Knowledge catalogue
arXiv:2607.22622v1 Announce Type: cross Abstract: Recent Text-to-SQL methods rely heavily on reasoning-centric paradigms such as Chain-of-Thought (CoT), achieving substantial gains on complex benchmar
arXiv:2607.22804v1 Announce Type: cross Abstract: Accurate geological characterization of subsurface reservoirs from well log data is essential to support projects such as carbon capture and storage (
arXiv:2607.24192v1 Announce Type: cross Abstract: We study the problem of lossless compression of source code, motivated by the storage demands of large-scale software archives, such as Software Herit
arXiv:2607.14952v3 Announce Type: replace Abstract: Long-context RL post-training is constrained by the lifetime of state and gradients, not attention cost alone. In GRPO, one multi-million-token prom
arXiv:2607.22564v1 Announce Type: new Abstract: Convolutional neural networks often contain redundant feature maps that increase storage and inference cost. This paper presents a loss-aware feature-ma
Hey everyone! 👋 I'm excited to announce the official release of Manga Coloring Tool 2.0, a completely free, local, open-source web application designed to colorize manga pages and chapters effortlessl
Many AI tools rent intelligence. Kimi K3 on Fireworks is different. Fine-tune it on your own data, serve from US-hosted endpoints, and own the weights. Zero data retention. ICYMI yesterday, start buil
arXiv:2607.22654v1 Announce Type: new Abstract: Vehicle-to-Everything (V2X) communication systems are based on datasets that not only contain vehicle trajectory data but also wireless network paramete
arXiv:2512.03522v3 Announce Type: replace-cross Abstract: Robots are often required to localize in environments with unknown object classes and semantic ambiguity. However, when performing global loca
arXiv:2607.23451v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) aims to retrieve specific objects by integrating complementary information from multiple modalities. However
arXiv:2607.22794v1 Announce Type: cross Abstract: Automatic depression detection with deep learning has shown promise but often suffers from limited generalization due to domain shift arising from int
arXiv:2607.23481v1 Announce Type: new Abstract: This paper presents Mwando, a virtual educational assistant designed to support the teaching and preservation of shiKomori, the language of the Comoros
Open weights let builders own and control their stack, and provide flexibility to optimized quality and performance, instead of being locked into a handful of closed platforms. We think that choice is
arXiv:2607.23110v1 Announce Type: cross Abstract: In this paper, we study the extension of Neural Jump ODEs to infinite-dimensional function spaces. In particular, the underlying process X now takes v
arXiv:2607.22786v1 Announce Type: cross Abstract: In this work, we explore how the inference time of a Transformer Neural Network can be efficiently optimized with applications to real-time anomaly de
arXiv:2603.02063v2 Announce Type: replace Abstract: Although data generation is often straightforward, extracting information from data is more difficult. Object-centric representation learning can ex
arXiv:2607.22797v1 Announce Type: cross Abstract: Trustworthy deployment of AI-based diagnosis in safety-critical mechanical systems hinges on validation: whether a prediction can be checked against p
arXiv:2607.22749v1 Announce Type: cross Abstract: Tracking residual tumor after surgery is essential for catching recurrence early, but automating post-operative glioma segmentation remains a difficul
arXiv:2511.22090v2 Announce Type: replace Abstract: Recent efforts in smart manufacturing have enhanced aerospace fuselage assembly processes, particularly by innovating shape adjustment techniques to
arXiv:2607.22714v1 Announce Type: cross Abstract: Real-time perception is a foundational requirement for advanced driver assistance systems (ADAS) and autonomous vehicles, yet embedded automotive plat
arXiv:2607.24098v1 Announce Type: new Abstract: Referring video object segmentation (RVOS) requires segmenting a target specified by natural language throughout a video. Recent agentic approaches comb
arXiv:2607.22709v1 Announce Type: cross Abstract: The proliferation of internet memes has introduced new complexities to automated content moderation, particularly in detecting misogyny. Memes often r
arXiv:2607.23758v1 Announce Type: new Abstract: Large-scale road surface reconstruction supports high-definition mapping, autonomous-driving perception, annotation, and simulation. Existing road-speci
arXiv:2607.23468v1 Announce Type: new Abstract: Real-time 6-DoF object pose tracking is essential for many robotics applications, and several approaches exist. Yet even today's approaches remain unrel
arXiv:2607.22985v1 Announce Type: cross Abstract: Conformalized selection has been widely applied to select high-quality candidates from large datasets with rigorous uncertainty quantification, such a
arXiv:2607.24706v1 Announce Type: new Abstract: Few-shot segmentation (FSS) commonly assumes clean pixel-level support masks, yet practical support supervision often uses boxes, scribbles, coarse mask
arXiv:2607.23821v1 Announce Type: new Abstract: Identifying therapeutic target genes from single-cell RNA sequencing (scRNA-seq) data remains a fundamental challenge in translational biology. Unlike b
arXiv:2603.15553v2 Announce Type: replace Abstract: The landscape of self-supervised learning (SSL) is currently dominated by generative approaches (e.g. MAE) that reconstruct raw low-level data, and
arXiv:2607.22562v1 Announce Type: new Abstract: Managing long-context dependencies remains a primary bottleneck in LLM agents, as redundant and irrelevant information can degrade multi-step reasoning.
arXiv:2607.22806v1 Announce Type: new Abstract: Modern cloud deployments distribute applications across multiple geographic regions, yet standard routing mechanisms prioritize latency while ignoring t
arXiv:2509.16909v2 Announce Type: replace Abstract: We present SLAM-Former, a neural approach that integrates full SLAM capabilities into a single transformer. Similar to traditional SLAM systems, SLA
arXiv:2607.22584v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation pipelines rank retrieved documents by semantic similarity alone, without accounting for source provenance or cre
arXiv:2607.22875v1 Announce Type: cross Abstract: Accurate estimation of soil microplastics and organic matter is essential to assess ecosystem health and support sustainable land use. This study pres
arXiv:2607.22931v1 Announce Type: cross Abstract: Analytic Continual Learning (ACL) offers a computationally efficient alternative to gradient-based approaches. Recent ACL methods are based on Recursi
arXiv:2607.23284v1 Announce Type: new Abstract: Automated sleep staging is increasingly used in large-scale studies to derive sleep-architecture endpoints: total sleep time, REM latency, sleep efficie
arXiv:2607.23273v1 Announce Type: cross Abstract: Computational nutrition needs precise ingredient data, but current databases are incomplete, inconsistent, and built for human reference rather than a
arXiv:2603.27577v2 Announce Type: replace Abstract: Vision-Language Navigation (VLN) requires an embodied agent to navigate complex environments by following natural language instructions, which typic
arXiv:2607.24206v1 Announce Type: cross Abstract: The introduction of new technologies, such as surgical robots, is driving the vision of a connected, smart operating room (OR). However, realizing thi
arXiv:2607.22807v1 Announce Type: cross Abstract: Although coding agents are now very effective in a variety of programming languages, this paper first shows that the cost (in tokens) can very signifi
arXiv:2607.23509v1 Announce Type: new Abstract: We present two approaches for predicting tennis match outcomes using topological data analysis and graph theory on ATP singles matches from 2000-2025. T
arXiv:2607.24563v1 Announce Type: new Abstract: Security Operations Centers increasingly rely on automated mapping of Cyber Threat Intelligence reports to MITRE ATT&CK, yet extractor outputs remain fa
arXiv:2607.23006v1 Announce Type: cross Abstract: Scientific question answering requires a retrieval system to solve two distinct problems: identifying which papers are relevant and locating the suppo
arXiv:2607.23581v1 Announce Type: new Abstract: Multimodal misinformation verification is challenging because misleading signals may come from different parts of a post and require different forms of
arXiv:2607.24124v1 Announce Type: new Abstract: We introduce ViDS, a Video Diffusion Shader that leverages 3D face tracking for expressive and identity-preserving portrait animation. We first reconstr
arXiv:2607.23888v1 Announce Type: cross Abstract: In the United States, artificial intelligence (AI) is rapidly deployed amid limited federal regulation. With courts become a recurring forum in which
arXiv:2607.23594v1 Announce Type: new Abstract: In prostate cancer histopathology, the Gleason Score is determined by the most frequent (Primary) and second most frequent (Secondary) Gleason patterns
We're opening applications for the OpenAI Student Collective—a program for undergraduate Campus Leads bringing AI innovation to their campuses. Campus Leads will work directly with OpenAI and receive
arXiv:2607.23638v1 Announce Type: new Abstract: Polarimetric Synthetic Aperture Radar (PolSAR) classification underpins all-weather Earth observation. Conventional Wishart methods depend on rigid hand
arXiv:2607.23920v1 Announce Type: new Abstract: Emotional image editing requires more than applying affective filters or modifying predefined visual factors: an effective edit must identify what a par
arXiv:2607.22081v1 Announce Type: new Abstract: Multiclass classification is a fundamental problem across a wide range of domains. It is still challenging due to possession of high inter-class similar
arXiv:2607.22320v1 Announce Type: new Abstract: The passive adaptability inherent in soft robotic hands affords them advantages in applications that require safe and compliant interaction. However, ex
arXiv:2607.22385v1 Announce Type: cross Abstract: Diagnosing the root cause of anomalies is essential for safe industrial operation. Despite extensive sensor instrumentation, formulating hypotheses an
arXiv:2607.17441v1 Announce Type: cross Abstract: Deepfake generation has raised growing concerns regarding digital media authenticity, misinformation, identity fraud, and public trust. Recent studies
I've been working on an open-source workflow automation platform over the past few months, with Ollama as one of the first-class providers rather than treating it as an afterthought. The goal wasn't t
arXiv:2503.07869v4 Announce Type: replace Abstract: Critical learning periods (CLPs) in federated learning (FL) refer to early stages during which low-quality contributions (e.g., sparse training data
arXiv:2607.22511v1 Announce Type: cross Abstract: Automating theoretical research is constrained not only by the generation of candidate results, but also by their reliable evaluation. A common approa
arXiv:2607.22123v1 Announce Type: new Abstract: Visual inertial odometry (VIO) is essential for accurate 6-DoF motion estimation in mobile robotic systems. Recent learning-based VIO methods have shown
arXiv:2607.22446v1 Announce Type: new Abstract: Recent radiance field methods represent scenes with 2D primitives that offer surface alignment and efficient rasterization, from Gaussian disks to trian
arXiv:2606.13842v2 Announce Type: replace Abstract: We present an algorithm for efficient domain-adaptive policy learning via kernel representations. Learning domain-adaptive policies is challenging s
arXiv:2506.18748v2 Announce Type: replace-cross Abstract: We consider resource allocation problems in multi-user wireless networks, where the goal is to optimize a network-wide utility function subjec