Tootfinder

Dominant scattering mechanisms and mobility peak in cryogenic 2D electron transport in Silicon (110) confinement by high-k oxides
Hsin-Wen Huang, Xi-Jun Fang, Edward Chen, Yuh-Renn Wu
https://arxiv.org/abs/2510.08220

Dominant scattering mechanisms and mobility peak in cryogenic 2D electron transport in Silicon (110) confinement by high-k oxides
The performance of silicon nano-devices at cryogenic temperatures is critical for quantum computing technologies. Through multi-valley Monte Carlo simulations of Si (110) systems, we reveal a fundamental shift in electron transport physics at low temperatures. Phonon scattering becomes negligible, and mobility is instead dictated by a competition between remote Coulomb scattering (RCS) at low carrier densities and surface roughness scattering (SRS) at high densities. This competition creates a …

CESRec: Constructing Pseudo Interactions for Sequential Recommendation via Conversational Feedback
Yifan Wang, Shen Gao, Jiabao Fang, Rui Yan, Billy Chiu, Shuo Shang
https://arxiv.org/abs/2509.09342

CESRec: Constructing Pseudo Interactions for Sequential Recommendation via Conversational Feedback
Sequential Recommendation Systems (SRS) have become essential in many real-world applications. However, existing SRS methods often rely on collaborative filtering signals and fail to capture real-time user preferences, while Conversational Recommendation Systems (CRS) excel at eliciting immediate interests through natural language interactions but neglect historical behavior. To bridge this gap, we propose CESRec, a novel framework that integrates the long-term preference modeling of SRS with t…

Score the Steps, Not Just the Goal: VLM-Based Subgoal Evaluation for Robotic Manipulation
Ramy ElMallah, Krish Chhajer, Chi-Guhn Lee
https://arxiv.org/abs/2509.19524 https://

Score the Steps, Not Just the Goal: VLM-Based Subgoal Evaluation for Robotic Manipulation
Robot learning papers typically report a single binary success rate (SR), which obscures where a policy succeeds or fails along a multi-step manipulation task. We argue that subgoal-level reporting should become routine: for each trajectory, a vector of per-subgoal SRs that makes partial competence visible (e.g., grasp vs. pour). We propose a blueprint for StepEval, a cost-aware plug-in evaluation framework that utilizes vision-language models (VLMs) as automated judges of subgoal outcomes from…

While the 20x single-level images of the PIC12F683 are only about 85 MB, the 100x focus stacked datasets are around 7GB each.
For comparison, all of the raw footage for my SRS GPSDO video was only 8.1 GB in total.
Sure, video is big, but when your microscope is spitting out a few thousand multi-megapixel stills an hour it'll chew through disk space pretty fast too.

Score the Steps, Not Just the Goal: VLM-Based Subgoal Evaluation for Robotic Manipulation
Ramy ElMallah, Krish Chhajer, Chi-Guhn Lee
https://arxiv.org/abs/2509.19524 https://

Score the Steps, Not Just the Goal: VLM-Based Subgoal Evaluation for Robotic Manipulation
Robot learning papers typically report a single binary success rate (SR), which obscures where a policy succeeds or fails along a multi-step manipulation task. We argue that subgoal-level reporting should become routine: for each trajectory, a vector of per-subgoal SRs that makes partial competence visible (e.g., grasp vs. pour). We propose a blueprint for StepEval, a cost-aware plug-in evaluation framework that utilizes vision-language models (VLMs) as automated judges of subgoal outcomes from…

Towards a Taxonomy of Sustainability Requirements for Software Design
Mandira Roy, Novarun Deb, Nabendu Chaki, Agostino Cortesi
https://arxiv.org/abs/2510.08990 https://

Towards a Taxonomy of Sustainability Requirements for Software Design
Software systems are a significant contributor to global sustainability concerns, demanding that environmental, social, technical, and economic factors be systematically addressed from the initial requirements engineering phase. Although existing research provides various sustainability requirements (SRs), these contributions are often fragmented, specific to certain dimensions, or limited to particular application domains, resulting in a critical lack of a unified, comprehensive taxonomy for t…

A Planning Strategy for Building a Heterogeneous Smart EM Environment
Arianna Benoni, Marco Salucci, Baozhu Li, Andrea Massa
https://arxiv.org/abs/2509.08378 https://

A Planning Strategy for Building a Heterogeneous Smart EM Environment
This paper presents a planning strategy for the deployment of smart electromagnetic entities (SEEs) to enhance the wireless coverage and the Quality-of-Service (QoS) in large urban areas. The integration of different technological solutions such as integrated access-and-backhaul nodes (IABs), smart repeaters (SRs), and electromagnetic skins (EMSs) is here addressed to enable an effective and efficient implementation of the concept of Smart Electromagnetic Environment (SEME). By combining the fe…

What Matters in LLM-Based Feature Extractor for Recommender? A Systematic Analysis of Prompts, Models, and Adaptation
Kainan Shi (Xi'an Jiaotong University), Peilin Zhou (Hong Kong University of Science,Technology), Ge Wang (Xi'an Jiaotong University), Han Ding (Xi'an Jiaotong University), Fei Wang (Xi'an Jiaotong University)
https://

What Matters in LLM-Based Feature Extractor for Recommender? A Systematic Analysis of Prompts, Models, and Adaptation
Using Large Language Models (LLMs) to generate semantic features has been demonstrated as a powerful paradigm for enhancing Sequential Recommender Systems (SRS). This typically involves three stages: processing item text, extracting features with LLMs, and adapting them for downstream models. However, existing methods vary widely in prompting, architecture, and adaptation strategies, making it difficult to fairly compare design choices and identify what truly drives performance. In this work, w…