Isaac Robinson — accepted AI-conference papers

2026

RF-DETR: Neural Architecture Search for Real-Time Detection Transformers

Isaac Robinson, Peter Robicheaux, Matvei Popov, Deva Ramanan, Neehar Peri

ICLR 2026poster

Open-vocabulary detectors achieve impressive performance on COCO, but often fail to generalize to real-world datasets with out-of-distribution classes not typically found in their pre-training. Rather than simply fine-tuning a heavy-weight vision-language model (VLM) for new domains, we introduce RF…

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2025

Roboflow100-VL: A Multi-Domain Object Detection Benchmark for Vision-Language Models

Matvei Popov, Peter Robicheaux, Anish Madan, Isaac Robinson, Joseph Nelson, Deva Ramanan +1

NeurIPS 2025poster

Vision-language models (VLMs) trained on internet-scale data achieve remarkable zero-shot detection performance on common objects like car, truck, and pedestrian. However, state-of-the-art models still struggle to generalize to out-of-distribution classes, tasks and imaging modalities not typically…

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