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Current VLMs ace diagram question answering, but DRAGON reveals they often fake it, failing to ground their answers in the actual visual evidence.
LLMs are revolutionizing conversational AI research, and this survey offers a structured guide to navigating the rapidly evolving landscape of LLM-powered user simulation.
Agentic RAG systems can be made significantly more efficient and accurate simply by adding a contextualization module and de-duplicating retrieved documents at test time.
Finally, AI can generate hour-long videos with consistent characters and backgrounds, thanks to a new framework that nails seamless transitions between shots.
LLM judges exhibit a surprising "blindness" to human-written summaries, increasingly preferring machine-generated content as the similarity to human references decreases, challenging their reliability in summarization tasks.
