MolRecBench-Wild reveals that 18 existing OCSR models suffer severe performance drops on complex real-world academic molecular images compared with prior patent benchmarks.
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InternVL 2.5 is the first open-source MLLM to surpass 70% on the MMMU benchmark via model, data, and test-time scaling, with a 3.7-point gain from chain-of-thought reasoning.
ChemVA framework uses hybrid-granularity visual anchors and entity-name alignment to improve LLM performance on chemical reaction diagrams by ~20 points, reaching 92% structural accuracy on the new OCRD-Bench dataset.
MolSeek-OCR reaches exact SMILES matching accuracy comparable to leading image-to-sequence OCSR models after two-stage fine-tuning on PubChem renderings and USPTO-MOL patent images, but remains below image-to-graph state-of-the-art.
citing papers explorer
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MolRecBench-Wild: A Real-World Benchmark for Optical Chemical Structure Recognition
MolRecBench-Wild reveals that 18 existing OCSR models suffer severe performance drops on complex real-world academic molecular images compared with prior patent benchmarks.
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Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
InternVL 2.5 is the first open-source MLLM to surpass 70% on the MMMU benchmark via model, data, and test-time scaling, with a 3.7-point gain from chain-of-thought reasoning.
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ChemVA: Advancing Large Language Models on Chemical Reaction Diagrams Understanding
ChemVA framework uses hybrid-granularity visual anchors and entity-name alignment to improve LLM performance on chemical reaction diagrams by ~20 points, reaching 92% structural accuracy on the new OCRD-Bench dataset.
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Fine-tuning DeepSeek-OCR-2 for Molecular Structure Recognition
MolSeek-OCR reaches exact SMILES matching accuracy comparable to leading image-to-sequence OCSR models after two-stage fine-tuning on PubChem renderings and USPTO-MOL patent images, but remains below image-to-graph state-of-the-art.