Good Papers

Showing papers from Friedrich-Alexander Universität Erlangen-Nürnberg Show all papers

80%Must read
?Must readVote to see the score
NeurIPS 2026Friedrich-Alexander University oFriedrich-Alexander Universität Representation & contrastive learning

Rethinking Neural Nonlinearity as Gating

Standard neural activations are instances of input-conditioned threshold gating, enabling lossless pretrained conversion and hardware-efficient training.

MUHAMMAD SABIH, Frank Hannig, Jürgen Teich

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
12/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 12 of 20 reviewers recommend it
lenient 4/5
medium 7/10
strict 1/5
72%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026Friedrich-Alexander Universität U WuerzburgU OxfordTechnical University of MunichDeep learning theory

Quantifying Concentration Phenomena of Mean-Field Transformers in the Low-Temperature Regime

Mean-field transformers exhibit rapid token distribution concentration onto projection-driven limits with explicit Wasserstein bounds scaling in inverse temperature β and time t.

Albert Alcalde, Leon Bungert, Konstantin Riedl, Tim Roith

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
8/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 8 of 20 reviewers recommend it
lenient 2/5
medium 4/10
strict 2/5