Showing papers from University of Bonn Show all papers
Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026
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Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026
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E²-TTT derives a closed-form chunk-level state transition that exactly reproduces per-token update dynamics, enabling parallel training that retains temporal structure, matches chunk-wise throughput, and achieves over 90% needle-in-a-haystack accuracy at 8× training length.
Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026 · ▲ 2 on Hugging Face · Code ★ 4
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