Study evaluates progress in common-sense reasoning tasks.
problem Assessing genuine progress in common-sense reasoning systems.
method Case studies of WSC and SWAG, protocol design to clarify results.
result Previous experimental designs had flaws, need for new protocols.
In this article, we investigate when the set of primitive geodesic lengths on a Riemannian manifold have arbitrarily long arithmetic progressions. We prove that in the space of negatively curved metrics, a metric having such arithmetic progressions is quite rare. We introduce almost arithmetic progressions, a coarsific…
Signed compression progress on a sealed audit is goodhart-resistant.
problem Intrinsic motivation for agents to improve their world models by compressing experience.
method Rewarding agents for the signed decrease of a fixed sealed-audit loss.
result Cumulative reward telescopes exactly to endpoint audit improvement, preventing infinite reward push while true audit performance stagnates.
We show that if a closed atoroidal 3-manifold M contains a genuine lamination, then it is group negatively curved in the sense of Gromov. Specifically, we exploit the structure of the non-product complementary regions of the genuine lamination and then apply the first author's Ubiquity Theorem to show that M satisfies …
We extend to the conformal realm the concept of genuine deformations of submanifolds, introduced by Dajczer and the first author for the isometric case. Analogously to that case, we call a conformal deformation of a submanifold Mn genuine if no open subset of Mn can be included as a submanifold of a higher dimens…
Deep learning models can discriminate against certain groups, requiring computational methods to ensure fairness.
problem Algorithmic discrimination in deep learning models affecting protected groups.
method Interpretability and mitigation approaches at different stages of deep learning lifecycle.
result Interpretability aids in diagnosing and mitigating algorithmic discrimination in deep learning.
We classify hypersurfaces of rank two of Euclidean space Rn+1 that admit genuine isometric deformations in Rn+2. That an isometric immersion f^:Mn→Rn+2 is a genuine isometric deformation of a hypersurface f:Mn→Rn+1 means that f^ is nowhere a composition $\hat f=\ha…
We extend the concept of genuine rigidity of submanifolds by allowing mild singularities, mainly to obtain new global rigidity results and unify the known ones. As one of the consequences, we simultaneously extend and unify Sacksteder and Dajczer-Gromoll theorems by showing that any compact n-dimensional submanifold …
Paper uses VAEs to detect genuine signatures.
problem Signature recognition performance plateaued at 2% error rate.
method Uses VAEs to learn latent space, then classifies unlabelled signatures.
result Method performs less well than existing alternatives but shows potential.
This paper extends classifications of hypersurface immersions to higher dimensions.
problem Local classifications of hypersurface immersions in higher codimensions.
method Complete description of moduli space of genuine deformations.
result Analogous classification of hypersurface immersions in higher dimensions.
In this paper we classify Euclidean hypersurfaces f:Mn→Rn+1 with a principal curvature of multiplicity n−2 that admit a genuine conformal deformation f~:Mn→Rn+2. That f~:Mn→Rn+2 is a genuine conformal defo…
We construct a pair of transverse genuine laminations on an atoroidal 3-manifold admitting transversely orientable uniform 1-cochain. The laminations are induced by the uniform 1-cochain and they are indeed the "straightening" of the coarse laminations defined in [Ca], by using minimal surface techniques. Moreover, whe…
AI mirrors modern math's autonomous development, raising interpretive challenges.
problem AI's effectiveness in math mirrors historical autonomy of math.
method Analyzes historical evolution of modern mathematics and AI's role.
result AI's affinity with math's historical autonomy suggests interpretive limits.
Study on infinitesimal bendings of submanifolds in high codimension.
problem Understanding infinitesimal bendings of submanifolds in high codimension.
method Analyzing the conditions for genuine infinitesimal bendings and describing the situation for compact submanifolds.
result A strong necessary condition for infinitesimal bendings is the submanifold being ruled, and a lower bound for the dimension of the rulings is provided.
Language model benchmarks often misrepresent true understanding, revealing vulnerabilities in evaluation methods.
problem Language model benchmarks fail to accurately reflect true language understanding and adaptability.
method Systematic analysis of NLP evaluation frameworks, identifying vulnerabilities in static benchmarks, human evaluation protocols, and LLM-as-judge frameworks.
result Current evaluation methods are unreliable and need improvement to accurately assess LLM performance.
Fine-tunes diffusion models to generate diverse samples with high genuine rewards.
problem Reward collapse in finetuning diffusion models.
method Entropy-regularized control against pretrained diffusion models.
result Efficient generation of diverse samples with high genuine rewards.
Proves deep networks can learn hierarchical structures efficiently.
problem Understanding how deep networks learn hierarchical structures in data.
method Random Hierarchy Models, gradient-based methods, layerwise training.
result Proves deep networks can efficiently learn hierarchical structures.
Concerning the problem of classifying complete submanifolds of Euclidean space with codimension two admitting genuine isometric deformations, until now the only known examples with the maximal possible rank four are the real Kaehler minimal submanifolds classified by Dajczer-Gromoll \cite{dg3} in parametric form. These…
Polynomial-time algorithm for list-decodable linear regression with batches.
problem Efficiently decoding linear regression with a fraction of adversarial data.
method Polynomial time algorithm using batches of i.i.d. samples.
result Returns a list of size O(1/α^2) with one item close to true parameter.
Survey compares methods for generating artificial outliers.
problem Difficulty in detecting genuine outliers.
method Generates artificial outliers to approximate genuine ones.
result Variability in quality of generation approaches.
Verified numerics prove existence of a curvature solution with known symmetries.
problem Existence of a curvature solution for the Nirenberg problem.
method Verified numerics and computer assistance.
result Existence of a genuine solution with known symmetry groups.
Proves the Kundt conjecture in arbitrary dimensions, confirming its validity.
problem Determining spacetimes not characterized by scalar polynomial curvature invariants.
method New bilinear map and analysis of covariant derivatives of the Riemann tensor.
result Confirms the Kundt conjecture in arbitrary dimensions, removing regularity assumptions.
Modeling true and false news diffusion in social networks using homogeneity.
problem Difficulties in distinguishing true from false news in social networks.
method Proposes a Bayesian nonparametric model that incorporates homogeneity of news stories to predict their genuineness.
result Homogeneity values of news stories strongly correlate with their genuineness and content.
Audit financial machine learning workflows to detect spurious predictability.
problem Spurious predictability in financial machine learning models.
method Falsification audit testing predictive workflows against synthetic environments.
result Many apparent financial predictions are artifacts, not genuine.
New method for dynamic valuation in markets with random endowments.
problem Dynamic valuation in markets with random endowments.
method Developed new FBSDE systems and established optimality conditions.
result Established necessary and sufficient conditions for optimality.
An observable for nonabelian, higher-dimensional forms is introduced, its properties are discussed and its expectation value in BF theory is described. This is shown to produce potential and genuine invariants of higher-dimensional knots.
BCPO optimizes offline RL policies by converting uncertainty into conservative bounds.
problem Offline RL's fragility under distribution shifts and model errors.
method Bayesian approach with credible lower bounds and KL regularization.
result BCPO yields an uncertainty-calibrated policy that avoids exploiting model errors.
We examine the difference between several notions of curvature homogeneity and show that the notions introduced by Kowalski and Vanžurová are genuine generalizations of the ordinary notion of k-curvature homogeneity. The homothety group plays an essential role in the analysis.
New concept SB-generation helps classify transformation groups.
problem Classifying transformation groups through quasi-isometry invariants.
method Identifying SB-generated groups in specific transformation groups.
result SB-generation provides robust extension of finite generation.
We present a simpler proof for the existence of adiabatic limits. Moreover, we added a new section where the adiabatic process is reversed and in some nondegenerate cases we deform the adiabatic limits to genuine irreducible solutions of the SW equations.
We show that among the Euclidean submanifolds with codimension two the ones of rank two that are parabolic but nonruled are isometrically rigid. This generalizes the result in [10] that these submanifolds are genuinely rigid. In addition, we give a parametric classifications of all parabolic submanifolds.
Novel construction of Bauer--Furuta invariant using sheaves of spectra.
problem Constructing the Bauer--Furuta invariant without finite-dimensional approximations.
method Using sheaves of spectra and Borel--Moore homology, avoiding approximations.
result Defines the shriek functors and Thom spectra for index calculations.
Gurau argued in [arXiv:1006.0714] that the gluing spaces arising as Feynman diagrams of three-dimensional group field theory are not all pseudo-manifolds. I dispute this conclusion: albeit not properly triangulated, these spaces are genuine pseudo-manifolds, viz. their singular locus is of codimension at least two.
Study on fake stationary Volterra Heston model for non-stationary processes.
problem Non-stationary nature of true Volterra equations.
method Weak notion of stationarity (fake stationary regime) for inhomogeneous affine Stochastic Volterra equations.
result Existence of limiting distributions in the long run, which may depend on initial state.
Study on special tensors in specific geometric spaces.
problem Characterizing symmetric Killing tensors on nilmanifolds.
method Investigated left-invariant symmetric Killing 2-tensors on 2-step nilpotent Lie groups with a Riemannian metric.
result Found genuine examples of symmetric Killing tensors that are not simple combinations.
Paper extends SI method for detecting CPs in complex systems' frequency domain.
problem Identifying change points in complex systems' frequency domain.
method Extends SI framework to frequency domain using DFT properties and develops valid p-values.
result Reliable detection of genuine CPs with strong statistical guarantees.
UNREAL selectively ensembles distinct models to improve active learning performance.
problem Difficulty in distinguishing genuine uncertainty from noise in limited labeled data.
method Selective ensembling of distinct models from the Rashomon set.
result UNREAL achieves faster convergence and up to 20% predictive accuracy improvement.
Using ideas from an article of P. Bieliavsky, M. Rooman and Ph. Spindel on BTZ black holes, I construct a family of interesting examples of quasi-Poisson actions as defined by A. Alekseev and Y. Kosmann-Schwarzbach. As an application, I obtain a genuine Poisson structure on SL(2,R) which induces a Poisson structure o…
New metrics improve scRNA-seq perturbation modeling by reducing mode collapse.
problem Outperformed by simple mean prediction in scRNA-seq perturbation modeling.
method Introduce DEG-aware metrics (WMSE, Rw2(Δ)) and negative/positive baselines. result WMSE loss function reduces mode collapse and improves model performance.
In this paper we prove that, in the category of chain complexes, partial algebras can be functorially replaced by quasi-isomorphic algebras. In particular, partial algebras contain all of the important homological and homotopical information that genuine algebras do. Applying this result to McClure's partial algebra in…
We give a general lower bound for the normal Gromov norm of genuine laminations in terms of the topology of the complementary regions. In the special case of 3-manifolds, this yields a generalization of Agol's inequality from incompressible surfaces to tight laminations. In particular, the inequality excludes the exist…
Industry evolution caused by various reasons, among which technology progress driving industry development has been approved, but with the new trend of industry convergence, inter-industry convergence also plays an increasing important role. This paper plans to probe the industry synergetic evolution mechanism based on…
Confidential Guardian prevents model abstention from being used to discriminate.
problem Dishonest institutions can exploit machine learning model abstention to unfairly deny services.
method Confidential Guardian uses zero-knowledge proofs to verify model confidence and detect suppression.
result Confidential Guardian effectively prevents the misuse of cautious predictions.
DPVis integrates HMMs into visualizations for disease progression analysis.
problem Challenges in interpreting HMMs for disease progression modeling.
method Design study with clinical experts, visualizations of HMM parameters and outcomes.
result DPVis successfully evaluates and summarizes disease progression models.
Paper introduces a new curriculum generation method for reinforcement learning.
problem Improving reinforcement learning performance and speed through curriculum learning.
method The paper proposes a novel curriculum generation paradigm based on progression and mapping functions.
result Empirical results show the new approach outperforms state-of-the-art algorithms.
Lie groups applied to tech progress in economic growth.
problem Understanding the impact of technical progress on economic growth.
method Application of Lie theory and economic modeling.
result Estimation of GDP function for Viet Nam, highlighting tech progress impact.
Research connects Lie algebras to configuration space (co)homology.
problem Understanding the (co)homology of configuration spaces.
method Identifying Lie algebra (co)homology as a counterpart to configuration space (co)homology.
result Lie algebras and configuration spaces have a deep mathematical relationship.
This paper improves disentanglement in VAEs by progressively learning hierarchical representations.
problem Compromised disentanglement in VAEs due to high-level abstraction extraction.
method Progressive learning of independent hierarchical representations from high to low levels.
result Improved disentanglement demonstrated on two benchmark datasets using new metrics.