Personalized recommendation is widely applicable in various domains like e-commerce and social media. Few recent research efforts have attempted to design general large language model (LLM) based recommenders to alleviate the issue of data ...

Job recommender systems are crucial for aligning job opportunities with job-seekers in online job-seeking. However, users tend to adjust their job preferences to secure employment opportunities continually, which limits the performance of job ...

We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods. We unveil several modeling improvements, including Residual DCN, which adds attention and residual ...

Large Language Models (LLMs) have emerged as powerful tools in the field of Natural Language Processing (NLP) and have recently gained significant attention in the domain of Recommendation Systems (RS). These models, trained on massive amounts of ...

The overwhelming surge of online video platforms has raised an urgent need for social interaction recognition techniques. Compared with simple short-term actions, long-term social interactions in semantic-rich videos could reflect more complicated ...

Text patterns typically exhibit distinct boundaries and sparse color histograms. However, in current hybrid codec frameworks, the positions of coding units are often misaligned with the text patterns, resulting in prediction and color mapping tools ...

Target detection is pivotal for modern urban computing applications. While image-based techniques are widely adopted, they falter under challenging environmental conditions such as adverse weather, poor lighting, and occlusion. To improve the ...

Instruction tuning is an effective technique to align large language models (LLMs) with human intents. In this work, we investigate how an adversary can exploit instruction tuning by injecting specific instruction-following examples into the training ...

With the booming of streaming media platforms, viewers now get used to watching dramas and movies via online platforms with more intelligent services. Usually, character relationships may dynamically evolve with stories promoting in long videos. Therefore,...

The recent development of recommender systems has a focus on collaborative ranking, which provides users with a sorted list rather than rating prediction. The sorted item lists can more directly reflect the preferences for users and usually perform better ...

Due to inherent interactivity, time-sync comment of videos have attracted increasing attention and were widely adopted in online video platforms. In addition to enhancing user engagement, time-sync comments provide abundant semantic information that can ...

Non-orthogonal multiple access (NOMA) has drawn much attention due to its capability in massive connections. It enables various joint designs with advanced technologies, e.g., cooperative transmission and aerial base station (ABS)-assisted networks. In ...

To enhance the performance of the Dynamic Window Approach (DWA) algorithm in complex obstacle environments and address its inability to handle negative-weighted edge graphs, this study proposes a path-planning algorithm that combines DWA with informed ...

Recent years have witnessed the booming of online social media platforms with embracing the popular service called “Time-Sync Comment”, which supports the viewers to share their time-sync opinions along with video content. In this way, we observe that ...

Incorporating physics in human motion capture to avoid artifacts like floating, foot sliding, and ground penetration is a promising direction. Existing solutions always adopt kinematic results as reference motions, and the physics is treated as a post-...

Multimodal entity linking (MEL) task, which aims at resolving ambiguous mentions to a multimodal knowledge graph, has attracted wide attention in recent years. Though large efforts have been made to explore the complementary effect among multiple ...

• Two horizontal low-carbon supply chain models are proposed.
• Double carbon ...

Under double carbon policies, this study proposes a horizontal low-carbon supply chain involving a traditional manufacturer and a low-carbon manufacturer. On this basis, we develop two scenarios, which differ in whether the traditional ...

Heterogeneous trajectory forecasting is critical for intelligent transportation systems, but it is challenging because of the difficulty of modeling the complex interaction relations among the heterogeneous road agents as well as their agent-environment ...

This study investigates the impact of government R&D spending on promoting technology convergence. We test the hypotheses that a government funding program positively affects technology convergence, and that the effects vary depending on the ...

Reconfigurable intelligent surfaces (RIS) have attracted a great deal of interests due to its potential contributions to the next-generation mobile networks. The deployment of RIS in multi-user wireless networks promises to reduce system hardware ...