arXiv subjects

Di Mo

Publications and source records attributed to Di Mo.

5 recordsLinked to original sources

arXiv2026

Semantic Search At LinkedIn

Semantic search with large language models (LLMs) enables retrieval by meaning rather than keyword overlap, but scaling it requires major inference efficiency advances. We present LinkedIn's LLM-based semantic search framework for AI Job Search and AI People Search, combining an LLM relevance judge, embedding-based retrieval, and a compact Small Language Model trained via multi-teacher distillation to jointly optimize relevance and engagement. A prefill-oriented inference architecture co-designed with model pruning, context compression, and text-embedding hybrid interactions boosts ranking throughput by over 75x under a fixed latency constraint while preserving near-teacher-level NDCG, enabling one of the first production LLM-based ranking systems with efficiency comparable to traditional approaches and delivering significant gains in quality and user engagement.

cs.IR↗

arXiv2026

RECITYGEN -- Interactive and Generative Participatory Urban Design Tool with Latent Diffusion and Segment Anything

Urban design profoundly impacts public spaces and community engagement. Traditional top-down methods often overlook public input, creating a gap in design aspirations and reality. Recent advancements in digital tools, like City Information Modelling and augmented reality, have enabled a more participatory process involving more stakeholders in urban design. Further, deep learning and latent diffusion models have lowered barriers for design generation, providing even more opportunities for participatory urban design. Combining state-of-the-art latent diffusion models with interactive semantic segmentation, we propose RECITYGEN, a novel tool that allows users to interactively create variational street view images of urban environments using text prompts. In a pilot project in Beijing, users employed RECITYGEN to suggest improvements for an ongoing Urban Regeneration project. Despite some limitations, RECITYGEN has shown significant potential in aligning with public preferences, indicating a shift towards more dynamic and inclusive urban planning methods. The source code for the project can be found at RECITYGEN GitHub.

cs.CV↗

arXiv2025

Trading off Relevance and Revenue in the Jobs Marketplace: Estimation, Optimization and Auction Design

We study the problem of position allocation in job marketplaces, where the platform determines the ranking of the jobs for each seeker. The design of ranking mechanisms is critical to marketplace efficiency, as it influences both short-term revenue from promoted job placements and long-term health through sustained seeker engagement. Our analysis focuses on the tradeoff between revenue and relevance, as well as the innovations in job auction design. We demonstrated two ways to improve relevance with minimal impact on revenue: incorporating the seekers preferences and applying position-aware auctions.

cs.GT↗

arXiv2024

Alternative sum rules and waterbed effects of Lorentz resonator system for sound absorption and transmission in a unidimensional waveguide

We investigate fundamental constraints on passive linear time-invariant acoustic systems through the developing alternative linear sum rules for sound absorption and transmission. Our approach, based on the Herglotz function method, yields integral identities without non-linear logarithmic terms or frequency weightings, providing clearer physical insights into system performance limits. The study focuses on unidimensional waveguides with Lorentz resonators, encompassing various practical acoustic structures. The developed sum rules are found to be particularly effective in predicting constraints on the average sound absorption coefficient for broadband absorbers operating in deep-subwavelength structures. Based on these rules, we demonstrate the waterbed effect in such systems, highlighting the inherent compromises between absorption efficiency, bandwidth, and device thickness. Through case studies of resonator arrays and membranes, we illustrate the practical implications of these new sum rules for designing optimal sound absorbers and isolators. The work concludes with a discussion on the challenges and future prospects in passive noise control, suggesting potential pathways to surpass current performance boundaries.

physics.class-ph↗

arXiv2024

The Role of Urban Designers in the Era of AIGC: An Experimental Study Based on Public Participation

This study explores the application of Artificial Intelligence Generated Content (AIGC) technology in urban planning and design, with a particular focus on its impact on placemaking and public participation. By utilizing natural language pro-cessing and image generation models such as Stable Diffusion, AIGC enables efficient transformation from textual descriptions to visual representations, advancing the visualization of urban spatial experiences. The research examines the evolving role of designers in participatory planning processes, specifically how AIGC facilitates their transition from traditional creators to collaborators and facilitators, and the implications of this shift on the effectiveness of public engagement. Through experimental evaluation, the study assesses the de-sign quality of urban pocket gardens generated under varying levels of designer involvement, analyzing the influence of de-signers on the aesthetic quality and contextual relevance of AIGC outputs. The findings reveal that designers significantly improve the quality of AIGC-generated designs by providing guidance and structural frameworks, highlighting the substantial potential of human-AI collaboration in urban design. This research offers valuable insights into future collaborative approaches between planners and AIGC technologies, aiming to integrate technological advancements with professional practice to foster sustainable urban development.

cs.HC↗