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From the 1 of 11 linked papers with an AI index.

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11 papers

cs.CV2026

Why Low-Light Cameras Go Color Blind: Removing Color Bias in Raw Denoising

Mohammad Mohammadi, Sina Honari, Stavros Tsogkas +6

The paper introduces a calibration‑free approach for low‑light raw image denoising that first estimates and removes color bias caused by black‑level errors, improving color fidelit…

cs.CV2026

AVIS: Adaptive Test-Time Scaling for Vision-Language Models

Ahmadreza Jeddi, Minh Ngoc Le, Amirhossein Kazerouni +8

Modern Vision-Language Models (VLMs) benefit from chain-of-thought prompting and test-time scaling, but these gains often come with prohibitive inference cost due to large visual c…

cs.NE2026

GEAR: Genetic AutoResearch for Agentic Code Evolution

Ahmadreza Jeddi, Minh Ngoc Le, Hakki C. Karaimer +2

Autonomous research agents can already run machine learning experiments without human supervision, but many rely on a narrow search strategy: they repeatedly modify one program and…

cs.CV2026

BurstGP: Enhancing Raw Burst Image Super Resolution with Generative Priors

Dong Huo, Tristan Aumentado-Armstrong, Samrudhdhi B. Rangrej +8

Burst image super resolution (BISR) aims to construct a single high-resolution (HR) image by aggregating information from multiple low-resolution (LR) frames, relying on temporal r…

cs.CV2026

Face2Scene: Using Facial Degradation as an Oracle for Diffusion-Based Scene Restoration

Amirhossein Kazerouni, Maitreya Suin, Tristan Aumentado-Armstrong +6

Recent advances in image restoration have enabled high-fidelity recovery of faces from degraded inputs using reference-based face restoration models (Ref-FR). However, such methods…

cs.CV2026

Universal Sparse Autoencoders: Interpretable Cross-Model Concept Alignment

Harrish Thasarathan, Julian Forsyth, Thomas Fel +2

We present Universal Sparse Autoencoders (USAEs), a framework for uncovering and aligning interpretable concepts spanning multiple pretrained deep neural networks. Unlike existing…