355 citations · 2.7k across the 325 of their papers we have counts for
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LLM as a Neural Architect: Controlled Generation of Image Captioning Models Under Strict API Contracts
Krunal Jesani, Dmitry Ignatov, Radu Timofte
Neural architecture search (NAS) traditionally requires significant human expertise or automated trial-and-error to design deep learning models. We present NN-Caption, an LLM-guide…
Experts-Guided Unbalanced Optimal Transport for ISP Learning from Unpaired and/or Paired Data
Georgy Perevozchikov, Nancy Mehta, Egor Ershov +1
Learned Image Signal Processing (ISP) pipelines offer powerful end-to-end performance but are critically dependent on large-scale paired raw-to-sRGB datasets. This reliance on cost…
Enhancing LLM-Based Neural Network Generation: Few-Shot Prompting and Efficient Validation for Automated Architecture Design
Raghuvir Duvvuri, Chandini Vysyaraju, Avi Goyal +2
Automated neural network architecture design remains a significant challenge in computer vision. Task diversity and computational constraints require both effective architectures a…
A Retrieval-Augmented Generation Approach to Extracting Algorithmic Logic from Neural Networks
Waleed Khalid, Dmitry Ignatov, Radu Timofte
Reusing existing neural-network components is central to research efficiency, yet discovering, extracting, and validating such modules across thousands of open-source repositories…
Layover or Direct Flight: Rethinking Audio-Guided Image Segmentation
Joel Alberto Santos, Zongwei Wu, Xavier Alameda-Pineda +1
Understanding human instructions is essential for enabling smooth human-robot interaction. In this work, we focus on object grounding, i.e., localizing an object of interest in a v…
Sequence-Adaptive Video Prediction in Continuous Streams using Diffusion Noise Optimization
Sina Mokhtarzadeh Azar, Emad Bahrami, Enrico Pallotta +3
In this work, we investigate diffusion-based video prediction models, which forecast future video frames, for continuous video streams. In this context, the models observe continuo…