How You Prompt Matters! Even Task-Oriented Constraints in Instructions Affect LLM-Generated Text Detection

Against the misuse (e.g., plagiarism or spreading misinformation) of Large Language Models (LLMs), many recent works have presented LLM-generated-text detectors with promising detection performance. Spotlighting a situation where users instruct LLMs to generate texts (e.g., essay writing), there are various ways to write the instruction (e.g., what task-oriented constraint to include). In this paper, we discover that even a task-oriented constraint in instruction can cause the inconsistent performance of current detectors to the generated texts. Specifically, we focus on student essay writing as a realistic domain and manually create the task-oriented constraint for each factor on essay quality by Ke and Ng (2019). Our experiment shows that the detection performance variance of the current detector on texts generated by instruction with each task-oriented constraint is up to 20 times larger than the variance caused by generating texts multiple times and paraphrasing the instruction. Our finding calls for further research on developing robust detectors that can detect such distributional shifts caused by a task-oriented constraint in the instruction

OUTFOX: LLM-generated Essay Detection through In-context Learning with Adversarially Generated Examples

Large Language Models (LLMs) have achieved human-level fluency in text generation, making it difficult to distinguish between human-written and LLM-generated texts. This poses a growing risk of misuse of LLMs and demands the development of detectors to identify LLM-generated texts. However, existing detectors degrade detection accuracy by simply paraphrasing LLM-generated texts. Furthermore, the effectiveness of these detectors in real-life situations, such as when students use LLMs for writing homework assignments (e.g., essays) and quickly learn how to evade these detectors, has not been explored. In this paper, we propose OUTFOX, a novel framework that improves the robustness of LLM-generated-text detectors by allowing both the detector and the attacker to consider each other's output and apply this to the domain of student essays. In our framework, the attacker uses the detector's prediction labels as examples for in-context learning and adversarially generates essays that are harder to detect. While the detector uses the adversarially generated essays as examples for in-context learning to learn to detect essays from a strong attacker. Our experiments show that our proposed detector learned in-context from the attacker improves the detection performance on the attacked dataset by up to +41.3 point F1-score. While our proposed attacker can drastically degrade the performance of the detector by up to -57.0 point F1-score compared to the paraphrasing method

Impact of Two Courses on Intercultural Competence of Undergraduate Students

Increasing migrations across the world mean leaders at all levels need to become more competent in working across cultures. During the past 30 years, program designers, researchers, and others have investigated intercultural competence (ICC), often described as the capability to accurately understand and adapt behavior to cultural differences and commonalities. Tertiary education programs (TEP) are accepting these challenges by offering experiences (such as coursework, study away, study abroad, cultural events, etc.) that are intended to produce culturally competent graduates. The teaching and learning experiences described in this study at a midwestern American university may inform others. This study examined archived data from two courses designed to enhance undergraduates’ ICC. Researchers expected that students who completed a course, called Critical Race Theory in Education (CRT), would show statistically larger gains during a second course, called Human Relations in a Multicultural Society (HRMS). At the beginning and conclusion of HRMS, students completed the Intercultural Development Inventory (IDI). Researchers used the two-sample t-test to compare the pre-HRMS scores of students who had completed CRT and students who had not completed CRT. Analysis showed students who took CRT before HRMS had statistically significantly higher beginning scores than students who had not completed CRT before they enrolled in HRMS (p = .042). Although students who completed CRT started HRMS with the higher IDI mean score, those individuals did not make statistically significant gains in their ICC during the HRMS course (p = .130). However, the students who had not completed CRT before HRMS did make statistically significant gains in their ICC during the HRMS course (p \u3c .001). These results, with additional research, could be used to redesign the courses or to design other curricula approaches

Temperature dependence of water cluster on functionalized graphite

Our recent experimental study of water adsorption in micro-mesoporous carbons at 263 K and 298 K show an unusual temperature dependence of adsorbed density with higher loading at 298 K at the same reduced pressure. The difference is in the filling of mesopore at 298 K and its absence at 263 K, and it was conjectured to the growth of water clusters on the functional groups in the confined space of mesopores in which the water clusters at 298 K are sufficiently large to induce the subsequent filling. Since the growth of these clusters and their coalescence is the prerequisite for filling, the filling is absent at 263 K simply because of the smaller size of the clusters, preventing them from coalescence and hence, no filling. In a quest to understand the effects of temperature on water adsorption in micro-mesoporous carbon, we used molecular dynamic simulation to reveal the mechanism of water adsorption around functional groups from 263 K to 328 K to clarify the growth of the water cluster as a function of temperature. The results clearly show that the water cluster is larger at 298 K compared to 263 K, confirming the conjecture from our previous works

2D/3D Deep Image Registration by Learning 3D Displacement Fields for Abdominal Organs

Deformable registration of two-dimensional/three-dimensional (2D/3D) images of abdominal organs is a complicated task because the abdominal organs deform significantly and their contours are not detected in two-dimensional X-ray images. We propose a supervised deep learning framework that achieves 2D/3D deformable image registration between 3D volumes and single-viewpoint 2D projected images. The proposed method learns the translation from the target 2D projection images and the initial 3D volume to 3D displacement fields. In experiments, we registered 3D-computed tomography (CT) volumes to digitally reconstructed radiographs generated from abdominal 4D-CT volumes. For validation, we used 4D-CT volumes of 35 cases and confirmed that the 3D-CT volumes reflecting the nonlinear and local respiratory organ displacement were reconstructed. The proposed method demonstrate the compatible performance to the conventional methods with a dice similarity coefficient of 91.6 \% for the liver region and 85.9 \% for the stomach region, while estimating a significantly more accurate CT values

Itinerant Ferromagnetism in layered crystals LaCoOX (X = P, As)

The electronic and magnetic properties of cobalt-based layered oxypnictides, LaCoOX (X = P, As), are investigated. LaCoOP and LaCoOAs show metallic type conduction, and the Fermi edge is observed by hard x-ray photoelectron spectroscopy. Ferromagnetic transitions occur at 43 K for LaCoOP and 66 K for LaCoOAs. Above the transition temperatures, temperature dependence of the magnetic susceptibility follows the Curie-Weiss law. X-ray magnetic circular dichroism (XMCD) is observed at the Co L2,3-edge, but not at the other edges. The calculated electronic structure shows a spin polarized ground state. These results indicate that LaCoOX are itinerant ferromagnets and suggest that their magnetic properties are governed by spin fluctuation.Comment: 16 pages, 9 figures, Physical Review B, in press. Received 17 February 2008. Accepted 29 May 200

Characteristics of liquid cluster ion beam for surface treatment

A liquid cluster ion source, which is an ion source for the cluster beams produced with liquid materials, has been developed for the surface treatment of solid materials. The electrodes were designed for increasing the cluster beam intensity by a computer simulation of beam trajectories. The peaks of the cluster size distributions of the water and ethanol cluster ion beams of 3 atm vapor pressure were approximately at 2.4×103 and 1.6×103 molecules, respectively. The cluster size distributions of ethanol clusters were not sensitive to the variations of the acceleration voltages (Ve) and currents (Ie) of the electrons for ionization when the Ve and Ie were larger than approximately 200 V and 200 mA, respectively

A role of central alpha-1 adrenergic mechanism in shaking stress-induced ACTH and noradrenaline secretion.

The role of alpha-1 adrenergic mechanism in the shaking stress-induced adrenocorticotropic hormone (ACTH), and plasma noradrenaline secretion and pressor response were investigated using conscious rats. We also studied whether or not central corticotropin releasing hormone (CRH) is involved in the shaking stress-induced ACTH secretion. The shaking stress caused significant elevations of plasma ACTH, noradrenaline, and systolic blood pressure. Intra-third ventricular administration of alpha-1 adrenergic blocker, bunazosin, inhibited the shaking stress-induced ACTH secretion, but did not alter stress-induced noradrenaline secretion and pressor response. Furthermore, intra-third ventricular administration of CRH antagonist, alpha-helical CRH, significantly attenuated stress-induced ACTH secretion. These results indicate that alpha-1 adrenergic pathway and CRH at least partly mediate the shaking stress-induced ACTH secretion.&#60;/P&#62;</p