{ "paper": { "title": "Attention Is All You Need", "authors": "Ashish Vaswani et al.", "arxiv_id": "1706.03762", "pdf_url": "https://arxiv.org/pdf/1706.03762", "pdf_sha256": "bdfaa68d8984f0dc02beaca527b76f207d99b666d31d1da728ee0728182df697", "observed_pdf_sha256": "bdfaa68d8984f0dc02beaca527b76f207d99b666d31d1da728ee0728182df697" }, "paper_text": { "path": "/Users/boj/book/ai-agent-book/chapter5/paper-to-ppt/validation/runs/exp5-4-real-pdf-both-20260730-v6/source/paper_text.md", "sha256": "4da5f2a1da38bad8149832b5ada3c94f0619188db8fed5cdca8ff63405587eb8", "characters": 39819 }, "visuals": [ { "filename": "paper_figure_1_transformer.png", "pdf_page": 3, "source_label": "Figure 1", "caption": "The Transformer model architecture.", "rect": [ 92, 60, 520, 405 ], "sha256": "09364ee993caf62234733a5aaacc31bc0472b8db4b6107455f898e3a7a020597", "bytes": 94487, "public_copy_sha256": "09364ee993caf62234733a5aaacc31bc0472b8db4b6107455f898e3a7a020597" }, { "filename": "paper_figure_3_long_distance.png", "pdf_page": 13, "source_label": "Figure 3", "caption": "Encoder self-attention following long-distance dependencies.", "rect": [ 92, 88, 525, 311 ], "sha256": "40bfb903dbadbcb20d3243defced540f9dc9d777e4de4061698865fb13878207", "bytes": 57364, "public_copy_sha256": "40bfb903dbadbcb20d3243defced540f9dc9d777e4de4061698865fb13878207" }, { "filename": "paper_figure_4_anaphora.png", "pdf_page": 14, "source_label": "Figure 4 (lower attention panel)", "caption": "A published attention head involved in anaphora resolution.", "rect": [ 92, 360, 525, 610 ], "sha256": "677e0c16942c3fab738b1ba34d8b205f04a71b842c372e32f6fbd795d2222e1e", "bytes": 48423, "public_copy_sha256": "677e0c16942c3fab738b1ba34d8b205f04a71b842c372e32f6fbd795d2222e1e" } ] }