Jiahao Tang, Henry Hengyuan Zhao, Lijian Wu, Zijian Zhang, Yifei Tao, Dongxing Mao, Yang Wan, Jingru Tan, Min Zeng, Min Li, Alex Jinpeng Wang. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

The Industrial Internet platform-based manufacturing service collaboration has made it possible for decentralized manufacturing enterprises to cooperate on a broad scale. The selection conflict problem may arise when many providers choose the same task at the same time, especially when there are more providers than consumers. At this moment, how to choose the appropriate manufacturing services, which should both satisfy the users’ requirements and enhance the participation of the providers, is of utmost importance. To increase the number of collaboration chances, the functional and quantitative manufacturing service collaboration is carried out simultaneously in this article. The variable utility models are used to represent the satisfaction levels of users while taking into account the bilateral coupling between providers and consumers and the unilateral irrationality of the provider. Finally, it is advised to choose providers with a short-term preference in situations where there is a strict time limit based on the findings and analysis of the manufacturing service collaboration optimization. At the same time, we can find that the providers, who get lower utilities when they focus on the current, are more likely to get greater utilities than others when they concentrate on long-term gains.

Fingerprinting indoor localization systems exploit wireless signal propagation features to estimate the location of wireless devices, where the major challenge in practice is the all-consuming training process: it requires site survey to establish the mapping between the signal feature and the location where the feature is observed. In this paper, we present a Wi-Fi localization scheme based on channel state information (CSI) of wireless signals, which manages to relieve time-consuming site survey. In particular, we first propose how to automatically generate the theoretical fingerprints database based on the signal propagation model and geometric methods. Localization with the theoretical fingerprints database yields accuracy close to existing methods. Second, we improve localization accuracy by parsing the user's trajectory instead of restricting to the single spot, where human movement features introduce more information for localization. Third, we present an automatic update scheme for the theoretical fingerprints database to improve time efficiency for localization, which can save 94 - 98% processing time for utilizing the CSI fingerprints database. We implement a prototype with COTS devices and conduct comprehensive experiments to verify proposed mechanisms. Results show that our design achieves 80% localization errors within 0.3m, which is 3× accuracy compared with the state-of-the-art design leveraging CSI.

Low power is widely considered as a key benefit of 3D ICs, yet there have been few thorough design studies on how to maximize power benefits in 3D ICs. In this paper, we present design methodologies to reduce power consumption in 3D ICs using a large-scale commercial-grade microprocessor (OpenSPARC T2). To further improve power benefits in 3D ICs on top of the traditional 3D floorplanning, we study the impact of block folding and bonding styles. We also develop an effective method to place face-to-face vias for our 2-tier 3D design for power optimization. With aforementioned methods combined, our 3D designs provide up to 20.3% power reduction over the 2D counterpart under the same performance.

In this paper, we present a transient modeling of electromigration (EM) in TSV and TSV-to-wire interfaces in the power delivery network (PDN) of 3D ICs. In particular, we model atomic depletion and accumulation, effective resistance degradation, and full chip-scale PDN lifetime degradation due to EM. Our major focuses are on: (1) time-dependent multi-physics EM modeling approach to model TSVs and connecting wires under the influence of coupled physical phenomenon including electric field, temperature, and stress; (2) time-dependent EM-aware power integrity analysis methodology, which is integrated with the TSV modeling approach to predict long-term IR-drop degradation in full-chip 3D power delivery networks. Our studies show that voids and hillocks grow at various TSV-to-wire interfaces and degrade the effective resistance of TSVs significantly. In addition, our full-chip PDN lifetime analysis shows significant increase in maximum IR drop during lifetime due to EM effects.

We study the problem of topic-level social network search, which aims to find who are the most influential users in a network on a specific topic and how the influential users connect with each other. We employ a topic model to find topical aspects of each user and a retrieval method to identify influential users by combining the language model and the topic model. An influence maximization algorithm is then presented to find the sub network that closely connects the influential users. Two demonstration systems have been developed and are online available. Empirical analysis based on the user's viewing time and the number of clicks validates the proposed methodologies.