Good Papers

Showing papers from Norwegian University of Science and Technology Show all papers

45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026SoutheastNorwegian University of Science LLM reasoning & chain of thought

MinPath: Learning Efficient LLM Reasoning via Minimal Dependency Paths

Zhijing Yang, Shuming Hou, Guohui Xiao, Lemei Zhang and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
45%Niche pick
?Niche pickVote to see the score
NeurIPS 2026Norwegian University of Science Efficient & distributed training

Simplified Reversible Residual Networks

Erland B Olsson, Zhirong Yang

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
0/20 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: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
70%Highly rated
?Highly ratedVote to see the score
NeurIPS 2026University FreiburgAlbert-Ludwigs-Universität FreibNorwegian University of Science CS Department, University of FreU Freiburg, Albert-Ludwigs-UniveNavigation & SLAM

Differentiable Nonlinear Model Predictive Control

Differentiable nonlinear MPC computes parametric NLP sensitivities via IFT and smoothed IPM conditions within SQP, achieving over 3x speedups versus prior solvers.

Jonathan Frey, Katrin Baumgärtner, Gianluca Frison, Dirk Reinhardt and 5 more

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
5/20 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: 5 of 20 reviewers recommend it
lenient 2/5
medium 3/10
strict 0/5