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From the 1 of 9 papers with an AI index.

most citedChallenges in Synchronous & Remote Collaboration Around Visualization

1 citations

9 papers

cs.CV2026

What to Remove, What to Preserve: Dual-Ambiguity Rectification for All-in-One Image Restoration

Cencen Liu, Wen Yin, Dongyang Zhang +6

The paper introduces DAR-Net, a deep network that tackles the dual ambiguity problem in all‑in‑one image restoration by modeling degradation states with a simplex‑constrained arche…

cs.LG2026

Physical Self-Supervised Learning: IMU Sensing without Manual Labels

Yuyang Leng, Renyuan Liu, Shaohan Hu +4

Deep neural networks have become a promising approach for IMU-based sensing, but their scalability is fundamentally limited by costly labeled data and poor robustness to heterogene…

quant-ph2026

Spin-Boson Mapping of the Quantum Approximate Optimization Algorithm

Sami Boulebnane, Abid Khan, Minzhao Liu +4

The Quantum Approximate Optimization Algorithm (QAOA) achieves monotonically improving performance with circuit depth , yet the study of the high-depth regime has been obstructe…

cs.HC20261 cited

Challenges in Synchronous & Remote Collaboration Around Visualization

Matthew Brehmer, Maxime Cordeil, Christophe Hurter +26

We characterize 16 challenges faced by those investigating and developing remote and synchronous collaborative experiences around visualization. Our work reflects the perspectives…

cs.SE2026

Software Self-Extension with SelfEvolve: an Agentic Architecture for Runtime Code Generation

Md Asif Iqbal Fahim, Oluwadamilola Adebayo, Alessio Ferrari

Traditional self-adaptive systems automatically reconfigure existing components in response to changing requirements, but provide limited support for the generation of novel functi…

cs.LG20261 cited

A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning

Siyuan Guo, Yanchao Sun, Jifeng Hu +5

Offline reinforcement learning (RL) provides a promising solution to learning an agent fully relying on a data-driven paradigm. However, constrained by the limited quality of the o…