erez-Juste, Martin Lopez-Garcia, Isabel Pastoriza-Santos, Sara N\'u\~nez-S\'anchez
https://arxiv.org/abs/2507.13784

Room-Temperature Surface Exciton Polaritons in Colloidal J-Aggregate Flakes
J-aggregates are promising organic materials for nanophotonic applications due to their excitonic properties and ability to support surface exciton polaritons at room temperature, providing a robust platform for nanoscale light manipulation. While thin films composed of J-aggregates have demonstrated these advantages, colloidal J-aggregate nanoparticles remain underexplored. Herein, we report the synthesis of colloidal J-aggregate flakes by electrostatic interaction of cyanine molecules (TDBC) …

A Survey of Reinforcement Learning for Software Engineering
Dong Wang, Hanmo You, Lingwei Zhu, Kaiwei Lin, Zheng Chen, Chen Yang, Junji Yu, Zan Wang, Junjie Chen
https://arxiv.org/abs/2507.12483

A Survey of Reinforcement Learning for Software Engineering
Reinforcement Learning (RL) has emerged as a powerful paradigm for sequential decision-making and has attracted growing interest across various domains, particularly following the advent of Deep Reinforcement Learning (DRL) in 2015. Simultaneously, the rapid advancement of Large Language Models (LLMs) has further fueled interest in integrating RL with LLMs to enable more adaptive and intelligent systems. In the field of software engineering (SE), the increasing complexity of systems and the ris…

ImpReSS: Implicit Recommender System for Support Conversations
Omri Haller, Yair Meidan, Dudu Mimran, Yuval Elovici, Asaf Shabtai
https://arxiv.org/abs/2506.14231

ImpReSS: Implicit Recommender System for Support Conversations
Following recent advancements in large language models (LLMs), LLM-based chatbots have transformed customer support by automating interactions and providing consistent, scalable service. While LLM-based conversational recommender systems (CRSs) have attracted attention for their ability to enhance the quality of recommendations, limited research has addressed the implicit integration of recommendations within customer support interactions. In this work, we introduce ImpReSS, an implicit recomme…