Differentiable nonlinear MPC computes parametric NLP sensitivities via IFT and smoothed IPM conditions within SQP, achieving over 3x speedups versus prior solvers.
STRABLE introduces 108 real-world string-and-number tables and benchmarks 445 pipelines, finding simple embeddings with advanced learners suffice for categorical tables while LLMs help on free-text tables.
MulTaBench benchmarks 40 multimodal tabular datasets and shows target-aware tuning of text and image embeddings improves predictive performance over frozen embeddings.
Temporal abstraction acts as a low-pass filter reducing effective successor representation rank to fix spectral mismatch in forward-backward representations and stabilize long-horizon continuous control learning.