Knowledge catalogue
arXiv:2405.09866v2 Announce Type: replace-cross Abstract: In recent years, novel communication strategies have emerged to face the challenges that the increased number of connected devices and the hig
arXiv:2604.11288v1 Announce Type: new Abstract: At K=16 tokens (0.4% of a 4K context), every existing KV-cache compression method achieves 0% on credential retrieval. The failure mode is dormant token
arXiv:2602.11623v2 Announce Type: replace Abstract: We revisit the use of probabilistic values, which include the well-known Shapley and Banzhaf values, to rank features for explaining the local predi
OpenAI is expanding trusted access to its AI models for cybersecurity purposes, enabling vetted researchers, defenders, and organizations to leverage advanced AI capabilities for cyber defense applica
arXiv:2604.11253v1 Announce Type: cross Abstract: Feature importance methods using unrestricted permutations are flawed due to extrapolation errors; such errors appear in all non-trivial variable impo
arXiv:2604.10485v1 Announce Type: cross Abstract: Low-visibility scenarios, such as low-light conditions, pose significant challenges to human pose estimation due to the scarcity of annotated low-ligh
arXiv:2604.11036v1 Announce Type: cross Abstract: Scientific fact-checking is vital for assessing claims in specialized domains such as biomedicine and materials science, yet existing systems often ha
arXiv:2502.09269v3 Announce Type: replace Abstract: Existing methods derive clinical functional metrics from ventricular semantic segmentation in cardiac cine sequences. While performing well on overa
arXiv:2604.10823v1 Announce Type: new Abstract: Plant seedling segmentation supports automated phenotyping in precision agriculture. Standard segmentation models face difficulties due to intricate bac
arXiv:2604.11685v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has become a state-of-the-art framework for real-time, high-fidelity novel view synthesis. However, its substantial storage
arXiv:2604.10952v1 Announce Type: new Abstract: Selecting prototypical examples from a source distribution to represent a target data distribution is a fundamental problem in machine learning. Existin
arXiv:2604.10571v1 Announce Type: cross Abstract: We test whether artificial intelligence architectural evolution obeys the same statistical laws as biological evolution. Compiling 935 ablation experi
arXiv:2505.09591v3 Announce Type: replace-cross Abstract: Despite remarkable progress in recent years, Vision Language Models (VLMs) remain prone to overconfidence and hallucinations on tasks such as
arXiv:2604.09838v1 Announce Type: new Abstract: We present a novel diffusion-based framework for synthesizing 2D vector fields from sparse, coherent inputs (i.e., streamlines) while maintaining physic
arXiv:2604.02467v2 Announce Type: replace-cross Abstract: Cinematic camera control relies on a tight feedback loop between director and cinematographer, where camera motion and framing are continuousl
arXiv:2604.09943v1 Announce Type: new Abstract: Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However,
arXiv:2604.10645v1 Announce Type: cross Abstract: There is a pressing need for better development methods and tools to keep up with the growing demand and increasing complexity of new software systems
arXiv:2604.11395v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact heart rate measurement from facial videos, but its performance is significantly degraded by facia
arXiv:2506.14629v3 Announce Type: replace-cross Abstract: Mosquito-borne diseases pose a major global health risk, requiring early detection and proactive control of breeding sites to prevent outbreak
arXiv:2604.10167v1 Announce Type: cross Abstract: Multi-vector models dominate Visual Document Retrieval (VDR) due to their fine-grained matching capabilities, but their high storage and computational
arXiv:2511.11533v3 Announce Type: replace-cross Abstract: Ergodic control synthesizes optimal coverage behaviors over spatial distributions for nonlinear systems. However, existing formulations model
This r/MachineLearning discussion post details a hands-on benchmark study in which TranslateGemma — Google's open translation model suite built on Gemma 3, available in 4B, 12B, and 27B sizes and cove
arXiv:2507.08339v4 Announce Type: replace Abstract: Recently, large language models (LLMs) and reasoning large language models (RLLMs) have gained considerable attention from many researchers. RLLMs e
arXiv:2604.10990v1 Announce Type: cross Abstract: Scientific claim verification, the task of determining whether claims are entailed by scientific evidence, is fundamental to establishing discoveries
arXiv:2604.11663v1 Announce Type: new Abstract: Large Language Models (LLMs) have been shown to generate harmful content. However, the underlying causes of such behavior remain under explored. We prop
arXiv:2510.27269v3 Announce Type: replace-cross Abstract: Reasoning language models (RLMs) achieve strong performance on complex reasoning tasks, yet they still exhibit a multilingual reasoning gap, p
arXiv:2604.10569v1 Announce Type: new Abstract: Decision-tree ensembles are a cornerstone of predictive modeling, and SHAP is a standard framework for interpreting their predictions. Among its variant
arXiv:2601.14477v2 Announce Type: replace-cross Abstract: Until open-world foundation models match the performance of specialized approaches, deep learning systems remain dependent on task- and sensor
This Reddit post from r/MachineLearning discusses the concept of decomposing machine learning models into a graph database representation, treating a model's components — such as layers, weights, and
arXiv:2604.03420v2 Announce Type: replace-cross Abstract: We show that robustness to post-training quantization (PTQ) is a transferable direction in weight space. We call this direction the quantizati
arXiv:2604.09713v1 Announce Type: new Abstract: Handwritten Text Recognition (HTR) models trained on synthetic handwriting often struggle to generalize to real text, and existing adaptation methods st
arXiv:2604.10333v1 Announce Type: new Abstract: Young children demonstrate early abilities to understand their physical world, estimating depth, motion, object coherence, interactions, and many other
arXiv:2604.09244v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as the mainstream of embodied intelligence. Recent VLA models have expanded their input modalities fr
arXiv:2604.08645v1 Announce Type: cross Abstract: Large multimodal models are increasingly used as the reasoning core of embodied agents operating in 3D environments, yet they remain prone to hallucin
arXiv:2604.08890v1 Announce Type: cross Abstract: Modeling causal relationships in graph representation learning remains a fundamental challenge. Existing approaches often draw on theories and methods
arXiv:2604.09157v1 Announce Type: cross Abstract: We introduce a novel learning framework for accelerated Monte Carlo (MC) dose calculation termed Energy-Shifting. This approach leverages deep learnin
arXiv:2604.08935v1 Announce Type: cross Abstract: Causal discovery from observational data remains a fundamental challenge in machine learning and statistics, particularly when variables represent inh
arXiv:2604.09208v1 Announce Type: cross Abstract: We develop a predictive-first optimisation framework for streaming hidden Markov models. Unlike classical approaches that prioritise full posterior re
arXiv:2604.08610v1 Announce Type: new Abstract: This paper presents a semi-automated framework for transforming two-dimensional miniatures from medieval manuscripts into three-dimensional digital mode
arXiv:2604.08718v1 Announce Type: cross Abstract: Geometric Foundation Models (GFMs) have recently advanced monocular SLAM by providing robust, calibration-free 3D priors. However, deploying these mod
arXiv:2604.09466v1 Announce Type: new Abstract: Under the lens of Marr's levels of analysis, we critique and extend two claims about language models (LMs) and language processing: first, that predicti
arXiv:2604.08742v1 Announce Type: cross Abstract: Adam has achieved strong empirical success, but its theory remains incomplete even in the deterministic full-batch setting, largely because adaptive p
arXiv:2604.09210v1 Announce Type: new Abstract: Monocular imaging of animals inherently reduces 3D structures to 2D projections. Detection algorithms lead to 2D bounding boxes that lack information ab
arXiv:2604.08580v1 Announce Type: cross Abstract: Reward fine-tuning of diffusion and flow models and sampling from tilted or Boltzmann distributions can both be formulated as stochastic optimal contr
arXiv:2412.16107v4 Announce Type: replace Abstract: Tilt-rotor aerial robots are more dynamic and versatile than fixed-rotor platforms, since the thrust vector and body orientation are decoupled. Howe
arXiv:2604.09280v1 Announce Type: cross Abstract: Extranodal extension (ENE) is an emerging prognostic factor in human papillomavirus (HPV)-associated oropharyngeal cancer (OPC), although it is curren
arXiv:2604.08669v1 Announce Type: cross Abstract: It is widely believed that tens of thousands of physical qubits are needed to build a practically useful quantum computer. Atom arrays formed by optic
arXiv:2604.09543v1 Announce Type: new Abstract: The persistent storage requirements for high-resolution, spatiotemporally evolving fields governed by large-scale and high-dimensional partial different
arXiv:2604.09364v1 Announce Type: cross Abstract: When a Vision-Language Model (VLM) sees a blue banana and answers 'yellow', is the problem of perception or arbitration? We explore the question in te
As a Catholic, I find it abhorrent that the President of the United States would publicly attack the Successor of St. Peter. Donald Trump is flailing. His war in Iran has led to the death and injury o
arXiv:2604.08564v1 Announce Type: new Abstract: Auto-regressive models (ARMs) have established a dominant paradigm in language modeling. However, their strictly sequential decoding paradigm imposes fu
arXiv:2603.24245v3 Announce Type: replace Abstract: Micro-actions, fleeting and low-amplitude motions, such as glances, nods, or minor posture shifts, carry rich social meaning but remain difficult fo
arXiv:2510.18075v2 Announce Type: replace Abstract: Machine learning (ML) holds great potential to advance anomaly detection (AD) in chemical processes. However, the development of ML-based methods is
arXiv:2512.04175v2 Announce Type: replace Abstract: Generalizing deepfake detection to unseen manipulations remains a key challenge. A recent approach to tackle this issue is to train a network with p
arXiv:2604.09085v1 Announce Type: cross Abstract: Large-scale digital platforms generate billions of timestamped user-item interactions (events) that are crucial for predicting user attributes in, e.g
arXiv:2509.14875v2 Announce Type: replace-cross Abstract: Characterizing the geometry of an object orbiting around a star from its transit light curve is a powerful tool to uncover various complex phe
arXiv:2604.09022v1 Announce Type: new Abstract: With the rapid adoption of diffusion models, synthetic data generation has emerged as a promising approach for addressing the growing demand for large-s
arXiv:2604.09359v1 Announce Type: new Abstract: Label noise in multi-label learning (MLL) poses significant challenges for model training, particularly in partial multi-label learning (PML) where cand
A developer shared a project on r/MachineLearning showcasing an AI-powered tool designed to automate common data preprocessing tasks, including dataset cleaning, intelligent imputation of missing valu
arXiv:2511.01383v2 Announce Type: replace Abstract: Accurate point-wise velocity estimation in 3D is crucial for robot interaction with non-rigid dynamic agents, enabling robust performance in path pl