Knowledge catalogue
arXiv:2606.05875v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language model (LLM) answer quality by grounding generation in external evidence, but processing ret
arXiv:2606.06316v1 Announce Type: cross Abstract: Financial crashes, cascading failures in infrastructure, and critical errors in AI systems are frequently triggered by events that occur with extremel
arXiv:2505.11766v4 Announce Type: replace-cross Abstract: Neural Operators (NOs) are powerful architectures for learning mappings between function spaces. While most advances focus on refining kernel
arXiv:2606.05555v1 Announce Type: cross Abstract: Scaling reinforcement learning (RL) to diverse multitask settings remains a central challenge. While recent advances in model-based RL achieve strong
Knowledge scaling—increasing the volume of learned information—provides reliable performance on familiar tasks but limited flexibility when facing novel problems. Intelligence, by contrast, enables ad
arXiv:2509.24882v2 Announce Type: replace-cross Abstract: Neural scaling laws underlie many of the recent advances in deep learning, yet their theoretical understanding remains largely confined to lin
arXiv:2606.05625v1 Announce Type: new Abstract: Implicit reward hacking is hard to audit when a language model's chain of thought appears benign: a final answer may be anchored by a prompt shortcut wh
arXiv:2602.22067v2 Announce Type: replace Abstract: Grounding is a critical step in classical planning, yet it often becomes a computational bottleneck due to the exponential growth in grounded action
arXiv:2406.08966v3 Announce Type: replace-cross Abstract: The separation power of a machine learning model refers to its ability to distinguish between different inputs and is often used as a proxy fo
arXiv:2606.05510v1 Announce Type: new Abstract: Telehealth systems have become increasingly important for delivering accessible and timely medical information. Existing large language models often str
arXiv:2602.19373v3 Announce Type: replace-cross Abstract: Deep reinforcement learning systems often suffer from unstable training dynamics due to non-stationarity, where learning objectives and data d
arXiv:2606.06102v1 Announce Type: new Abstract: Ultra-short-term solar irradiance prediction is critical for photovoltaic system dispatch and power grid stability. Existing approaches suffer from thre
arXiv:2606.05217v1 Announce Type: cross Abstract: We exhibit an exact correspondence between sampling with score-based diffusion models and adiabatic transport of ground states for a family of Schrodi
This is an actual page on the White House web site. It reads like something written about a third world dictator. So embarrassing. I have not seen any branch of the federal government sink this low in
This is really stupid, and it’s not getting enough attention. The Trump administration is pulling a working $368 million ocean monitoring system out of the water, equipment taxpayers already bought, b
arXiv:2606.05481v1 Announce Type: cross Abstract: Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining usefu
arXiv:2606.06034v1 Announce Type: cross Abstract: Matrix inversion in chunk-wise parallel linear attention is a major bottleneck for long-context modeling, particularly on NPUs, where forward-substitu
arXiv:2606.05528v1 Announce Type: new Abstract: Existing frameworks assess whether AI systems might be conscious but provide no guidance on what to do with that assessment. We address this gap with a
arXiv:2606.05654v1 Announce Type: cross Abstract: Hate moderation is often evaluated as classification on clean English inputs, but deployed systems must route content to actions such as ALLOW, FLAG,
arXiv:2606.05262v1 Announce Type: cross Abstract: Uncrewed aerial vehicles (UAVs) are increasingly considered as aerial platforms capable of providing both sensing and communication services, represen
You have to read this. Trump demolished the East Wing of the White House and replaced it with a private ballroom funded by corporate donors. Now we know what they got for it. More than half of the pub
arXiv:2606.05330v1 Announce Type: new Abstract: Large language models can shift human beliefs across high-stakes domains, but most persuasion studies rely on pre/post belief change. These endpoint mea
arXiv:2606.05236v1 Announce Type: new Abstract: Robotic arms capable of traversing arbitrary spatial paths, especially in highly obstructed workspaces, are highly desired across several industries. Qu
arXiv:2606.06407v1 Announce Type: new Abstract: Medical imaging artificial intelligence has achieved strong performance in isolated image interpretation, but remains poorly aligned with radiological p
arXiv:2510.05544v2 Announce Type: replace Abstract: Large language models (LLM) and vision-language models (VLM) have achieved state-of-the-art performance, but they impose significant memory and comp
arXiv:2606.05742v1 Announce Type: new Abstract: Speculative decoding accelerates generation by verifying multiple drafted tokens in a single target-model forward pass, reducing sequential decoding ite
arXiv:2606.05840v1 Announce Type: cross Abstract: Nonlinear Model Predictive Control requires solving a constrained nonlinear program (NLP) in real-time at every sampling instant, a computational bott
arXiv:2606.05620v1 Announce Type: new Abstract: Recursion enables the generation of hierarchical linguistic structures but imposes substantial processing demands during real-time comprehension. While
This week I’ve been at SXSW London. There’s been music, film, and a lot—and I mean a lot—of talk about AI. I also had the opportunity to sit down with Gloria Mark, a psychologist at the University of
arXiv:2606.05999v1 Announce Type: new Abstract: Cloud removal aims to accurately reconstruct the ground objects obscured by clouds in remote sensing images. Existing Transformer-based methods utilizin
arXiv:2606.06047v1 Announce Type: new Abstract: Errors in speech translations reduce trustworthiness of Speech Translation (ST) systems and can have serious consequences. Yet currently there is no est
arXiv:2606.05778v1 Announce Type: new Abstract: Traditional Image Aesthetic Assessment (IAA) methods mainly rely on regressing absolute Mean Opinion Scores (MOS). However, such a paradigm overlooks th
arXiv:2512.08560v3 Announce Type: replace Abstract: Understanding how the human brain represents visual concepts, and in which brain regions these representations are encoded, remains a long-standing
arXiv:2606.05515v1 Announce Type: new Abstract: Learning representations of CAD models is a largely open problem. While 3D representation learning has flourished around point clouds and meshes, the na
arXiv:2606.05799v1 Announce Type: cross Abstract: Existing calibration methods for Large Language Models (LLMs) often overlook a critical dimension of trustworthiness: a model's {em behavioral robustn
arXiv:2606.05478v1 Announce Type: new Abstract: Diffusion Models (DM) have revolutionized text-driven generation by enabling the synthesis of high-quality, photorealistic visual content from user prom
arXiv:2601.12983v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are increasingly used to automate chart generation from data tables, improving analysis and reporting effic
arXiv:2606.05568v1 Announce Type: cross Abstract: While ColBERT is an effective neural retrieval architecture, it requires a heavy index structure to support candidate set retrieval based on approxima
arXiv:2606.06359v1 Announce Type: new Abstract: In this study, UAV multispectral imagery is used to segment the severity of bacterial leaf blight (BLB) in rice using convolutional neural networks (CNN
arXiv:2606.06142v1 Announce Type: new Abstract: Event-to-frame (E2F) reconstruction bridges asynchronous event streams with frame-based vision pipelines, but existing methods often face a trade-off be
Congrats to Reardon and team on @flourishailabs. If they can get AI sample efficiency and energy consumption to human levels, thats going to change so many things in the world! And we are live! https:
arXiv:2510.05709v2 Announce Type: replace-cross Abstract: LLM benchmarking metrics often misstate performance and uncertainty as they rely on two assumptions that frequently do not hold in practice: (
arXiv:2509.04027v3 Announce Type: replace-cross Abstract: Test-time scaling, primarily manifested through multi-step Chain-of-Thought (CoT) reasoning via Reinforcement Learning (RL), has emerged as a
arXiv:2606.06306v1 Announce Type: new Abstract: Factual sycophancy occurs when a language model abandons a correct, verifiable answer under social pressure. Because a flip occurs only when pressure to
arXiv:2606.05379v1 Announce Type: new Abstract: To develop and evaluate deep learning models for automated grading of age-related macular degeneration (AMD) severity using optical coherence tomography
arXiv:2606.05998v1 Announce Type: new Abstract: Oral 3D modelling is one of the most essential stages in dentistry, and many different approaches, such as impression taking and intraoral scanning, are
arXiv:2606.05728v1 Announce Type: cross Abstract: Generating executable tool plans requires selecting appropriate subsets from tool libraries, a combinatorial search problem with an exponentially larg
arXiv:2606.05758v1 Announce Type: new Abstract: Many modern vision-language models (VLMs) build on autoregressive decoding of discrete tokens. While text-based output interfaces enable scalable pretra
arXiv:2601.18383v2 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) excel at solving complex problems by explicitly generating a reasoning trace before deriving the final answer. H
arXiv:2606.05372v1 Announce Type: new Abstract: Vector-field-based methods are widely used for robot control and are often applied to the path-tracking problem. Some vector field approaches require re
arXiv:2606.05816v1 Announce Type: new Abstract: T2I models cannot effectively capture sentiment from various types of text, including diaries, as they primarily focus on visual object-related patterns
arXiv:2606.05760v1 Announce Type: new Abstract: Deepfake videos are increasingly challenging the credibility of online content. Many existing detection methodology relies on complex, resource-intensiv
arXiv:2606.05949v1 Announce Type: new Abstract: Scientific illustrations are essential tools for communicating research findings, especially in natural science, where they visualize complex concepts a
Find an important unsolved problem you care about. Then use AI to solve it. Go deep! Talk to people. Build a community. It might take you months or years, but always know that AI capabilities will onl
arXiv:2606.06066v1 Announce Type: new Abstract: Typography generation in diffusion models faces a persistent trade-off: enabling precise font control typically degrades text legibility, while maintain
arXiv:2606.05983v1 Announce Type: cross Abstract: Generative AI makes answers easy and understanding hard, and uncritical use invites cognitive offloading. Schools still measure unaided performance, y
arXiv:2606.05180v1 Announce Type: new Abstract: Automated scoring models are increasingly used to assign rubric-based quality ratings to complex language performances, including classroom transcripts,
arXiv:2606.06002v1 Announce Type: new Abstract: Large Vision-Language Models have achieved significant reasoning performance in various tasks.However, there are few studies on text-to-3D indoor scene
arXiv:2606.06363v1 Announce Type: new Abstract: Urban green-space extraction from ultra-high-resolution (UHR) imagery is commonly performed patch by patch, which limits semantic reuse among spatially
arXiv:2606.06249v1 Announce Type: new Abstract: Transformer-based multimodal models rely on attention mechanisms to integrate information across heterogeneous modalities. Despite their success, existi