Search the full wire by company, model, lab, or keyword. Every story we have ever aggregated.
Selecting which instances to label is a key challenge in low-label tabular learning. For recent Tabular Foundation Models such as TabPFN, context selection directly determines predictive performance. Supervised oracle experiments show that carefully chosen labeled context sets…
Animation elevates digital documents into immersive experiences, yet creating custom motion paths remains cumbersome, requiring designers to manually select presets, plot Bézier points, and configure timing properties. We introduce Generative Animations, a system that…
Chart-to-data extraction with vision-language models (VLMs) is increasingly evaluated on benchmarks that show diminishing headroom (frontier VLMs exceed 89% on ChartQA) and with metrics that treat extracted points as unordered key-value pairs, ignoring the temporal structure of…
Nathan Witkin critiques METR's Long Tasks benchmark methodology, identifying severe flaws in the widely-cited AI time horizons graph.
OrpQuant: geometric orthogonal residual projection for power-of-two quantization enabling multiplier-free LLM/ViT deployment on edge devices.
Wasserstein Policy Gradient for entropy-regularized RL proves global convergence using optimal-transport geometry for continuous control.
Neural operator surrogates for Bayesian inverse design in CFD to accelerate MCMC sampling for aerodynamic geometry inference.
3D foundation model for light sheet fluorescence microscopy enables few-shot segmentation and classification of volumetric biological imaging data.
4D Gaussian Splatting reconstructs 3D spatial data from 2D video footage; technique converts flat imagery into volumetric representations.
Reddit discussion on hyperparameter selection and evaluation metrics for non-contrastive self-supervised learning methods like BYOL and JEPA.
Some AI startups are stretching traditional revenue metrics when talking about progress publicly. And their investors are fully aware.
Token selection strategy reduces quadratic attention cost in visual geometry transformers for 3D reconstruction by restricting key/value interactions.
PGT generates procedural geometric tasks to improve MLLM fine-grained visual grounding and diagnose perception failure sources.
Distributional theory: hypernymy geometry in word2vec emerges from co-occurrence, with eigenvectors encoding taxonomic hierarchy.
Graph-based analysis of semantic type coercion in BERT embeddings using neighborhood probability and entropy metrics.
Scaling laws for sparse-activation neural networks show double-descent and asymmetric loss dynamics.
Tokenisation is an integral part of the current NLP pipeline. Current tokenisation algorithms such as BPE and Unigram are greedy algorithms -- they make locally optimal decisions without considering the resulting vocabulary as a whole. We instead formulate tokeniser…
Robustness, domain adaptation, photometric and occlusion invariance, compositional generalisation, temporal robustness, alignment safety, and classical anisotropic regularisation are usually treated as separate problems with separate method families. This paper argues that much…
Large language models (LLMs) exhibit systematic political bias across a variety of sensitive contexts. We find that LLMs handle counterpart topics from opposing political sides asymmetrically. We refer to this phenomenon as covert political bias and identify 7 categories of…
Large language models (LLMs) increasingly excel at mathematical reasoning, but their unreliability limits their utility in mathematics research. A mitigation is using LLMs to generate formal proofs in languages like Lean. We perform the first large-scale evaluation of this…
Optimization over the intersection of two manifolds arises in a broad range of applications, but is hindered by the coupled geometry of the feasible region. In this paper, we prove that the regularities -- clean intersection and intrinsic transversality -- are equivalent, which…
Parametric modular logic programs extend ASP with subprogram parameters and intensionality; connects clingo collective control to traditional ASP.
AnyMo framework enables human motion recognition across heterogeneous wearable IMU sensors via geometry-aware setup-agnostic modeling.
Hierarchical offline GCRL framework using relativised options and representational abstraction to reuse experience across state-goal symmetries.
Interactive guide matching 50+ LLMs to 60+ hardware builds with throughput metrics and YouTube reviewer citations.
OpenAI model disproves Erdős geometry conjecture; researcher claims breakthrough significance will compound through 2025.
OpenAI's reasoning model discovered a counterexample to Erdős's unit-distance conjecture in discrete geometry, disproving a decades-old bound.
OpenAI claims its reasoning model disproved a geometry conjecture unsolved since 1946 — and this time, the mathematicians who exposed its last embarrassing claim are backing it up.
OpenAI model disproved a longstanding conjecture in discrete geometry, demonstrating AI capability in mathematical research and theorem discovery.
Also covered by r/singularity
Velocityformer applies equivariant graph transformers to cosmological kinematic Sunyaev-Zel'dovich velocity reconstruction.