Mind's Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models

Large language models (LLMs) have achieved remarkable advancements in the field of natural language processing. However, the sheer scale and computational demands of these models present formidable challenges when considering their practical deployment in resource-constrained contexts. While techniques such as chain-of-thought (CoT) distillation have displayed promise in distilling LLMs into small language models (SLMs), there is a risk that distilled SLMs may still carry over flawed reasoning or hallucinations inherited from their LLM counterparts. To address these issues, we propose a twofold methodology: First, we introduce a novel method for distilling the self-evaluation capability inherent in LLMs into SLMs, which aims to mitigate the adverse effects of erroneous reasoning and reduce hallucinations. Second, we advocate for a comprehensive distillation process that incorporates multiple distinct chain-of-thought and self-evaluation paradigms and ensures a more holistic and robust knowledge transfer into SLMs. Experiments on three NLP benchmarks demonstrate that our method significantly improves the performance of distilled SLMs and sheds light on the path towards developing smaller models closely aligned with human cognition.Comment: 13 pages, 5 figure

Abdomen anatomic characteristics on CT scans as predictive markers for short-term complications following radical resection of colorectal cancer

BackgroundPrediction and management of short-term postoperative complications in patients with colorectal cancer are essential in postoperative rehabilitation. Through CT scan images, we can easily measure some parameters of abdomen anatomic characteristics. This study aimed to assess whether there is a relationship between the abdomen anatomic characteristics and short-term postoperative complications.Materials and methodsWe conducted a retrospective study. Eighty patients in each complication group and non-complication group were recruited with propensity score match. Demographics, perioperative laboratory results and surgical information were collected and compared between groups with univariate analysis. Significant elements were brought into subsequent logistic regression analysis and ROC analysis for further identification.ResultsUnivariate analysis showed that preoperative white blood cells, preoperative neutrophil counts, rectus abdominis thickness (RAT), subcutaneous fat thickness (SFT), and abdomen depth (AD) were significantly different between the complication group and non-complication group. Logistic regression analysis demonstrated that higher RAT (p = 0.002), SFT (p < 0.001) and AD (p < 0.001) independently predicted the incidence of short-term postoperative complications.ConclusionsIn this study on patients undergoing radical resection of colorectal cancer, abdomen anatomic characteristics including higher RAT, SFT and AD are associated with an increased risk of short-term postoperative complications

Chemical compositions, A-glucosidase and A-amylase inhibitory activities of crude polysaccharides from the endodermis of shaddock (Citrus maxima)

The chemical composition of shaddock mainly includes polyphenols, proteins and polysaccharides. However, polysaccharides from shaddock materials have received much less consideration than polyphenols (Fellers et al., 1990). Herein the chemical compositions, α-glucosidase and α-amylase inhibitory activities of crude polysaccharides from the endodermis of shaddock were investigated. The exopolysaccharides (EPS) exhibited a broad and intense peak at 3300-3400 cm-1 that characterized the absorption of the hydroxyl group, and one weak C-H band at around 2941.3 cm-1 in the IR spectrum. The content of neutral sugars in EPS was determined as 37.16%. The content of acidic sugar in EPS was determined as 33.71%. EPS exhibited the highest content of neutral sugar. The content of proteins in EPS was 5.75%. The content of polyphenols was 6.52%. The EPS mainly consisted of four types of polysaccharides with molecular weights of 110 kD, 68 kD, 31 kD and 12 kD. The crude EPS showed significantly higher inhibitory effects on α-glucosidase and α-amylase (inhibition to 74.12% and 86.59%, respectively)

Deeper and Mixed Supervision for Salient Object Detection in Automated Surface Inspection

In recent years, researches in the field of salient object detection have been widely made in many industrial visual inspection tasks. Automated surface inspection (ASI) can be regarded as one of the most challenging tasks in computer vision because of its high cost of data acquisition, serious imbalance of test samples, and high real-time requirement. Inspired by the requirements of industrial ASI and the methods of salient object detection (SOD), a task mode of defect type classification plus defect area segmentation and a novel deeper and mixed supervision network (DMS) architecture is proposed. The backbone network ResNeXt-101 was pretrained on ImageNet. Firstly, we extract five multiscale feature maps from backbone and concatenate them layer by layer. In addition, to obtain the classification prediction and saliency maps in one stage, the image-level and pixel-level ground truth is trained in a same side output network. Supervision signal is imposed on each side layer to realize deeper and mixed training for the network. Furthermore, the DMS network is equipped with residual refinement mechanism to refine the saliency maps of input images. We evaluate the DMS network on 4 open access ASI datasets and compare it with other 20 methods, which indicates that mixed supervision can significantly improve the accuracy of saliency segmentation. Experiment results show that the proposed method can achieve the state-of-the-art performance

The Effect of the Chemical Composition on Mechanical Properties of CMAS Diopside Glass Ceramics

Molecular dynamics simulations were performed on CaO-MgO-Al2O3-SiO2 (CMAS) diopside glass ceramics (GCs) to study the effect of nanocrystal on glass and the effect of chemical composition on mechanical properties. Under tensile loading, the GCs demonstrated that the strength lay between its glass and ceramic counterparts and maintained considerable ductility. Moreover, high Mg/Ca ion ratios are conductive to both the strength and ductility of GCs. In addition, Al ions should be avoided as far as possible since they would promote fracture. After analyzing the shear strain and displacement vector map for ion structures, we found that the presence of nanocrystal in glass changes the original deformation pattern and led to the deformation concentration surrounding the nanocrystal. A high Mg/Ca ion ratio would make the deformation more homogeneous, while a high Ca/Mg ion ratio would aggregate the deformation in the glass region near the nanocrystal. The existence of Al ions near the interface between glass and crystal would promote the formation of voids

Construction of a Well-Defined S-Scheme Heterojunction Based on Bi-ZnFe₂O₄/S-g-C₃N₄ Nanocomposite Photocatalyst to Support Photocatalytic Pollutant Degradation Driven by Sunlight

Currently, organic dyes and other environmental contaminants are focal areas of research, with considerable interest in the production of stable, high-efficiency, and eco-friendly photocatalysts to eliminate these contaminants. In the present work, bismuth-doped zinc ferrite (Bi-ZnFe2O4) nanoparticles (NPs) and bismuth-doped zinc ferrites supported on sulfur-doped graphitic carbon nitride (Bi-ZnFe2O4/S-g-C3N4) (BZFG) photocatalysts were synthesized via a hydrothermal process. SEM, XRD, and FTIR techniques were used to examine the morphological, structural, and bonding characteristics of the synthesized photocatalysts. The photocatalytic competence of the functional BZFG nanocomposites (NCs) was studied against MB under sunlight. The influence of Bi (0.5, 1, 3, 5, 7, 9, and 11 wt.%) doping on the photocatalytic performance of ZnFe2O4 was verified, and the 9%Bi-ZnFe2O4 nanoparticles exhibited the maximum MB degradation. Then, 9%Bi-ZnFe2O4 NPs were homogenized with varying amounts of S-g-C3N4 (10, 30, 50, 60, and 70 wt.%) to further enhance the photocatalytic performance of BZFG NCs. The fabricated Bi-ZnFe2O4/30%S-g-C3N4 (BZFG-30) composite outperformed ZnFe2O4, S-g-C3N4 and other BZFG NCs in terms of photocatalytic performance. The enriched photocatalytic performance of the BZFG NCs might be ascribed to a more efficient transfer and separation of photo-induced charges due to synergic effects at the Bi-ZnFe2O4/S-g-C3N4 interconnection. The proposed modification of ZnFe2O4 using Bi and S-g-C3N4 is effective, inexpensive, and environmentally safe

Fabrication of Cr-ZnFe2O4/S-g-C3N4 Heterojunction Enriched Charge Separation for Sunlight Responsive Photocatalytic Performance and Antibacterial Study

There has been a lot of interest in the manufacture of stable, high-efficiency photocatalysts. In this study, initially Cr doped ZnFe2O4 nanoparticles (NPs) were made via surfactant-assisted hydrothermal technique. Then Cr-ZnFe2O4 NPs were modified by incorporating S-g-C3N4 to enhance their photocatalytic efficiency. The morphological, structural, and bonding aspects were analyzed by XRD, FTIR, and SEM techniques. The photocatalytic efficiency of the functional Cr-ZnFe2O4/S-g-C3N4 (ZFG) heterostructure photocatalysts was examined against MB under sunlight. The produced ZFG-50 composite has the best photocatalytic performance, which is 2.4 and 3.5 times better than that of ZnFe2O4 and S-g-C3N4, respectively. Experiments revealed that the enhanced photocatalytic activity of the ZFG nanocomposite was caused by a more effective transfer and separation of photo-induced charges. The ZFG photocatalyst can use sunlight for treating polluted water, and the proposed modification of ZnFe2O4 using Cr and S-g-C3N4 is efficient, affordable, and environmentally benign. Under visible light, Gram-positive and Gram-negative bacteria were employed to ZFG-50 NCs’ antimicrobial activity. These ZFG-50 NCs also exhibit excellent antibacterial potential