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From the 1 of 7 linked papers with an AI index.

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7 papers

cs.CV2026

Holistic Optimal Label Selection for Robust Prompt Learning under Partial Labels

Yaqi Zhao, Haoliang Sun, Yating Wang +2

The paper introduces Holistic Optimal Label Selection (HopS), which combines a local density‑based filter with a global optimal‑transport objective to choose reliable labels for pr…

cs.LG2026

Riemannian MeanFlow for One-Step Generation on Manifolds

Zichen Zhong, Haoliang Sun, Yukun Zhao +2

Flow Matching enables simulation-free training of generative models on Riemannian manifolds, yet sampling typically still relies on numerically integrating a probability-flow ODE.…

cs.CV2026

Joint Semantic Token Selection and Prompt Optimization for Interpretable Prompt Learning

Yating Wang, Yaqi Zhao, Yongshun Gong +2

Vision-language models such as CLIP achieve strong visual-textual alignment, but often suffer from overfitting and limited interpretability when adapted through continuous prompt l…

cs.CL2026

Distributed Multi-Layer Editing for Rule-Level Knowledge in Large Language Models

Yating Wang, Wenting Zhao, Yaqi Zhao +3

Large language models store not only isolated facts but also rules that support reasoning across symbolic expressions, natural language explanations, and concrete instances. Yet mo…

cs.CV2026

EFF-Grasp: Energy-Field Flow Matching for Physics-Aware Dexterous Grasp Generation

Yukun Zhao, Zichen Zhong, Yongshun Gong +2

Denoising generative models have recently become the dominant paradigm for dexterous grasp generation, owing to their ability to model complex grasp distributions from large-scale…

cs.CL2026

From Text to Forecasts: Bridging Modality Gap with Temporal Evolution Semantic Space

Lehui Li, Yuyao Wang, Jisheng Yan +5

Incorporating textual information into time-series forecasting holds promise for addressing event-driven non-stationarity; however, a fundamental modality gap hinders effective fus…