Flat minima are illusory; generalization is driven by weakness, a reparameterization-invariant measure of compatible completions that predicts performance better than sharpness on MNIST and Fashion-MNIST.
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A formal basis for the heuristic determination of minimum cost paths
15 Pith papers cite this work. Polarity classification is still indexing.
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Tree of Thoughts enables language models to solve complex planning tasks by generating, evaluating, and searching over coherent intermediate thoughts in a tree, raising Game of 24 success from 4% to 74% with GPT-4.
cGAN surrogates recover 45-60% of CFD energy savings and high-velocity wake avoidance in 3D AUV path planning while running at 28-146 microsecond inference speeds across 19,800 trajectories.
OSCAR learns class-conditioned survival distributions for obstacle clearance times online (handling right-censored data) to compute patience thresholds in graph-based navigation, converging near oracle performance after few observations per class.
The anti-lexicographic SUS-anchor achieves sampling densities less than 1% above the lower bound for alphabet size 4 and k=1, substantially outperforming bidirectional anchors.
GRAFT-ATHENA projects combinatorial method choices into factored trees that embed as fingerprints in a metric space, enabling an agentic system to accumulate experience across domains and autonomously discover new numerical techniques for physics-informed problems.
CogInstrument represents human reasoning as revisable cognitive motifs in graphical form to support iterative alignment with LLMs during planning tasks, with a N=12 study indicating gains in targeted revision, agency, and trust over standard dialogue interfaces.
A branch-and-bound algorithm with custom node selection, branching rules, and conflict definitions solves the logic-constrained shortest path problem for flight planning with traffic flow restrictions, showing order-of-magnitude speedups on a public global dataset with 20000 real constraints.
IR-SIM is a YAML-defined simulator for mobile robot navigation that supports text-prompt scenario creation, policy training, benchmarking, and bridging to higher-fidelity or real-world settings.
Presents a framework for training empirically admissible neural heuristics via underestimating Bellman operator, asymmetric loss, and validation calibration offset, reporting reduced node expansions with no observed admissibility violations on small puzzles.
A hybrid LLM-plus-physics-simulation framework generates synthesis routes for niobium oxides and finds that LLM implicit priors produce more viable plans than classical path-planning algorithms in computational tests.
Distill refines user task specifications for robots by pruning unnecessary steps, generalizing meanings, and relaxing order constraints, as demonstrated in a crowdsourcing study on a web interface.
A hybrid PLL oracle and neural A* method constrains LLM generation to paths in a 700K-node medical graph, claiming better latency-recall tradeoffs and fewer hallucinations than text-only RAG on fertility queries.
Genetic algorithm with AHP produces more diverse paths than A* whose runtime is independent of environment size, claimed to increase continuum robot resilience in two simulated settings.
A review of ARG-based simulation and inference methods in population genetics, evaluating their performance, usability, and biological realism with links to software.
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CogInstrument: Modeling Cognitive Processes for Bidirectional Human-LLM Alignment in Planning Tasks
CogInstrument represents human reasoning as revisable cognitive motifs in graphical form to support iterative alignment with LLMs during planning tasks, with a N=12 study indicating gains in targeted revision, agency, and trust over standard dialogue interfaces.