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Jing Tang

7 papers indexed

openalexCell Communication and Signaling2026-07-24

Lactylation in cancer: a new frontier in metabolic-epigenetic regulation and clinical practice

Yihan Zhang, Lan Chen, Yaxi Qin, Yuxing Wang, Xi Liu, Minghui Zhang, et al.

The discovery of lysine lactylation (Kla) redefines lactate from a passive glycolytic by-product into a bioactive metabolic mediator that directly links cellular metabolism to epigenetic regulation. This emerging post-translational modification dynamically alters histone and non-…

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arxivcs.CV2026-07-22

STEREOFLOW: Progressive Stereo Matching with StereoDiT and Transition Flow Matching

Hao Wang, Haoran Geng, Xiaotong Yang, Jing Tang, Songlin Wei, Linlong Lang, et al.

Stereo matching is a fundamental task in 3D reconstruction. Despite remarkable advances, the prevailing paradigms formulate stereo matching as a deterministic regression problem, collapsing the multimodal distribution modeling into a single-point estimation. This formulation suff…

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arxivcs.AI2026-07-19

LenGuard-GPC: Length Guarding with Guided-Prompt Consistency for Spatial Reasoning Reinforce Learning

Xingjian Tao, Yiwei Wang, Yujun Cai, Jing Tang

Multi-view spatial reasoning requires vision-language models to compare visual evidence across images, align object correspondences, and infer spatial relations over long visual contexts, a setting where chain-of-thought reasoning tends to grow verbose without becoming more accur…

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arxivcs.CV2026-07-15

Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment

Geng Li, Haiwen Li, Rui Chen, Jing Tang, Lei Sun, Xiangxiang Chu

Video aesthetic assessment (VAA) aims to predict how aesthetically pleasing a video is, yet remains far less explored than other visual assessment tasks. Its progress is hindered not only by the scarcity of large-scale benchmarks, but also by the intrinsic subjectivity of aesthet…

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arxivcs.AIcs.CE2026-07-14

EVOQUANT: Self-Evolving Verifier-Guided Strategy Optimization for Robust Quantitative Trading

Jie Mao, Changlun Li, Xiang Li, Qiqi Duan, Jinhui Yuan, Xiang Liu, et al.

Quantitative strategy optimization remains largely manual, requiring domain experts to identify weak signals, tune risk-control rules, and repeatedly validate iterative revisions. Large language models can accelerate this process, but directly relying on them to rewrite trading s…

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crossrefFuture Internet2026-06-16

Computing Incentive and Data Offloading in Digital Twin Networks: A Contract Theory and Multi-Agent Deep Reinforcement Learning Approach

Nan Zhao, Henan Xu, Yuxiang Su, Bokun He, Fan Zhang, Jing Tang, et al.

In the digital twin (DT) network, effective edge data processing is essential to meet the real-time requirements of DT models. However, edge servers (ESs) are self-interested and have limited computation resources. The virtual content operator (VCO) cannot observe their true comp…

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