VLRS-Bench is the first benchmark dedicated to complex vision-language reasoning in remote sensing, with 2000 QA pairs across 14 tasks in cognition, decision, and prediction dimensions.
Mmbench: Is your multi-modal model an all-around player? InEuropean conference on computer vi- sion, pages 216–233
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WildFireVQA is a new large-scale visual question answering benchmark that pairs RGB imagery with radiometric thermal measurements for aerial wildfire monitoring across six task categories.
CaptionQA is a new benchmark with 33,027 questions across natural, document, e-commerce, and embodied AI domains that measures how much utility model-generated captions retain compared to original images when used by LLMs for downstream tasks.
Argos is an agentic verifier that adaptively picks scoring functions to evaluate accuracy, localization, and reasoning quality, enabling stronger multimodal RL training for AI agents.
citing papers explorer
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VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing
VLRS-Bench is the first benchmark dedicated to complex vision-language reasoning in remote sensing, with 2000 QA pairs across 14 tasks in cognition, decision, and prediction dimensions.
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WildFireVQA: A Large-Scale Radiometric Thermal VQA Benchmark for Aerial Wildfire Monitoring
WildFireVQA is a new large-scale visual question answering benchmark that pairs RGB imagery with radiometric thermal measurements for aerial wildfire monitoring across six task categories.
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CaptionQA: Is Your Caption as Useful as the Image Itself?
CaptionQA is a new benchmark with 33,027 questions across natural, document, e-commerce, and embodied AI domains that measures how much utility model-generated captions retain compared to original images when used by LLMs for downstream tasks.
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Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents
Argos is an agentic verifier that adaptively picks scoring functions to evaluate accuracy, localization, and reasoning quality, enabling stronger multimodal RL training for AI agents.