Tootfinder

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Hood:
🎵 It's Been a Long Time Since I Was Last Here
#Hood
https://hoodband.bandcamp.com/track/its-been-a-long-time-since-i-was-last-here
https://open.spotify.com/track/7y2JdwNAbNR021s2iZZT1o

Reinforced Language Models for Sequential Decision Making
Jim Dilkes, Vahid Yazdanpanah, Sebastian Stein
https://arxiv.org/abs/2508.10839 https://arxiv.org…

Reinforced Language Models for Sequential Decision Making
Large Language Models (LLMs) show potential as sequential decision-making agents, but their application is often limited due to a reliance on large, computationally expensive models. This creates a need to improve smaller models, yet existing post-training methods are designed for single-turn interactions and cannot handle credit assignment in multi-step agentic tasks. To address this, we introduce Multi-Step Group-Relative Policy Optimization (MS-GRPO), a new algorithm for post-training LLM ag…

Crosslisted article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[3/5]:
- A Co-Training Semi-Supervised Framework Using Faster R-CNN and YOLO Networks for Object Detection...
Hossein Yazdanjouei, Arash Mansouri, Mohammad Shokouhifar

TubeBEND: A Real-World Dataset for Geometry Prediction in Rotary Draw Bending
Zeyneddin Oz, Jonas Knoche, Alireza Yazdani, Bernd Engel, Kristof Van Laerhoven
https://arxiv.org/abs/2509.10272

TubeBEND: A Real-World Dataset for Geometry Prediction in Rotary Draw Bending
This paper presents TubeBEND, a real-world dataset comprising 318 rotary tube bending processes, which were collected and sorted by experts from various fields to evaluate machine learning and signal analysis methods. The dataset addresses the industrial challenge of predicting the geometry of a first-stage bend, which can be beneficial for designing machine clamping molds for the second-stage bend in two-stage rotary draw bending. Some geometry criteria, such as the tube's final bent angle (or…

Replaced article(s) found for cond-mat.supr-con. https://arxiv.org/list/cond-mat.supr-con/new
[1/1]:
- Influence of Fermi Surface Geometry and Van Hove Singularities on the Optical Response of Sr$_2$R...
Meghdad Yazdani-Hamid, Mehdi Biderang, Alireza Akbari

Artificial intelligence for simplified patient-centered dosimetry in radiopharmaceutical therapies
Alejandro Lopez-Montes, Fereshteh Yousefirizi, Yizhou Chen, Yazdan Salimi, Robert Seifert, Ali Afshar-Oromieh, Carlos Uribe, Axel Rominger, Habib Zaidi, Arman Rahmim, Kuangyu Shi
https://arxiv.org/abs/2510.12714…

Artificial intelligence for simplified patient-centered dosimetry in radiopharmaceutical therapies
KEY WORDS: Artificial Intelligence (AI), Theranostics, Dosimetry, Radiopharmaceutical Therapy (RPT), Patient-friendly dosimetry KEY POINTS - The rapid evolution of radiopharmaceutical therapy (RPT) highlights the growing need for personalized and patient-centered dosimetry. - Artificial Intelligence (AI) offers solutions to the key limitations in current dosimetry calculations. - The main advances on AI for simplified dosimetry toward patient-friendly RPT are reviewed. - Future directions on th…

This was always how it was going to end, just a financial settlement and AI companies can continue.
https://www.nytimes.com/2025/09/05/technology/anth…

Anthropic Agrees to Pay $1.5 Billion to Settle Lawsuit With Book Authors
The settlement is the largest payout in the history of U.S. copyright cases and could lead more A.I. companies to pay rights holders for use of their works.

Two-Stage Swarm Intelligence Ensemble Deep Transfer Learning (SI-EDTL) for Vehicle Detection Using Unmanned Aerial Vehicles
Zeinab Ghasemi Darehnaei, Mohammad Shokouhifar, Hossein Yazdanjouei, S. M. J. Rastegar Fatemi
https://arxiv.org/abs/2509.08026

Two-Stage Swarm Intelligence Ensemble Deep Transfer Learning (SI-EDTL) for Vehicle Detection Using Unmanned Aerial Vehicles
This paper introduces SI-EDTL, a two-stage swarm intelligence ensemble deep transfer learning model for detecting multiple vehicles in UAV images. It combines three pre-trained Faster R-CNN feature extractor models (InceptionV3, ResNet50, GoogLeNet) with five transfer classifiers (KNN, SVM, MLP, C4.5, Naïve Bayes), resulting in 15 different base learners. These are aggregated via weighted averaging to classify regions as Car, Van, Truck, Bus, or background. Hyperparameters are optimized with t…

🇺🇦 #NowPlaying on BBCRadio3's #ThroughTheNight
Johann Wilhelm Wilms & Arthur Schoonderwoerd:
🎵 Rondo - Polonaise pour le pianoforte in D major
#JohannWilhelmWilms #ArthurSchoonderwoerd
https://open.spotify.com/track/0Y9QTNbhyrAboLmF5H8DPD

🇺🇦 #NowPlaying on KEXP's #MiddayShow
Tres Leches:
🎵 No Llores
#TresLeches
https://tresleches.bandcamp.com/track/no-llores-2
https://open.spotify.com/track/3YjyTnWG4yHcCUwpB0zFe4