Knowledge catalogue
arXiv:2604.11817v1 Announce Type: cross Abstract: Hybrid quantum-classical models offer a promising route for learning from complex data; however, their application to multi-band remote sensing imager
arXiv:2603.29977v2 Announce Type: replace-cross Abstract: Multimodal deep learning for cancer prognosis is commonly assumed to benefit from synergistic cross-modal interactions, yet this assumption ha
arXiv:2604.12834v1 Announce Type: cross Abstract: Radio frequency fingerprints (RFFs) enable secure wireless authentication but struggle in open-set scenarios with unknown devices and varying channels
arXiv:2604.11992v1 Announce Type: cross Abstract: 3D Gaussian Splatting is a powerful visual representation, providing high-quality and efficient 3D scene reconstruction, but it is crucially dependent
arXiv:2604.11820v1 Announce Type: cross Abstract: As data-privacy regulations tighten and statistical models are increasingly deployed on sensitive human-sourced data, privacy-preserving linear regres
arXiv:2509.08660v3 Announce Type: replace Abstract: Replication of experimental results has been a challenge faced by many scientific disciplines, including the field of machine learning. Recent work
arXiv:2604.13021v1 Announce Type: cross Abstract: Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel disease (IBD), yet the representational choices t
arXiv:2604.12894v1 Announce Type: new Abstract: We present CUBE (Control-based Unified B-spline Encoding), a new geometric representation for human faces that combines B-spline volumes with learned fe
arXiv:2604.12195v1 Announce Type: new Abstract: Work in cognitive science and artificial intelligence has suggested that exposing learning agents to traces of interaction between multiple individuals
arXiv:2604.11947v1 Announce Type: cross Abstract: Unlocking large-scale low-bandwidth decentralized training has the potential to utilize otherwise untapped compute resources. In centralized settings,
arXiv:2501.13340v4 Announce Type: replace Abstract: Diffusion models (DMs) have recently demonstrated remarkable generation capability. However, their training generally requires huge computational re
arXiv:2604.12169v1 Announce Type: new Abstract: We present a screw geometry-based manipulation planning framework for the robotic automation of solution-based synthesis, exemplified through the prepar
arXiv:2511.21211v3 Announce Type: replace Abstract: Gene prioritization (identifying genes potentially associated with a biological process) is increasingly tackled with Artificial Intelligence. Howev
arXiv:2604.12079v1 Announce Type: cross Abstract: Traditional machine learning depends on high-precision arithmetic and near-ideal hardware assumptions, which is increasingly challenged by variability
arXiv:2604.12271v1 Announce Type: new Abstract: Multimodal attributed graphs (MAGs) combine multimodal node attributes with structured relations. However, existing methods usually perform shared messa
arXiv:2604.12988v1 Announce Type: cross Abstract: Execution Accuracy (EX), the widely used metric for evaluating the effectiveness of Natural Language to SQL (NL2SQL) solutions, is becoming increasing
arXiv:2604.12319v1 Announce Type: new Abstract: Multimodal semantic segmentation has emerged as a powerful paradigm for enhancing scene understanding by leveraging complementary information from multi
arXiv:2604.12446v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models have achieved remarkable success in image synthesis, but their reliance on large-scale data and open ecosystems i
arXiv:2604.12752v1 Announce Type: new Abstract: In-context learning (ICL) enables medical image segmentation models to adapt to new anatomical structures from limited examples, reducing the clinical a
arXiv:2604.13035v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) increasingly generate indoor scenes through intermediate structures such as layouts and
arXiv:2604.12377v1 Announce Type: cross Abstract: Korean is a morphologically rich language with a featural writing system in which each character is systematically composed of subcharacter units know
This is a community discussion post on the r/MachineLearning subreddit where a researcher shares their proposed methodology for tackling Open Set Recognition (OSR) and/or novelty detection, inviting p
arXiv:2602.15876v1 Announce Type: cross Abstract: Adapting instruction to the fine-grained needs of individual students is a powerful application of recent advances in large language models. These gen
Sakana AI is hiring a Software Engineer focused on Research and Development, as shared by David Ha (known as hardmaru on X), who is a co-founder of the Tokyo-based AI research company. The role likely
arXiv:2604.12110v1 Announce Type: new Abstract: Recent advances in recommendation scaling laws have led to foundation models of unprecedented complexity. While these models offer superior performance,
arXiv:2604.12254v1 Announce Type: cross Abstract: SpanKey is a lightweight way to gate inference without encrypting weights or chasing leaderboard accuracy on gated inference. The idea is to condition
arXiv:2412.07238v3 Announce Type: replace Abstract: The identity of a speaker influences language comprehension through modulating perception and expectation. This review explores speaker effects and
arXiv:2604.12247v1 Announce Type: cross Abstract: Speculative decoding has emerged as a promising approach to accelerate autoregressive inference in large language models (LLMs). Self-draft methods, w
arXiv:2604.12746v1 Announce Type: new Abstract: Stress remains a significant social problem for individuals in modern societies. This paper presents a machine learning approach for the automatic detec
arXiv:2604.11890v1 Announce Type: new Abstract: We study signal propagation at initialization in transformers through the averaged partial Jacobian norm (APJN), a measure of gradient amplification acr
arXiv:2508.04282v3 Announce Type: replace Abstract: Recent benchmarks for memory-augmented reinforcement learning (RL) have introduced partially observable Markov decision process (POMDP) environments
arXiv:2604.12534v1 Announce Type: new Abstract: Similarity in formal argumentation has recently gained attention due to its significance in problems such as argument aggregation in semantics and enthy
arXiv:2604.12097v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in daily applications, from content generation to code writing, where each interaction treats the mod
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. NASA is building the first nuclear reactor-powered interplanet
arXiv:2604.12099v1 Announce Type: cross Abstract: Analyses of document collections often require selecting what data to analyze, as not all documents are relevant to a particular research question and
arXiv:2604.12289v1 Announce Type: cross Abstract: Online hate speech is associated with substantial social harms, yet it remains unclear how consistently platforms enforce hate speech policies or whet
arXiv:2604.11962v1 Announce Type: new Abstract: Identifying and understanding the features that a deep network (DN) extracts from its inputs to produce its outputs is a focal point of interpretability
arXiv:2604.11828v1 Announce Type: new Abstract: Science is widely regarded as humanity's most reliable method for uncovering truths about the natural world. Yet the trajectory of scientific discovery
arXiv:2604.11998v1 Announce Type: cross Abstract: Cross-domain few-shot object detection (CD-FSOD) remains a challenging problem for existing object detectors and few-shot learning approaches, particu
arXiv:2604.12046v1 Announce Type: new Abstract: Large language models (LLMs) often hallucinate in long-form generation. Existing approaches mainly improve factuality through post-hoc revision or reinf
arXiv:2604.12216v1 Announce Type: cross Abstract: The widespread use of Large Language Models (LLMs) in text generation has raised increasing concerns about intellectual property disputes. Watermarkin
Francois Chollet makes the observation that achieving a perfect score on certain AI benchmark games or tasks only requires surpassing the median performance of an unfiltered random population sample,
arXiv:2604.12931v1 Announce Type: cross Abstract: Token-based semantic communication is promising for future wireless networks, as it can compact semantic tokens under very limited channel capacity. H
arXiv:2604.12503v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown remarkable capabilities across various tasks but remain prone to hallucinations in knowledge-intensive scenari
arXiv:2604.12309v1 Announce Type: new Abstract: We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generati
arXiv:2604.10861v1 Announce Type: cross Abstract: The computational demands of deep learning motivate the investigation of alternative approaches to computation. One alternative is physical neural net
arXiv:2511.06424v2 Announce Type: replace-cross Abstract: While zero-shot diffusion-based compression methods have seen significant progress in recent years, they remain notoriously slow and computati
arXiv:2604.12015v1 Announce Type: cross Abstract: In-context learning (ICL) performance depends critically on which demonstrations are placed in the prompt, yet most existing selectors prioritize heur
arXiv:2604.11833v1 Announce Type: new Abstract: Despite the popularity of Convolutional Neural Networks (CNN), the problem of uncertainty quantification (UQ) of CNN has been largely overlooked. Lack o
arXiv:2505.14129v2 Announce Type: replace Abstract: Evolution and learning have historically been interrelated topics, and their interplay is attracting increased interest lately. The emerging new fac
arXiv:2604.11843v1 Announce Type: new Abstract: Invisible watermarking for autoregressive (AR) image generation has recently gained attention as a means of protecting image ownership and tracing AI-ge
arXiv:2505.17384v2 Announce Type: replace-cross Abstract: Discrete diffusion models have recently shown great promise for modeling complex discrete data, with masked diffusion models (MDMs) offering a
arXiv:2604.12431v1 Announce Type: cross Abstract: Organisations increasingly outsource privacy-sensitive data transformations to cloud providers, yet no practical mechanism lets the data owner verify
arXiv:2604.12159v1 Announce Type: new Abstract: The task of video geolocalization aims to determine the precise GPS coordinates of a video's origin and map its trajectory; with applications in forensi
arXiv:2602.22394v2 Announce Type: replace Abstract: Vision Transformers (ViTs), when pre-trained on large-scale data, provide general-purpose representations for diverse downstream tasks. However, art
arXiv:2604.12044v1 Announce Type: cross Abstract: Deep learning models may converge to suboptimal solutions despite strong validation accuracy, masking an optimization failure we term Trajectory Devia
arXiv:2510.21697v2 Announce Type: replace Abstract: In this paper we show that visual diffusion models can serve as effective geometric solvers: they can directly reason about geometric problems by wo
This Reddit thread from r/MachineLearning reflects community skepticism about the peer review standards at top ML conferences, with a user expressing surprise that a particular paper received an oral
We are hiring Software Engineers in Tokyo to help us scale Sakana AI’s R&D. If you’re interested in building the data pipelines and full stack infrastructure needed to push the boundaries of automated
Weird how some people always target open-source in AI! First it was: “Open-source AI will destroy the world” (spoiler: it didn't and it won't) Now: “Open-source is a cybersecurity threat because of AI