FEC: Three Finetuning-free Methods to Enhance Consistency for Real Image Editing

Text-conditional image editing is a very useful task that has recently emerged with immeasurable potential. Most current real image editing methods first need to complete the reconstruction of the image, and then editing is carried out by various methods based on the reconstruction. Most methods use DDIM Inversion for reconstruction, however, DDIM Inversion often fails to guarantee reconstruction performance, i.e., it fails to produce results that preserve the original image content. To address the problem of reconstruction failure, we propose FEC, which consists of three sampling methods, each designed for different editing types and settings. Our three methods of FEC achieve two important goals in image editing task: 1) ensuring successful reconstruction, i.e., sampling to get a generated result that preserves the texture and features of the original real image. 2) these sampling methods can be paired with many editing methods and greatly improve the performance of these editing methods to accomplish various editing tasks. In addition, none of our sampling methods require fine-tuning of the diffusion model or time-consuming training on large-scale datasets. Hence the cost of time as well as the use of computer memory and computation can be significantly reduced

Research on the impact of green finance on carbon emissions: evidence from China

Green finance is an effective means adopted by the Chinese government to reduce carbon emissions. Does the development of green finance in Chinese provinces reduce carbon emissions to a certain extent? This study selects panel data of various provinces and cities in China from 2003 to 2019. Based on the Hansen threshold regression model, an empirical analysis is conducted with economic growth and industrial structure as threshold variables to test the impact of green finance on carbon emissions. The results show that green finance increases the speed of carbon emission mitigation when PGDP is the threshold. Taking industrial structure as the threshold, the impact of green finance development on carbon emissions presents an inverted N shape. At the same time, it is found that green finance has become an important means to reduce carbon emissions in the eastern region, the impact of green finance on carbon emissions in the central region presents an inverted U shape, and the driving force of green finance on carbon emission reduction in the western region is weak. Furthermore, it is pointed out that improving the quality of green finance and enhancing the level of green finance empowered by science and technology are the keys to realizing sustainable green development

KV Inversion: KV Embeddings Learning for Text-Conditioned Real Image Action Editing

Text-conditioned image editing is a recently emerged and highly practical task, and its potential is immeasurable. However, most of the concurrent methods are unable to perform action editing, i.e. they can not produce results that conform to the action semantics of the editing prompt and preserve the content of the original image. To solve the problem of action editing, we propose KV Inversion, a method that can achieve satisfactory reconstruction performance and action editing, which can solve two major problems: 1) the edited result can match the corresponding action, and 2) the edited object can retain the texture and identity of the original real image. In addition, our method does not require training the Stable Diffusion model itself, nor does it require scanning a large-scale dataset to perform time-consuming training

DREditor: An Time-efficient Approach for Building a Domain-specific Dense Retrieval Model

Deploying dense retrieval models efficiently is becoming increasingly important across various industries. This is especially true for enterprise search services, where customizing search engines to meet the time demands of different enterprises in different domains is crucial. Motivated by this, we develop a time-efficient approach called DREditor to edit the matching rule of an off-the-shelf dense retrieval model to suit a specific domain. This is achieved by directly calibrating the output embeddings of the model using an efficient and effective linear mapping. This mapping is powered by an edit operator that is obtained by solving a specially constructed least squares problem. Compared to implicit rule modification via long-time finetuning, our experimental results show that DREditor provides significant advantages on different domain-specific datasets, dataset sources, retrieval models, and computing devices. It consistently enhances time efficiency by 100-300 times while maintaining comparable or even superior retrieval performance. In a broader context, we take the first step to introduce a novel embedding calibration approach for the retrieval task, filling the technical blank in the current field of embedding calibration. This approach also paves the way for building domain-specific dense retrieval models efficiently and inexpensively.Comment: 15 pages, 6 figures, Codes are available at https://github.com/huangzichun/DREdito

Spatial and temporal variation of north-west pacific tropical cyclone under the background of upper ocean warming

879-885Under the background of global warming, the activities of north-west pacific (NWP) tropical cyclones (TCs) are undergoing significant changes. The TC frequencies have been characterized by an initial slow increase followed by a rapid increase and then a decrease, the past 33 years. During the 21st century, the TC frequency of the NWP has clearly decreased. However, the three TC origin types in the NWP have experienced different types of changes. The TC frequencies of origin 1 (10°~22°N,110°~120°E) and origin 2 (8°~20°N,125°~145°E) are both increasing, but the TC frequency of origin 3 (5°~20°N,145°~155°E) is decreasing. Under the background of upper ocean warming, the average TC duration has shown a decreasing trend (-0.27d/10a), while the TC mean and maximum intensity has increased (0.93 m/s/10a and 1.57 m/s/10a, respectively). Therefore, the potential threats of TC activities to NWP coastal countries are likely to intensify. The changes in the thermal state of the upper ocean have many effects on TC activities. Sea surface temperature is not the main factor affecting the frequency of TCs. However, the response of TCs to the upper ocean heat content is obvious