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ICML 2026 Workshop on Efficient Multimodal Question Answering

organizationactiveprovisionalicml-2026-workshop-on-efficient-multimodal-question-answering-c64a511a·1 events·first seen 11h ago

Aliases: ICML 2026 Workshop on Efficient Multimodal Question Answering

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GPT-4.1 mini OpenAI GPT-4.1 QANTA 2026

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4arXiv · cs.CL·11h ago·source ↗

Task-specific two-agent architecture wins QANTA 2026 multimodal QA challenge

Researchers present the top-scoring submission to the QANTA 2026 shared challenge at ICML 2026's EMM-QA Workshop, achieving an overall leaderboard score of 0.402 on multimodal quizbowl tasks. The system uses a two-agent architecture: a GPT-4.1-mini-based Tossup agent with confidence calibration and a GPT-4.1-based Bonus agent with structured relational and multimodal reasoning. Notably, the approach avoids retrieval pipelines and model ensembles, relying instead on lightweight task-specific reasoning policies under efficiency constraints. Results suggest that targeted reasoning strategies can be competitive on resource-constrained multimodal QA benchmarks.

Evaluation and Benchmarking Agent and Tool Ecosystem GPT-4.1 mini OpenAI GPT-4.1 +3 more