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QANTA 2026 Challenge: Task-Specific Multimodal QA Agents with Confidence Calibration

A team submitted a system to the QANTA 2026 shared challenge at ICML 2026, addressing multimodal quizbowl questions with incremental text and images. The system uses confidence calibration for tossup questions and incremental reasoning for bonus questions, aiming to balance accuracy and efficiency.

0 engagement·1 source·Fri, Jul 10, 2026, 05:22 PM
The submission targets the QANTA 2026 challenge at the ICML 2026 Workshop on Efficient Multimodal Question Answering (EMM-QA). The challenge features two tasks: Tossup questions (deciding when to answer under uncertainty) and Bonus questions (accurate answer selection with human adoption). The system employs task-specific strategies: confidence calibration for tossups and incremental reasoning for bonuses. No specific model names, parameter counts, or benchmark numbers are provided in the post.

Entities

QANTA 2026(benchmark)ICML 2026 Workshop on Efficient Multimodal Question Answering(concept)confidence calibration(concept)incremental reasoning(concept)

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