Knowledge catalogue
arXiv:2604.08772v1 Announce Type: cross Abstract: Atmospheric clouds exhibit complex three-dimensional structure and microphysical details that are poorly constrained by the predominantly two-dimensio
arXiv:2604.09282v1 Announce Type: cross Abstract: Reliable position and attitude sensing is critical for highly automated vehicles that operate on conventional roadways. Lidar sensors are increasingly
arXiv:2603.21935v2 Announce Type: replace-cross Abstract: Quantitative disease severity scoring in medical imaging is costly, time-consuming, and subject to inter-reader variability. At the same time,
arXiv:2604.09101v1 Announce Type: cross Abstract: Organisations with limited data and computational resources increasingly outsource model training to Machine Learning as a Service (MLaaS) providers,
arXiv:2604.09446v1 Announce Type: cross Abstract: The Tactile Internet demands sub-millisecond latency and ultra-high reliability, as high latency or packet loss could lead to haptic control instabili
arXiv:2604.08924v1 Announce Type: new Abstract: Infrared-visible image fusion aims to integrate complementary information for robust visual understanding, but existing fusion methods struggle with sim
arXiv:2604.09246v1 Announce Type: cross Abstract: Differentiable Digital Signal Processing (DDSP) pipelines for voice conversion rely on subtractive synthesis, where a periodic excitation signal is sh
arXiv:2604.08711v1 Announce Type: cross Abstract: The disintegration of liquid sheets into ligaments and droplets involves highly transient, multi-scale dynamics that are difficult to quantify from hi
arXiv:2604.09145v1 Announce Type: new Abstract: Nighttime photography is severely degraded by light pollution induced by pervasive artificial lighting in urban environments. After long-range scatterin
arXiv:2604.09089v1 Announce Type: cross Abstract: Large Language Models (LLMs) for code generation can replicate insecure patterns from their training data. To mitigate this, a common strategy for sec
arXiv:2604.08720v1 Announce Type: cross Abstract: Performance optimization of AI infrastructure is key to the fast adoption of large language models (LLMs). The PyTorch compiler (torch.compile), a cor
arXiv:2602.20028v2 Announce Type: replace-cross Abstract: Accurate taxonomic identification is the cornerstone of biodiversity monitoring and agricultural management, particularly for the hyper-divers
arXiv:2604.09106v1 Announce Type: new Abstract: Diffusion models are known for generating high-quality images, causing serious security concerns. To combat this, most efforts rely on deep neural netwo
arXiv:2604.08609v1 Announce Type: cross Abstract: Digital forensic investigations increasingly rely on heterogeneous evidence such as images, scanned documents, and contextual reports. These artifacts
arXiv:2512.01708v2 Announce Type: replace-cross Abstract: Learning the structure of a Bayesian network from decentralized data poses two major challenges: (i) ensuring rigorous privacy guarantees for
arXiv:2604.09240v1 Announce Type: new Abstract: High-Level Synthesis (HLS) compiles C/C++ into RTL, but exploring pragma-driven optimization choices remains expensive because each design point require
arXiv:2604.08837v1 Announce Type: new Abstract: Flow-based image generative models exhibit stable training and produce high quality samples when using multi-step sampling procedures. One-step generati
arXiv:2604.08574v1 Announce Type: cross Abstract: Large Genomic Foundation Models have recently achieved remarkable results and in-vivo translation capabilities. However these models quickly grow to o
arXiv:2604.09276v1 Announce Type: new Abstract: Distributed online convex optimization (D-OCO) is a powerful paradigm for modeling distributed scenarios with streaming data. However, the communication
arXiv:2602.05862v2 Announce Type: replace-cross Abstract: Two-sample testing, where we aim to determine whether two distributions are equal or not equal based on samples from each one, is challenging
arXiv:2604.08577v1 Announce Type: cross Abstract: Large Language Models (LLMs) tend to respond correctly to prompts that align to the data they were trained and fine-tuned on. Yet, small shifts in wor
arXiv:2602.10603v3 Announce Type: replace Abstract: Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff in their input representation. Standard fixed-voc
arXiv:2604.09425v1 Announce Type: new Abstract: Vision Language Models (VLMs) have achieved remarkable success by integrating visual encoders with large language models (LLMs). While VLMs process dens
arXiv:2604.09018v1 Announce Type: new Abstract: Face Anti-Spoofing (FAS) algorithms, designed to secure face recognition systems against spoofing, struggle with limited dataset diversity, impairing th
arXiv:2511.06756v3 Announce Type: replace Abstract: Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to b
arXiv:2604.08565v1 Announce Type: cross Abstract: At typical context lengths, the feed-forward MLP block accounts for a large share of a transformer's compute budget, motivating sparse alternatives to
arXiv:2604.09391v1 Announce Type: cross Abstract: Machine unlearning poses challenges in removing mislabeled, contaminated, or problematic data from a pretrained model. Current unlearning approaches a
arXiv:2604.08694v1 Announce Type: new Abstract: How do you build a sign language recognizer that works on a phone? That question drove this work. We built EfficientSign, a lightweight model which take
arXiv:2511.03122v2 Announce Type: replace-cross Abstract: Designing materials with targeted properties remains challenging due to the vastness of chemical space and the scarcity of property-labeled da
arXiv:2604.08589v1 Announce Type: new Abstract: Mental health challenges among young adults, are on the rise, necessitating effective solutions such as digital mental health interventions (DMHIs). Des
arXiv:2604.09130v1 Announce Type: cross Abstract: As SE(3)-equivariant graph neural networks mature as a core tool for 3D atomistic modeling, improving their efficiency, expressivity, and physical con
arXiv:2510.09093v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now routinely used to autonomously execute complex tasks, from natural language processing to dynamic workflo
arXiv:2604.02598v2 Announce Type: replace-cross Abstract: LLM-generated explanations can make technical content more accessible, but there is a ceiling on what they can support interactively. Because
arXiv:2412.12686v3 Announce Type: replace Abstract: Current large language models (LLMs) often exhibit imbalances in multilingual capabilities and cultural adaptability, largely attributed to their En
Research: Exploring the new `servo` crate In Servo is now available on crates.io the Servo team announced the initial release of the servo crate, which packages their browser engine as an embeddable l
arXiv:2603.23199v2 Announce Type: replace Abstract: Deep learning-based 3D medical image segmentation methods relies on large-scale labeled datasets, yet acquiring such data is difficult due to privac
arXiv:2604.09094v1 Announce Type: cross Abstract: Abusive speech detection is becoming increasingly important as social media shifts towards voice-based interaction, particularly in multilingual and l
arXiv:2603.02417v3 Announce Type: replace-cross Abstract: Classical stochastic-approximation analyses treat the covariance of stochastic gradients as an exogenous modeling input. We show that under ex
arXiv:2512.02826v3 Announce Type: replace-cross Abstract: Flow-based diffusion models have emerged as a leading paradigm for training generative models across images and videos. However, their memoriz
arXiv:2604.08894v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) offer superior energy efficiency over Artificial Neural Networks (ANNs). However, they encounter significant deficienci
arXiv:2604.09142v1 Announce Type: new Abstract: Despite remarkable advances in image-driven stereo matching over the past decade, Synthetic-to-Realistic Zero-Shot (Syn-to-Real) generalization remains
arXiv:2604.09199v1 Announce Type: new Abstract: We solve the problem of determining the pose of known shapes in R^3 from their unoccluded silhouettes. The pose is determined up to global optimality us
arXiv:2503.14075v3 Announce Type: replace-cross Abstract: Large vision-language models (VLMs) have demonstrated remarkable capabilities in open-world multimodal understanding, yet their high computati
arXiv:2604.06165v2 Announce Type: replace Abstract: Large vision-language models can produce object hallucinations in image descriptions, highlighting the need for effective detection and mitigation s
arXiv:2604.08877v1 Announce Type: new Abstract: In this paper, we study the text-based person search, which is to retrieve the person of interest via natural language description. Prevailing methods u
arXiv:2603.27222v2 Announce Type: replace Abstract: High-resolution imagery is essential for accurate 3D reconstruction, as many geometric details only emerge at fine spatial scales. Recent feed-forwa
arXiv:2604.09336v1 Announce Type: new Abstract: Accurate prediction of intersection turning movements is essential for adaptive signal control but remains difficult due to the high volatility of direc
arXiv:2604.08829v1 Announce Type: new Abstract: The Hierarchical Kernel Transformer (HKT) is a multi-scale attention mechanism that processes sequences at L resolution levels via trainable causal down
arXiv:2604.08872v1 Announce Type: new Abstract: Many language tasks can be modeled as classification problems where a large language model (LLM) is given a prompt and selects one among many possible a
arXiv:2511.16136v2 Announce Type: replace Abstract: The rapid advancement of generative models has made real and synthetic images increasingly indistinguishable. Although extensive efforts have been d
In this video from Dwarkesh Patel's channel, Dr. Natalie Crawford, a double board-certified physician specializing in obstetrics and gynecology, fertility, and reproductive health , discusses how wome
A Reddit discussion thread on r/MachineLearning criticizing a procedural misstep in the ICML 2026 review process, where reviewers are newly required this year to provide a final justification describi
arXiv:2604.09135v1 Announce Type: cross Abstract: Unobserved confounding is a key challenge when estimating causal effects from a treatment on an outcome in scientific applications. In this work, we a
arXiv:2604.08754v1 Announce Type: new Abstract: We introduce IKKA (Inversion Classification via Critical Anomalies), a topologically motivated weighting framework for robust visual servoing under dist
'I'm just contemplating the fact that one moron, one psychotic moron, one capricious idiot, has completely bollocksed up the global economy not only to the detriment of his own people, but the detrime
arXiv:2601.05383v4 Announce Type: replace Abstract: Imitation learning (IL) provides a data-driven framework for approximating policies for large-scale combinatorial optimisation problems formulated a
This Reddit discussion on r/MachineLearning explores the practical implementation details of backpropagation in Siamese networks, which consist of two or more identical subnetworks with shared weights
arXiv:2604.09478v1 Announce Type: new Abstract: Geometric high-fidelity mesh reconstruction from LiDAR-inertial scans remains challenging in large, complex indoor environments -- such as cultural buil
arXiv:2604.08646v1 Announce Type: new Abstract: Instruction-based video editing is a natural way to control video content with text, but adapting a video generation model into an editor usually appear
arXiv:2604.09512v1 Announce Type: new Abstract: Transformers have emerged as the dominant neural-network architecture, achieving state-of-the-art performance in language processing and computer vision