Keywords
vision-in-the-loop
active visual acquisition
long-horizon search
simulation
Abstract
The evidence base for vision-in-the-loop search spans Universal Multimodal Neural Machine Translation Via Image Retrieval from Search Engines, while related work on Visual Image Browsing and Exploration (Vibe): User Evaluations of Image Search… and ISE: Interactive Image Search using Visual Content broadens the methodological context. The discussion uses evaluation protocols, search intent, and visual localization as analytical lenses. Rather than ranking reported results, it examines which claims remain comparable across tasks, datasets, and operating conditions. By aligning terminology and evidence requirements, the article offers a more defensible basis for future empirical work. The final recommendations focus on traceable data, bounded claims, and evaluation under meaningful operating conditions.
References
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