Claims Browser

DocTalkBN preserves spontaneity, contextual richness, and spoken characteristics of authentic medical interactions unlike prior resources from forums, written content, or synthetic data

"Unlike prior resources derived from medical forums, written health content, or synthetic data, our dataset preserves the spontaneity, contextual richness, and spoken characteristics of authentic medical interactions in a low-resource setting."

DocTalkBN is a practically useful resource, particularly for clinically grounded reasoning tasks

"Our results show that DocTalkBN is a practically useful resource, particularly for clinically grounded reasoning tasks."

Post-composing a fixed number of pairwise distinct nonconstant polynomials with a generic polynomial of sufficiently large degree yields linearly independent polynomials

"post-composing a fixed number of pairwise distinct nonconstant polynomials with a generic polynomial of sufficiently large degree yields linearly independent polynomials"

The conjecture on polynomial composition generalizes Newman-Slater's theorem on powers of polynomials

"This generalizes Newman--Slater's theorem on powers of polynomials"

The polynomial composition conjecture has been proven for two polynomials and for an arbitrary number of polynomials when their degrees are bounded

"We prove the result for two polynomials, and for an arbitrary number of polynomials when their degrees are bounded"

The polynomial composition conjecture implies a complete understanding of the identifiability of deep fully connected neural network architectures with generic polynomial activation functions

"the conjecture implies a complete understanding of the identifiability (i.e., parameter symmetries) of deep fully connected neural network architectures with generic polynomial activation functions"

For neural network architectures with layer-specific activations of increasing degree, the established versions of the conjecture fully characterize the set of parameters yielding the same end-to-end network function

"for network architectures with layer-specific activations of increasing degree, our established versions of the conjecture fully characterize the set of parameters yielding the same end-to-end network function"

The identifiability of shallow polynomial networks has been fully resolved

"we fully resolve the identifiability of shallow polynomial networks"

Monolingual language models trained on non-parallel data learn alignable representations without joint training

"monolingual models trained on non-parallel data learn alignable representations without joint training"

Monolingual models develop alignable representational geometry that strengthens with increased data scale, model scale, or linguistic proximity

"these models develop alignable representational geometry across layers, with alignment strengthening as data scale, model scale, or linguistic proximity increases"

A single Procrustes rotation fitted on parallel sentences can map hidden states between independently trained monolingual models

"a single Procrustes rotation fit on parallel sentences maps hidden states between models"

Rotated cross-lingual representations transfer functional content, as demonstrated by patching rotated English residuals into German models flipping predictions to the donor's answer

"the same rotation transfers functional content; patching a rotated English residual into a German model on a factual cloze flips the prediction to the donor's capital in most cases"

Cross-lingual alignment emerges from the structure of language itself rather than requiring joint training

"cross-lingual alignment can emerge from the structure of language and the information it carries rather than from joint training"

AI models can form aesthetic categorization of human-produced media without explicit labels or cross-modal supervision

"What remains under-explored is how AI models form their own aesthetic categorization of human-produced media without explicit labels or cross-modal supervision."

A self-supervised framework can project four modalities into a shared 256-dimensional embedding space and discover aesthetic structure through iterative clustering

"We present a self-supervised framework that projects four modalities (text, audio, image and video) into a shared 256-dimensional embedding space and applies iterative clustering to discover aesthetic structure."

There is divergence between AI-generated cluster assignments and human affective register labels

"We discuss the divergence between AI-generated cluster assignments and human affective register labels on a weakly supervised multimodal dataset."

Directed graph learning with nonsymmetric propagation operators can be theoretically certified and controlled using a two-sided cone Rayleigh framework for generalized pencils

"Building on the two-sided cone Rayleigh framework for generalized pencils \[ B_θ-λG, \] we develop a learning-oriented methodology for spectral certification, sensitivity analysis, and control without requiring symmetry, nonnegativity, or cone preservation."

Computable cone bounds provide rigorous spectral enclosure with differentiable soft-min/max surrogates that maintain explicit approximation errors

"computable lower and upper cone bounds provide an a posteriori enclosure of a distinguished cone level, while smooth soft-min/max surrogates preserve rigorous one-sided bounds with explicit approximation errors and remain differentiable with respect to the trainable parameters."