In this task, you are given the abstract of a research paper. Your task is to generate a summary of this abstract. Your summary should not be very short, but it's better if it's not more than 30 words.

We present Line-Storm, an interactive computer system for creative performance. The context we investigated was writing on paper using Line-Storm. We used self-report questionnaires as part of research involving human participants, to evaluate Line-Storm. Line-Storm consisted of a writing stylus and writing pad, augmented with electronics. The writing pad was connected to a contact microphone, and the writing stylus had a small micro-controller board and peripherals attached to it. The signals from these electronic augmentations were fed into the audio-synthesis environment Max/MSP to produce an interactive soundscape. We attempted to discover whether Line-Storm enhanced a self-reported sense of being present and engaged during a writing task, and we compared Line-Storm to a non-interactive control condition. After performing statistical analysis in SPSS, we were unable to support our research hypothesis, that presence and engagement were enhanced by Line-Storm. Participants reported they were, on average, no more present and engaged during the experimental condition than during the control condition. As creativity is subtle, and varies with person, time, context,  space and so many other factors, this result was somewhat expected by us. A statistically significant result of our study is that some participants responded to Line-Storm more positively than others. These Preservers of Line-Storm were a group, distinct from other participants, who reported greater presence and engagement and who wrote more words with Line-Storm and during the control condition. We discuss the results of our research and place Line-Storm in an artistic-technological context, drawing upon writings by Martin Heidegger when considering the nature of Line-Storm. Future work includes modifying interactive components, improving aesthetics and using more miniaturized electronics, experimenting with a drawing task instead of a writing task, and collaborating with a composer of electronic music to make a more interesting, immersive, and engaging interactive soundscape for writing or drawing performance.
Interactive stylus based sound incorporating writing system

We present local ensembles, a method for detecting extrapolation at test time in a pre-trained model. We focus on underdetermination as a key component of extrapolation: we aim to detect when many possible predictions are consistent with the training data and model class. Our method uses local second-order information to approximate the variance of predictions across an ensemble of models from the same class. We compute this approximation by estimating the norm of the component of a test point's gradient that aligns with the low-curvature directions of the Hessian, and provide a tractable method for estimating this quantity. Experimentally, we show that our method is capable of detecting when a pre-trained model is extrapolating on test data, with applications to out-of-distribution detection, detecting spurious correlates, and active learning.
We present local ensembles, a method for detecting extrapolation in trained models, which approximates the variance of an ensemble using local-second order information.

Emoji suggestion systems based on typed text have been proposed to encourage emoji usage and enrich text messaging; however, such systems’ actual effects on the chat experience remain unknown. We built an Android keyboard with both lexical (word-based) and semantic (meaning-based) emoji suggestion capabilities and compared these in two different studies. To investigate the effect of emoji suggestion in online conversations, we conducted a laboratory text-messaging study with 24 participants, and also a 15-day longitudinal field deployment with 18 participants. We found that lexical emoji suggestions increased emoji usage by 31.5% over a keyboard without suggestions, while semantic suggestions increased emoji usage by 125.1%. However, suggestion mechanisms did not affect the chatting experience significantly. From these studies, we formulate a set of design guidelines for future emoji suggestion systems that better support users’ needs.

We built an Android keyboard with both lexical (word-based) and semantic (meaning-based) emoji suggestion capabilities and compared their effects in two different chat studies.