A new benchmark called MissionBench reveals that even the strongest multimodal large language models (MLLMs) succeed on fewer than 35% of aerial missions, compared to 84.4% human performance, accordin…
Researchers introduced ADAPT, a framework that reduces hallucinations in multimodal large language models by up to 60% through refining text-to-image cross-attention dynamics. The approach uses a cros…
Researchers have introduced PaperGuard, the first comprehensive benchmark designed to systematically evaluate and defend AI-generated peer review against domain-specific, cross-modal attacks. The fram…
Researchers have developed Brick-Composer, a learning framework that enables multimodal large language models (MLLMs) to assemble objects from diverse building blocks by improving brick selection accu…
Multimodal large language models fail to infer how individual mental states interact and crystallize into group-level outcomes, according to a new benchmark called GroupToM-Bench. The benchmark, the f…