'%3e%3cpath%20id='Union_1'%20data-name='Union%201'%20d='M-5781,4536a7.008,7.008,0,0,1-7-7V4303a7.008,7.008,0,0,1,7-7h406a7.007,7.007,0,0,1,7,7v226a7.007,7.007,0,0,1-7,7Zm296.87-59.21h.429a34.709,34.709,0,0,0,13.062,12.363,41.318,41.318,0,0,0,19.833,4.623,44.184,44.184,0,0,0,18.991-4.085,41.906,41.906,0,0,0,14.738-11.663,54.459,54.459,0,0,0,9.538-18.357,81.868,81.868,0,0,0,3.389-24.161,76.7,76.7,0,0,0-3.524-23.615,56.05,56.05,0,0,0-9.833-18.417,44.205,44.205,0,0,0-15.033-11.965,43.653,43.653,0,0,0-19.125-4.268,41.589,41.589,0,0,0-10.4,1.253,33.377,33.377,0,0,0-8.442,3.451,35.836,35.836,0,0,0-11.906,11.636h-.645v-56.76H-5512.3V4490.55h28.165v-13.759h0Zm-86.973-77.544a16.939,16.939,0,0,1,5.783,2.644,11.2,11.2,0,0,1,3.483,4.136,12.285,12.285,0,0,1,1.165,5.4,7.957,7.957,0,0,1-1.6,5.124,11.352,11.352,0,0,1-4.881,3.289c-4.365,1.74-10.826,2.737-20.184,4.059-14.33,2.012-24.288,5.163-31.337,9.917a31.516,31.516,0,0,0-5.4,4.564,26.736,26.736,0,0,0-4.077,5.686,28.308,28.308,0,0,0-2.576,6.949,37.143,37.143,0,0,0-.9,8.358,35.863,35.863,0,0,0,2.84,14.526,28.821,28.821,0,0,0,7.937,10.576c6.757,5.661,16.339,8.653,27.709,8.653,8.826,0,15.771-1.4,21.231-4.272a27.467,27.467,0,0,0,6.464-4.706,35.968,35.968,0,0,0,4.769-5.857h.43c.566,4.336,1.621,9.981,3.44,12.255h28.166v-1.075c-2.6-1.952-3.87-6.946-3.87-15.266v-56.115a52.109,52.109,0,0,0-2.6-17.232,33.613,33.613,0,0,0-3.363-6.962,30,30,0,0,0-4.84-5.8,32.371,32.371,0,0,0-6.393-4.587,41.66,41.66,0,0,0-8.02-3.333,73.776,73.776,0,0,0-21.226-2.722,68.568,68.568,0,0,0-20.907,2.958,41.752,41.752,0,0,0-14.62,7.955,33.743,33.743,0,0,0-8.735,11.583,37.016,37.016,0,0,0-3.252,13.84h26.014c.436-5.33,2.334-9.154,5.806-11.691,3.489-2.55,8.553-3.79,15.479-3.79A31.85,31.85,0,0,1-5571.1,4399.246Zm-172.534,91.3h31.174v-63.64h66.866v-26.66h-66.866v-36.98h78.9v-26.446h-110.079Zm565.082,0V4336.825h31.175V4490.55Zm-47.3,0-10.319-32.68h-55.47l-10.105,32.68h-31.605l53.535-153.725h32.25l54.179,153.725Zm-44.72-100.835-13.76,44.29h40.635l-13.76-44.29c-2.58-8.169-6.234-23.649-6.234-23.649h-.43S-5267.994,4381.545-5270.574,4389.715Zm-322.508,82.258a15.1,15.1,0,0,1-5.428-2.385,10.732,10.732,0,0,1-3.494-4.32,15.912,15.912,0,0,1-1.237-6.538,14.009,14.009,0,0,1,1.415-6.557,12.537,12.537,0,0,1,4.256-4.622c3.37-2.3,8.331-4.04,17.119-6.021l1.478-.346.119-.028c6.9-1.614,14.042-3.283,18.828-6.076v16.555a18.766,18.766,0,0,1-1.707,7.828,20.2,20.2,0,0,1-5.012,6.739,24.3,24.3,0,0,1-8.156,4.724,33.506,33.506,0,0,1-11.14,1.779A30.49,30.49,0,0,1-5593.083,4471.973Zm116.477-11.683c-4.641-5.844-7.1-14.189-7.1-24.135,0-10.853,1.936-19.36,5.752-25.289a20.911,20.911,0,0,1,7.853-7.334,25.024,25.024,0,0,1,11.765-2.637,22.381,22.381,0,0,1,10.724,2.537,21.5,21.5,0,0,1,7.66,7.112,34.013,34.013,0,0,1,4.595,10.941,59.734,59.734,0,0,1,1.532,14.025,60.268,60.268,0,0,1-1.545,14.254,32.125,32.125,0,0,1-4.528,10.6,20.177,20.177,0,0,1-7.352,6.615,21.564,21.564,0,0,1-10.011,2.281C-5465.25,4469.265-5471.94,4466.162-5476.606,4460.29Z'%20transform='translate(5788%20-4296)'/%3e%3c/g%3e%3c/svg%3e)
Enhancing Essay Scoring with Adversarial Weights Perturbation and Metric-specific AttentionPooling
This paper proposes using DeBERTa with Adversarial Weights Perturbation and Metric-specific AttentionPooling to improve automated essay scoring specifically for English Language Learners (ELLs), focusing on optimizing hyperparameters to better evaluate writing proficiency.
The objective of this study is to improve automated feedback tools designed for English Language Learners (ELLs) through the utilization of data science techniques encompassing machine learning, natural language processing, and educational data analytics. Automated essay scoring (AES) research has made strides in evaluating written essays, but it often overlooks the specific needs of English Language Learners (ELLs) in language development. This study explores the application of BERT-related tec