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Work2Skill 提出一个框架，通过 WorkRecorder 收集人类 GUI 操作演示，构建 WorkDemo-350 多模态数据集，并用智能体式技能归纳方法从人类经验中提炼可复用的智能体技能，在 MyPCBench 和 OSWorld-Verified 上显著提升了多种执行模型的任务表现。
This paper introduces MultiHuSE, a multimodal dataset comprising videos of actors with annotations for humour styles and emotions. Baseline experiments show that multimodal fusion improves humour style classification accuracy over unimodal approaches.
WildCity introduces a large-scale multimodal dataset for city-scale urban navigation and spatial representation, collected by autonomous fleets. It provides 18 long trajectories and establishes baselines for reconstruction and closed-loop simulation to advance AI systems that can perceive and reason about city-scale environments.
Introduces DigitalCoach, a multimodal dataset of 72 human expert-novice computer use coaching sessions, and evaluates state-of-the-art models' ability to teach software skills. Models tend to give direct instructions without explanations or visual grounding, while human coaches provide more adaptive guidance.
Introduces MatMMExtract pipeline to decompose compound scientific figures into panels and annotate them using LLMs, creating the MatSciFig dataset of over 390,000 image-text pairs for vision-language learning in materials science.
KITScenes Multimodal is a high-fidelity European autonomous driving dataset with synchronized sensors, complete 3D HD maps, and four benchmarks for spatial learning and embodied AI research.
This paper introduces GroupAffect-4, a multimodal dataset of 40 participants in 10 four-person groups performing collaborative tasks. It includes aligned physiology, eye-tracking, audio, self-report, and personality data, along with benchmark targets for within-person, between-person, and group-level analysis.
BEACON is a large-scale multimodal dataset capturing behavioral signals from Valorant gameplay for continuous authentication and behavioral biometrics research.