Soohak is a new 439-problem mathematician-authored benchmark showing frontier LLMs reach only 30% on research math and fail to exceed 50% on refusing ill-posed questions.
InACM MM, pages 6501–6509
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TEMA is the first framework for multi-modification composed image retrieval, using entity mapping to improve accuracy on both new complex datasets and existing benchmarks while balancing efficiency.
SemanticQA is a unified benchmark that reveals substantial performance gaps in language models on semantic reasoning tasks involving multiword expressions.
citing papers explorer
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Soohak: A Mathematician-Curated Benchmark for Evaluating Research-level Math Capabilities of LLMs
Soohak is a new 439-problem mathematician-authored benchmark showing frontier LLMs reach only 30% on research math and fail to exceed 50% on refusing ill-posed questions.
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TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrieval
TEMA is the first framework for multi-modification composed image retrieval, using entity mapping to improve accuracy on both new complex datasets and existing benchmarks while balancing efficiency.
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Revisiting a Pain in the Neck: A Semantic Reasoning Benchmark for Language Models
SemanticQA is a unified benchmark that reveals substantial performance gaps in language models on semantic reasoning tasks involving multiword expressions.