Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation

Language models have achieved impressive performances on dialogue generation tasks. However, when generating responses for a conversation that requires factual knowledge, they are far from perfect, due to an absence of mechanisms to retrieve, encode, and reflect the knowledge in the generated responses. Some knowledge-grounded dialogue generation methods tackle this problem by leveraging facts from Knowledge Graphs (KGs); however, they do not guarantee that the model utilizes a relevant piece of knowledge from the KG. To overcome this limitation, we propose SUbgraph Retrieval-augmented GEneration (SURGE), a framework for generating context-relevant and knowledge-grounded dialogues with the KG. Specifically, our SURGE framework first retrieves the relevant subgraph from the KG, and then enforces consistency across facts by perturbing their word embeddings conditioned by the retrieved subgraph. Then, we utilize contrastive learning to ensure that the generated texts have high similarity to the retrieved subgraphs. We validate our SURGE framework on OpendialKG and KOMODIS datasets, showing that it generates high-quality dialogues that faithfully reflect the knowledge from KG.Comment: Preprint. Under revie

Knowledge-Augmented Language Model Verification

Recent Language Models (LMs) have shown impressive capabilities in generating texts with the knowledge internalized in parameters. Yet, LMs often generate the factually incorrect responses to the given queries, since their knowledge may be inaccurate, incomplete, and outdated. To address this problem, previous works propose to augment LMs with the knowledge retrieved from an external knowledge source. However, such approaches often show suboptimal text generation performance due to two reasons: 1) the model may fail to retrieve the knowledge relevant to the given query, or 2) the model may not faithfully reflect the retrieved knowledge in the generated text. To overcome these, we propose to verify the output and the knowledge of the knowledge-augmented LMs with a separate verifier, which is a small LM that is trained to detect those two types of errors through instruction-finetuning. Then, when the verifier recognizes an error, we can rectify it by either retrieving new knowledge or generating new text. Further, we use an ensemble of the outputs from different instructions with a single verifier to enhance the reliability of the verification processes. We validate the effectiveness of the proposed verification steps on multiple question answering benchmarks, whose results show that the proposed verifier effectively identifies retrieval and generation errors, allowing LMs to provide more factually correct outputs. Our code is available at https://github.com/JinheonBaek/KALMV.Comment: EMNLP 202

Urodynamic and Histological Changes in a Sterile Rabbit Vesicoureteral Reflux Model

This study aimed to investigate pressure changes of renal pelvis and histological change of kidneys in a surgically induced sterile rabbit vesicoureteral reflux (VUR) model. Five rabbits served as a control group, 7 as the sham-operated group, and 8 served as the VUR group. Three weeks later, urodynamic studies were performed, and histological examinations evaluated degree of inflammation, fibrosis, and tubular damage in the kidneys. At a low infusion rate, renal pelvic pressure in the VUR group was stable until late filling phase and then increased slightly. At a high infusion rate, the renal pelvic pressures of the sham-operated and control groups were stable until late filling phase and then increased slightly, whereas the renal pelvic pressure in the VUR group steadily increased from mid filling phase. Focal thinning of the tubular epithelium and interstitial widening were observed in certain cortical areas of refluxing kidneys, without inflammatory cell infiltration. Obvious changes in the mean diameters of distal tubules and extracellular matrix volume fractions were observed in two highly refluxing kidneys. High pressure reflux with bladder instability may result in renal cortical changes

Simple but Effective Way To Enhance Photoelectrochemical Solar-Water-Splitting Performance of ZnO Nanorod Arrays: Charge-Trapping Zn(OH)2 Annihilation and Oxygen Vacancy Generation by Vacuum Annealing

This study presents an effective and the simplest method to substantially improve the photoelectrochemical water-splitting ability of hydrothermally grown ZnO nanorod arrays (NRAs). In the hydrothermal growth of ZnO NRAs, unwanted Zn(OH)(2) species are formed, which act as trapping sites of photoexcited charges. We found that those inherent charge-trapping sites could be annihilated by the desorption of the hydroxyl groups upon vacuum annealing above 200 degrees C, which resulted in an enhancement of the charge-separation efficiency and photocurrent density. Another drastic increase in the photocurrent density occurred when ZnO NRAs were treated with annealing at higher temperature (700 degrees C), which can be attributed to,the introduced oxygen vacancies acting, as shallow donors in the ZnO crystal lattice. The removal of the charge-trapping Zn(OH)(2) and the generation of oxygen vacancies were confirmed by photoluminescence (PL) and XPS analyses. The ZnO NRAs treated by this simple method yield a photocurrent density of 600 mu A/cm(2) at 1.23 V-RHE under 1 sun illumination, which is 20 times higher than that obtained from as-grown ZnO NRAs. This, study presents a highly efficient way of increasing the bulk electric conductivity and photoelectrochemical activity of metal oxide nanorods, without requiring the introduction of any extrinsic dopants.1122sciescopu

Fabrication of ZnO/CdS, ZnO/CdO core/shell nanorod arrays and investigation of their ethanol gas sensing properties

The sensing properties of ZnO/CdS and ZnO/Cd0 core/shell nanorod arrays were studied for ethanol gas sensing. ZnO nanorod arrays were synthesized on sputtered ZnO films through a simple hydrothermal method, and CdS films were then deposited on the ZnO nanorods by successive ionic layer adsorption and reaction (SILAR). After air annealing of the ZnO/CdS core/shell nanorods at 400 degrees C for 2h, the CdS films were converted to CdO films. Using scanning electron microscopy (SEM), X-ray diffraction (XRD), transmission electron microscopy (TEM) and diffused reflectance spectroscopy (DRS), ZnO/CdS and ZnO/CdO core/shell nanorod heterostructures were characterized. With respect to ethanol gas sensing, the ZnO/CdO core/shell nanorods exhibited highly enhanced responses compared to those of the ZnO/CdS core/shell nanorods. Based on the gas sensing mechanism, the effects of CdS and CdO shells on ZnO nanorod array gas sensors were discussed.1123Nsciescopu