A study of ChatGPT, Claude, Grok, and DeepSeek finds that searching the Web more often does not necessarily improve answer quality, which matters if you rely on these agents for research. The researchers tracked when agents searched, how they formed queries, which domains their platform-specific search engines returned, and how results became answers. Responses were mostly grounded in search results, but some claims relied on uncited results, creating attribution and reliability concerns.
FLAT gives image and text models one shared sequence of up to 256 continuous tokens, so the same representation can power retrieval, captioning, and image generation instead of separate systems. Nested dropout orders those tokens from broad meaning to fine detail: use a short prefix for cheaper, coarse results, or add tokens to recover composition and attributes. The page reports 83.1 GenEval and 138.6 COCO CIDEr, while COCO retrieval changes by less than one point from one token to 256.