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+# SpecVQA: A Benchmark for Spectral Understanding and Visual Question Answering in Scientific Images
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+![SpecVQA 示例图](example/SpecVQA.jpg)
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+## 1. Background
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+Multimodal Large Language Models (MLLMs) have achieved notable progress in visual–language understanding and cross-modal reasoning, yet their capabilities remain limited when applied to the highly specialized task of spectral understanding. These limitations are further obscured by existing benchmarks, which either emphasize general object recognition or focus on simple chart-based data retrieval, lacking the scientific grounding needed to accurately assess or diagnose model performance in this domain.
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+To address this gap, we introduce SpecVQA, an expert-curated benchmark that targets the key failure modes of MLLMs in spectral interpretation. By focusing on seven essential spectrum types, it enables concise yet rigorous evaluation of scientific accuracy and domain-knowledge usage, providing clearer guidance for developing more domain-aware multimodal models. The seven spectrum types and their core interpretation requirements are:
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+
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+1. NMR (Nuclear Magnetic Resonance) involves interpreting chemical shifts ($\delta$), integration areas, coupling constants ($J$), and multiplicity to deduce molecular structures.
+2. IR (Infrared Absorption Spectroscopy) involves identifying characteristic vibrational frequencies ($\text{cm}^{-1}$) to determine the presence or absence of specific functional groups.
+3. XRD (X-ray Diffraction) requires analyzing diffraction peak positions ($2\theta$), intensities, and widths to infer crystal structures, lattice parameters, and crystallite sizes.
+4. Raman (Raman Spectroscopy) focuses on interpreting Raman-active vibrational modes to probe molecular symmetry and bonding characteristics, particularly in materials such as carbon-based systems.
+5. MS (Mass Spectrometry) involves analyzing molecular ion peaks and fragmentation patterns to determine molecular weight and identify structural fragments.
+6. UV-Vis (Ultraviolet-Visible Spectrophotometry) requires extracting maximum absorption wavelengths ($\lambda_{\text{max}}$) and quantifying concentrations based on absorption intensity.
+7. XPS (X-ray Photoelectron Spectroscopy) involves analyzing core-level peak binding energies to determine elemental composition and chemical states at the sample surface.
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+## 2. Details
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+To ensure the scientific validity and representativeness of the benchmark, a PhD team of domain experts manually curated a subset of **620 spectral figures** from 20k candidates collected from peer-reviewed journals and open-access scientific databases. The selection process was guided by six key criteria: Spectra Type, Image Structure, Text Completeness, Subplot Correlation, Sample Diversity and Resolution.