Papers by Hanani Bathina
Can Vision-Language Models Evaluate Handwritten Math? (2025.acl-long)
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| Challenge: | Recent advances in Vision-Language Models (VLMs) have significantly enhanced the ability to interpret both textual and visual data. |
| Approach: | They propose a benchmark to assess VLMs’ ability to detect, localize and correct errors in handwritten mathematical content. |
| Outcome: | The proposed benchmark covers over 2,200 handwritten math solutions from 609 manually curated problems from grades 7-12 with intentionally introduced perturbations. |