A block-product gadget with shared period-2 orbits but irrational eigenvalue log-ratios produces an AdaBoost burst-winner sequence with irrational asymptotic frequency, proving non-periodicity.
Title resolution pending
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
verdicts
UNVERDICTED 6representative citing papers
LNTrust has nodes learn compact trust functions from validation evidence that both guide training distillation and define deployment ensembles, yielding higher accuracy with less communication than prior output-only baselines.
Introduces structured Stackelberg games and the Stackelberg-Littlestone dimension to characterize the leader's optimal regret and sample complexity when context predicts follower type.
Verifier-backed committee search boosts a weak reasoning model from 67% to 76.4% on SWE-bench Verified, matching stronger models by using local soundness signals to select among proposals.
A proportional weight-update rule creates implicit binary evaluation signals that propagate losslessly through hierarchical selectors while preserving algebraic market integrity and admitting unique interior equilibria.
Probabilistic language tries unify compression, sequential decision making, and inference caching by making explicit the prefix structure of any generative model over sequences.
citing papers explorer
-
AdaBoost Does Not Always Cycle: A Computer-Assisted Counterexample
A block-product gadget with shared period-2 orbits but irrational eigenvalue log-ratios produces an AdaBoost burst-winner sequence with irrational asymptotic frequency, proving non-periodicity.
-
Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning
LNTrust has nodes learn compact trust functions from validation evidence that both guide training distillation and define deployment ensembles, yielding higher accuracy with less communication than prior output-only baselines.
-
Learning in Structured Stackelberg Games
Introduces structured Stackelberg games and the Stackelberg-Littlestone dimension to characterize the leader's optimal regret and sample complexity when context predicts follower type.
-
Agentic Systems as Boosting Weak Reasoning Models
Verifier-backed committee search boosts a weak reasoning model from 67% to 76.4% on SWE-bench Verified, matching stronger models by using local soundness signals to select among proposals.
-
Implicit Evaluation Under Minimal Information: Price Formation in Hierarchical Component Selection
A proportional weight-update rule creates implicit binary evaluation signals that propagate losslessly through hierarchical selectors while preserving algebraic market integrity and admitting unique interior equilibria.
-
Probabilistic Language Tries: A Unified Framework for Compression, Decision Policies, and Execution Reuse
Probabilistic language tries unify compression, sequential decision making, and inference caching by making explicit the prefix structure of any generative model over sequences.