Tootfinder

Granular feedback merits sophisticated aggregation
Anmol Kagrecha, Henrik Marklund, Potsawee Manakul, Richard Zeckhauser, Benjamin Van Roy
https://arxiv.org/abs/2507.12041

Granular feedback merits sophisticated aggregation
Human feedback is increasingly used across diverse applications like training AI models, developing recommender systems, and measuring public opinion -- with granular feedback often being preferred over binary feedback for its greater informativeness. While it is easy to accurately estimate a population's distribution of feedback given feedback from a large number of individuals, cost constraints typically necessitate using smaller groups. A simple method to approximate the population distribut…

Humanizing Automated Programming Feedback: Fine-Tuning Generative Models with Student-Written Feedback
Victor-Alexandru P\u{a}durean, Tung Phung, Nachiket Kotalwar, Michael Liut, Juho Leinonen, Paul Denny, Adish Singla
https://arxiv.org/abs/2509.10647

Humanizing Automated Programming Feedback: Fine-Tuning Generative Models with Student-Written Feedback
The growing need for automated and personalized feedback in programming education has led to recent interest in leveraging generative AI for feedback generation. However, current approaches tend to rely on prompt engineering techniques in which predefined prompts guide the AI to generate feedback. This can result in rigid and constrained responses that fail to accommodate the diverse needs of students and do not reflect the style of human-written feedback from tutors or peers. In this study, we…

Two-point Random Gradient-free Methods for Model-free Feedback Optimization
Amir Mehrnoosh, Gianluca Bianchin
https://arxiv.org/abs/2509.11666 https://arxi…

Two-point Random Gradient-free Methods for Model-free Feedback Optimization
Feedback optimization has emerged as a promising approach for optimizing the steady-state operation of dynamical systems while requiring minimal modeling efforts. Unfortunately, most existing feedback optimization methods rely on knowledge of the plant dynamics, which may be difficult to obtain or estimate in practice. In this paper, we introduce a novel randomized two-point gradient-free feedback optimization method, inspired by zeroth-order optimization techniques. Our method relies on functi…

Leveraging Bi-Directional Channel Reciprocity for Robust Ultra-Low-Rate Implicit CSI Feedback with Deep Learning
Zhenyu Liu, Yi Ma, Rahim Tafazolli, Zhi Ding
https://arxiv.org/abs/2507.12301

Leveraging Bi-Directional Channel Reciprocity for Robust Ultra-Low-Rate Implicit CSI Feedback with Deep Learning
Deep learning-based implicit channel state information (CSI) feedback has been introduced to enhance spectral efficiency in massive MIMO systems. Existing methods often show performance degradation in ultra-low-rate scenarios and inadaptability across diverse environments. In this paper, we propose Dual-ImRUNet, an efficient uplink-assisted deep implicit CSI feedback framework incorporating two novel plug-in preprocessing modules to achieve ultra-low feedback rates while maintaining high enviro…

Ehemaliger KGB-Agent betritt ehemaliges russisches Gebiet, um einen aktiven KGB-Agenten zu begrüßen.
#trump #putin

User eXperience Perception Insights Dataset (UXPID): Synthetic User Feedback from Public Industrial Forums
Mikhail Kulyabin, Jan Joosten, Choro Ulan uulu, Nuno Miguel Martins Pacheco, Fabian Ries, Filippos Petridis, Jan Bosch, Helena Holmstr\"om Olsson
https://arxiv.org/abs/2509.11777

User eXperience Perception Insights Dataset (UXPID): Synthetic User Feedback from Public Industrial Forums
Customer feedback in industrial forums reflect a rich but underexplored source of insight into real-world product experience. These publicly shared discussions offer an organic view of user expectations, frustrations, and success stories shaped by the specific contexts of use. Yet, harnessing this information for systematic analysis remains challenging due to the unstructured and domain-specific nature of the content. The lack of structure and specialized vocabulary makes it difficult for tradi…

US is working on doubling aid to Argentina to $40 billion by tapping private funding sources (Associated Press)
https://apnews.com/article/trump-argentina-financing-economy-milei-billion-peso-fd38553ae03f4c33ce1288999469f7fb
http://www.memeorandum.com/251016/p82#a251016p82

Characterizing the interplay between Galactic star formation and ionization feedback with PRIMA
Annie Zavagno, Delphine Russeil, Paolo Suin, Siju Zhang, Ram Kesh Yadav, Miguel Figueira, Loris Berthelot, Doris Arzoumanian, Manash Ranjan Samal, Vineet Rawat, Philippe Andr\'e, Michael Mattern, Hong-Li Liu, Sarah Sadavoy, Parisa Nozari, Beno\^it Epinat
https://…

Characterizing the interplay between Galactic star formation and ionization feedback with PRIMA
Recent results from the James Webb Space Telescope show that nearby spiral galaxies are dominated by the presence of H I and H II bubbles that strongly shape their surrounding medium. These bubbles result from the feedback of high-mass stars at different stages of their life cycle. However, early (pre-supernova) feedback from high-mass stars is still poorly quantified. Recent results from numerical simulations suggest that the impact of high-mass star early feedback (photoionization, wind) on s…

bro what even HAPPENED
#fedifc #vasco

NEFT: A Unified Transformer Framework for Efficient Near-Field CSI Feedback in XL-MIMO Systems
Haiyang Li, Tianqi Mao, Pengyu Wang, Ruiqi Liu, Shunyu Li, Zhaocheng Wang
https://arxiv.org/abs/2509.12748

NEFT: A Unified Transformer Framework for Efficient Near-Field CSI Feedback in XL-MIMO Systems
Extremely large-scale multiple-input multiple-output (XL-MIMO) systems, operating in the near-field region due to their massive antenna arrays, are a key enabler of next-generation wireless communications but face significant challenges in channel state information (CSI) feedback. Deep learning has emerged as a powerful tool by learning compact CSI representations for feedback. However, existing methods struggle to capture the intricate structure of near-field CSI while incurring prohibitive co…