Information-Theoretic Text Hallucination Reduction for Video-grounded Dialogue

Video-grounded Dialogue (VGD) aims to decode an answer sentence to a question regarding a given video and dialogue context. Despite the recent success of multi-modal reasoning to generate answer sentences, existing dialogue systems still suffer from a text hallucination problem, which denotes indiscriminate text-copying from input texts without an understanding of the question. This is due to learning spurious correlations from the fact that answer sentences in the dataset usually include the words of input texts, thus the VGD system excessively relies on copying words from input texts by hoping those words to overlap with ground-truth texts. Hence, we design Text Hallucination Mitigating (THAM) framework, which incorporates Text Hallucination Regularization (THR) loss derived from the proposed information-theoretic text hallucination measurement approach. Applying THAM with current dialogue systems validates the effectiveness on VGD benchmarks (i.e., AVSD@DSTC7 and AVSD@DSTC8) and shows enhanced interpretability.Comment: 12 pages, Accepted in EMNLP 202

ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure

Studies have shown that modern neural networks tend to be poorly calibrated due to over-confident predictions. Traditionally, post-processing methods have been used to calibrate the model after training. In recent years, various trainable calibration measures have been proposed to incorporate them directly into the training process. However, these methods all incorporate internal hyperparameters, and the performance of these calibration objectives relies on tuning these hyperparameters, incurring more computational costs as the size of neural networks and datasets become larger. As such, we present Expected Squared Difference (ESD), a tuning-free (i.e., hyperparameter-free) trainable calibration objective loss, where we view the calibration error from the perspective of the squared difference between the two expectations. With extensive experiments on several architectures (CNNs, Transformers) and datasets, we demonstrate that (1) incorporating ESD into the training improves model calibration in various batch size settings without the need for internal hyperparameter tuning, (2) ESD yields the best-calibrated results compared with previous approaches, and (3) ESD drastically improves the computational costs required for calibration during training due to the absence of internal hyperparameter. The code is publicly accessible at https://github.com/hee-suk-yoon/ESD.Comment: ICLR 202

Full Tendon Transposition Augmented with Posterior Intermuscular Suture and Recession - Resection Surgery

Purpose: To report an effect of the full tendon transposition augmented with posterior intermuscular suture and recession-resection surgery, for the patient with monocular elevation deficiency (MED) and large exotropia. Methods: Interventional case report. Full tendon transposition augmented with posterior intermuscular suture and recession-resection surgery was performed for a 26-year-old male patient had monocular elevation deficiency (MED) and large exotropia. Results: Preoperative angle of deviation was 56 prism diopters (PD) hypotropia and 45 PD right exotropia, compared with 18 PD left hypertropia and 10 PD right esotropia postoperatively. Essotropia persisted after 2.5 years, however, and so the right medial rectus was recessed after removal of the previous posterior intermuscular suture. At a three-year follow-up after the second surgery, alignment was straight in the primary position at near and far distances. Conclusions: Full tendon transposition augmented with posterior intermuscular suture and recession-resection surgery was effective for a patient with MED associated with significant horizontal deviation, and a second operation was easily performed when overcorrection occurred.ope

C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion

In deep learning, test-time adaptation has gained attention as a method for model fine-tuning without the need for labeled data. A prime exemplification is the recently proposed test-time prompt tuning for large-scale vision-language models such as CLIP. Unfortunately, these prompts have been mainly developed to improve accuracy, overlooking the importance of calibration, which is a crucial aspect for quantifying prediction uncertainty. However, traditional calibration methods rely on substantial amounts of labeled data, making them impractical for test-time scenarios. To this end, this paper explores calibration during test-time prompt tuning by leveraging the inherent properties of CLIP. Through a series of observations, we find that the prompt choice significantly affects the calibration in CLIP, where the prompts leading to higher text feature dispersion result in better-calibrated predictions. Introducing the Average Text Feature Dispersion (ATFD), we establish its relationship with calibration error and present a novel method, Calibrated Test-time Prompt Tuning (C-TPT), for optimizing prompts during test-time with enhanced calibration. Through extensive experiments on different CLIP architectures and datasets, we show that C-TPT can effectively improve the calibration of test-time prompt tuning without needing labeled data. The code is publicly accessible at https://github.com/hee-suk-yoon/C-TPT.Comment: ICLR 202

Calcium Uptake and Release through Sarcoplasmic Reticulum in the Inferior Oblique Muscles of Patients with Inferior Oblique Overaction

We characterized and compared the characteristics of Ca2+ movements through the sarcoplasmic reticulum of inferior oblique muscles in the various conditions including primary inferior oblique overaction (IOOA), secondary IOOA, and controls, so as to further understand the pathogenesis of primary IOOA. Of 15 specimens obtained through inferior oblique myectomy, six were from primary IOOA, 6 from secondary IOOA, and the remaining 3 were controls from enucleated eyes. Ryanodine binding assays were performed, and Ca2+ uptake rates, calsequestrins and SERCA levels were determined. Ryanodine bindings and sarcoplasmic reticulum Ca2+ uptake rates were significantly decreased in primary IOOA (p<0.05). Western blot analysis conducted to quantify calsequestrins and SERCA, found no significant difference between primary IOOA, secondary IOOA, and the controls. Increased intracellular Ca2+ concentration due to reduced sarcoplasmic reticulum Ca2+ uptake may play a role in primary IOOA

Parent-Reported Symptoms of Attention Deficit Hyperactivity Disorder in Children with Intermittent Exotropia before and after Strabismus Surgery

∙ The authors have no financial conflicts of interest. © Copyright: Yonsei University College of Medicine 2012 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial Licens