The first benchmark for AI-generated scientific figure detection shows existing detectors fail in zero-shot transfer, overfit to specific generators, and break under common image corruptions.
arXiv preprint arXiv:2405.08807 , year=
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A multi-agent AI system generates novel biomedical hypotheses that show promising experimental validation in drug repurposing for leukemia, new targets for liver fibrosis, and a bacterial gene transfer mechanism.
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SciFigDetect: A Benchmark for AI-Generated Scientific Figure Detection
The first benchmark for AI-generated scientific figure detection shows existing detectors fail in zero-shot transfer, overfit to specific generators, and break under common image corruptions.
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PlanBench-V: A Spatial Planning Map Benchmark for Vision-Language Models
PlanBench-V is a new benchmark and dataset for evaluating VLMs on spatial planning map interpretation via a four-stage framework of Perception, Reasoning, Association, and Implementation.
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GENFIG1: Visual Summaries of Scholarly Work as a Challenge for Vision-Language Models
GENFIG1 is a new benchmark that tests whether vision-language models can create effective Figure 1 visuals capturing the central scientific idea from paper text.
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Towards an AI co-scientist
A multi-agent AI system generates novel biomedical hypotheses that show promising experimental validation in drug repurposing for leukemia, new targets for liver fibrosis, and a bacterial gene transfer mechanism.