Real Feedback
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
Coil-Integrated Alignment Sensor for Real-Time Feedback of Coil-Scalp Contact Point and Angle During Transcranial Magnetic Stimulation (TMS)
arXiv:2606.08618v1 Announce Type: new Abstract: Whereas coil positioning in transcranial magnetic stimulation (TMS) to reach a specific cortical target with modern focal stimulation coils has been intensively studied, the alignment and contact of a coil with the head is often ignored. Focal figure-of-eight coils have a point on the surface, where they generate the largest induced electric field.
Coil-Integrated Alignment Sensor for Real-Time Feedback of Coil-Scalp Contact Point and Angle During Transcranial Magnetic Stimulation (TMS)
Announce Type: cross Abstract: Whereas coil positioning in transcranial magnetic stimulation (TMS) to reach a specific cortical target with modern focal stimulation coils has been intensively studied, the alignment and contact of a coil with the head is often ignored. Focal figure-of-eight coils have a point on the surface, where they generate the largest induced electric field.
Automatic, Real-time Classification of User Feedback Using Large Language Models
arXiv:2606.08050v1 Announce Type: new Abstract: In this paper we discuss an ongoing multi-year project that aims to make open text feedback more accessible and useful to UX practitioners by automating classification and providing real time access to comments, themes, and analysis. By significantly lowering the time and knowledge cost of implementing automated solutions, we aim to effectively democratize our data analysis processes, allowing and encouraging non-technical stakeholders to...
UXBench: Benchmarking User Experience in AI Assistants
arXiv:2606.09570v1 Announce Type: new Abstract: As AI assistants serve millions of users daily, evaluating user experience (UX) beyond general model capability has become increasingly important. We present UXBench, the first user-centric benchmark grounded in real user feedback signals for evaluating preference alignment and dialogue generation. The benchmark consists of three interconnected tasks, UX Judge, UX Eval, and UX Recovery, with 7,400 test instances extracted from over 70K...
ModuLoop : Low-Level Code Generation using Modular Synthesizer and Closed-Loop Debugger for Robotic Control
arXiv:2606.03047v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated impressive performance across various domains, including code generation and problem solving. However, their application in robotic control, particularly in low-level tasks that require precise manipulation, real-time feedback, and environment-dependent execution, remains limited.
QuickLAP: Quick Language-Action Preference Learning for Semi-Autonomous Agents
arXiv:2511.17855v5 Announce Type: replace Abstract: Robots must learn from both what people do and what they say, but either modality alone is often incomplete: physical corrections are grounded but ambiguous in intent, while language expresses high-level goals but lacks physical grounding. We introduce QuickLAP: Quick Language-Action Preference learning, a Bayesian framework that fuses physical and language feedback to infer reward functions in real time. Our key insight is to treat...
Closed-loop neurofeedback reshapes preparatory brain states to bias subsequent pain processing
Pain perception is strongly influenced by neural states preceding stimulus onset, yet whether such preparatory states can be causally reshaped remains unclear. Using a double-blind design, we tested whether closed-loop neurofeedback can reconfigure preparatory brain dynamics to influence subsequent pain processing. Real, but not sham, feedback enabled learning-dependent enhancement of pre-stimulus oscillations in primary somatosensory cortex and their trans-hemispheric propagation.
Time series Foundation Models based on Physics-Informed Synthetic Histories for Cold-Start Photovoltaic Forecasting
arXiv:2606.07457v1 Announce Type: new Abstract: At commissioning time, Photovoltaic (PV) operators must forecast production before target-site observations are available, limiting the direct use of standard supervised forecasters. This cold-start setting is addressed with a zero-shot pipeline that generates a synthetic production history from plant metadata and meteorological covariates, enabling time-series foundation models (TSFMs) to forecast through inference-time conditioning. Five...
Optimal Feedback Communication with Information Maximization and Distortion Minimization
Announce Type: new Abstract: We study the problem of optimally sending a real-valued source through multiple uses of a channel with feedback. First, we state a set of conditions that are sufficient for an encoder to achieve maximal mutual information between the source and all the channel outputs. This set of conditions are also necessary when the channel is input-identifiable, a condition widely satisfied by common channel models.
Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams
arXiv:2606.01770v2 Announce Type: replace Abstract: Auto-harness systems such as A-Evolve, GEPA, and Meta-Harness improve LLM agents by optimizing prompts, skills, tools, memories, and supporting infrastructure from execution feedback, but they are typically evaluated on fixed offline benchmarks. Real deployments instead present open-ended task streams: histories grow without a fixed endpoint, heterogeneous tasks require different harnesses, and problem distributions shift over time. These...