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Anjali Chaudhary

Publications and source records attributed to Anjali Chaudhary.

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Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we present Global PIQA, a participatory commonsense reasoning benchmark for over 100 languages, constructed by hand by over 350 researchers from over 65 countries around the world. The 141 language varieties in Global PIQA cover five continents, 19 language families, and 24 writing systems. In the non-parallel split of Global PIQA, over 50% of examples reference local foods, customs, traditions, or other culturally-specific elements. In the parallel split, we translate more "culturally agnostic" commonsense reasoning questions into 131 language varieties, for direct cross-lingual comparisons. In both splits, all examples have been verified by native speakers of the languages. We find that state-of-the-art LLMs perform well on Global PIQA in aggregate, but they exhibit weaker performance in lower-resource languages (e.g. up to a 68% accuracy gap between languages in the parallel split). Global PIQA highlights that in many languages and cultures, everyday knowledge remains an area for improvement in LLMs, alongside more widely-discussed capabilities such as complex reasoning and expert knowledge. Beyond its uses for LLM evaluation, Global PIQA provides a glimpse into the wide diversity of cultures in which human language is embedded.

cs.CL

Malignancy Induced Subtle Perturbation Sensitive Raman Scattering for Glioma Detection and Grading

Subtle changes in Raman spectral line-shape have been observed from malignant human brain cells and its possibility for being used in detection and grading of Glioma has been explored here. The latter has been developed as a result of the fact that the width of the Raman spectra is more sensitive, as compared to the peak position, to the brain tumors. The perturbations induced by the cell-modification, as a consequence to the cancerous growth, may be responsible for the widths variation in the Raman spectrum due to vibrational lifetime alteration enforced at the molecular levels. A consistent cancer induced effect on the spectral width has been observed for three different brain cells Raman modes at different frequencies . Raman spectral analysis reveals that for cancerous cells, the FWHM varies up to 35 % in comparison with the healthy cells. It has been established how a careful analysis of Raman spectra can help in easy detection of brain tumors. The methodology has been validated by studying the effect of similar microscopic perturbations, e.g, Fano coupling and quantum size effects, on different Raman spectral parameters which also reveals Raman width to be the most sensitive parameter.

physics.app-ph