Knowledge catalogue
arXiv:2604.15027v1 Announce Type: new Abstract: Significant progress has been made in detecting synthetic images, however most existing approaches operate on a single image instance and overlook a key
arXiv:2604.15151v1 Announce Type: new Abstract: Large language models have demonstrated strong performance on general-purpose programming tasks, yet their ability to generate executable algorithmic tr
arXiv:2602.20370v2 Announce Type: replace Abstract: The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in approx
arXiv:2604.14487v1 Announce Type: new Abstract: Quantization is a natural complement to the sparse, event-driven computation of Spiking Neural Networks, reducing memory bandwidth and arithmetic cost f
arXiv:2604.14287v1 Announce Type: new Abstract: Tensor networks were developed in the context of many-body physics as compressed representations of multiparticle quantum states. These representations
arXiv:2412.14751v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) mitigates hallucination in Large Language Models (LLMs) by using query pipelines to retrieve relevant external
arXiv:2604.15281v1 Announce Type: new Abstract: 3D policy learning promises superior generalization and cross-embodiment transfer, but progress has been hindered by training instabilities and severe o
arXiv:2604.14885v1 Announce Type: new Abstract: Autoregressive decoding in Large Language Models (LLMs) generates one token per step, causing high inference latency. Speculative decoding (SD) mitigate
arXiv:2604.15308v1 Announce Type: new Abstract: High-level autonomous driving requires motion planners capable of modeling multimodal future uncertainties while remaining robust in closed-loop interac
arXiv:2506.13139v2 Announce Type: replace-cross Abstract: Modern Machine Learning (ML) and Deep Neural Networks (DNNs) often operate on high-dimensional data and rely on overparameterized models, wher
arXiv:2604.14951v1 Announce Type: cross Abstract: Tool learning with foundation models aims to endow AI systems with the ability to invoke external resources -- such as APIs, computational utilities,
arXiv:2604.14888v1 Announce Type: new Abstract: Recent advances in vision language models (VLMs) offer reasoning capabilities, yet how these unfold and integrate visual and textual information remains
arXiv:2603.21094v3 Announce Type: replace Abstract: Human annotation is central to NLP evaluation, yet subjective tasks often exhibit substantial variability across annotators. While large language mo
Q-Day—the moment when quantum computers can break widely used cryptography—may be approaching faster than expected due to recent algorithmic and hardware advances. Advances in algorithms and design ar
arXiv:2502.05740v2 Announce Type: replace-cross Abstract: Cancer surgery is a key treatment for gastrointestinal (GI) cancers, a group of cancers that account for more than 35% of cancer-related death
Soft directives don’t stop crawlers from ingesting deprecated content. Redirects for AI Training allows anybody on Cloudflare to redirect verified crawlers to canonical pages with one toggle and no or
arXiv:2511.19204v3 Announce Type: replace Abstract: We present a sampling-based model predictive control (MPC) framework that enables emergent locomotion without relying on handcrafted gait patterns o
arXiv:2604.14876v1 Announce Type: cross Abstract: We study the tail behavior of regret in stochastic multi-armed bandits for algorithms that are asymptotically optimal in expectation. While minimizing
arXiv:2604.14265v1 Announce Type: new Abstract: We study behavior-regularized reinforcement learning (RL), where regularization toward a reference distribution (the dataset in offline RL or the base m
arXiv:2604.14725v1 Announce Type: cross Abstract: Recent advances in query optimization have shifted from traditional rule-based and cost-based techniques towards machine learning-driven approaches. A
Renuka Kumar and Prashanth Ramagopal from the @Cisco team built a LangSmith + LangGraph powered framework for multi-agent coordination that behaves like a real-world software team. An inside look → ht
Replit Agent got even better at keeping you in your creative flow! It now suggests follow-up tasks using full context of your project to build on your ideas: • new features to build • performance impr
Research paper link: https://www.nature.com/articles/s41928-026-01594-4 I break down stories like this every day in my free newsletter. Keep up with the latest in AI/Robotics in 5 min a day: https://w
Resolve AI Inc., a startup that helps enterprises make their infrastructure more reliable, has raised 40 million in funding. DST Global and Salesforce Ventures led the investment. It comes as an exten
arXiv:2604.13392v1 Announce Type: new Abstract: Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy
arXiv:2604.13757v1 Announce Type: new Abstract: The next generation of autonomous AI systems will be constrained not only by model capability, but by how intelligence is structured across heterogeneou
arXiv:2601.20868v2 Announce Type: replace Abstract: Large Language Models (LLMs) have advanced the field of Combinatorial Optimization through automated heuristic generation. Instead of relying on man
arXiv:2604.14656v1 Announce Type: cross Abstract: Most medical multimodal benchmarks focus on static tasks such as image question answering, report generation, and plain-language rewriting. Patient ed
arXiv:2604.14616v1 Announce Type: new Abstract: Clinical value set authoring -- the task of identifying all codes in a standardized vocabulary that define a clinical concept -- is a recurring bottlene
arXiv:2604.14261v1 Announce Type: new Abstract: The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-base
arXiv:2604.14563v1 Announce Type: new Abstract: Vision Transformer (ViT)-based sparse multi-view 3D object detectors have achieved remarkable accuracy but still suffer from high inference latency due
arXiv:2604.14910v1 Announce Type: new Abstract: Achieving high-fidelity generation in extremely few sampling steps has long been a central goal of generative modeling. Existing approaches largely rely
arXiv:2604.05302v2 Announce Type: replace Abstract: Text simplification supports second language (L2) learning by providing comprehensible input, consistent with the Input Hypothesis. However, constru
arXiv:2604.15201v1 Announce Type: new Abstract: As reinforcement learning (RL) deployments expand into safety-critical domains, existing evaluation methods fail to systematically identify hazards aris
arXiv:2604.14973v1 Announce Type: cross Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, bright
SpaceX completed a full-duration static fire test of Starship V3, igniting all 33 Raptor 3 engines at Starbase and clearing the final major technical hurdle before Flight 12. The upgraded megarocket i
arXiv:2604.14353v1 Announce Type: new Abstract: Localization of autonomous mobile robots (AMRs) in enclosed or semi-enclosed environments such as offices, hotels, hospitals, indoor parking facilities,
arXiv:2604.15022v1 Announce Type: cross Abstract: Cost-aware routing dynamically dispatches user queries to models of varying capability to balance performance and inference cost. However, the routing
Roy Rogers demonstrates his preferred style of playing the hurdy-gurdy, showcasing traditional or characteristic technique in this post shared by Jeremy Howard on X. The post reflects appreciation for
Runway's Big Pitch Contest For Shows That Don't Exist Yet. * but that might exist soon Two weeks to pitch a show you wish existed. $100K in cash prizes. Bring your biggest, most ambitious ideas to lif
arXiv:2512.00995v3 Announce Type: replace Abstract: Part-level point cloud segmentation has recently attracted significant attention in 3D computer vision. Nevertheless, existing research is constrain
arXiv:2509.12833v2 Announce Type: replace Abstract: Projection-based safety filters, which modify unsafe actions by mapping them to the closest safe alternative, are widely used to enforce safety cons
arXiv:2604.13630v1 Announce Type: cross Abstract: The performance of large language model (LLM) agents depends critically on the execution harness, the system layer that orchestrates tool use, context
arXiv:2604.14168v1 Announce Type: new Abstract: We introduce SAGE Celer 2.6, the latest in our line of general-purpose Celer models from SAGEA. Celer 2.6 is available in 5B, 10B, and 27B parameter siz
arXiv:2604.07663v2 Announce Type: replace Abstract: The AdamW optimizer, while standard for LLM pretraining, is a critical memory bottleneck, consuming optimizer states equivalent to twice the model's
Trainees from the National Institute for Defense Studies' second-period Security Strategy course visited Sakana AI Corporation on April 8 to learn about the company's latest AI technologies and applic
arXiv:2507.18454v2 Announce Type: replace-cross Abstract: CPUs are critical for LLM serving due to their availability, cost efficiency, and edge applicability. However, efficient CPU serving is hinder
arXiv:2512.08914v2 Announce Type: replace-cross Abstract: Quantum Error Correction (QEC) decoding faces a fundamental accuracy-efficiency tradeoff. Classical methods like Minimum Weight Perfect Matchi
arXiv:2604.14373v1 Announce Type: new Abstract: Rural environmental risks are shaped by place-based conditions (e.g., housing quality, road access, land-surface patterns), yet standard vulnerability i
arXiv:2604.14810v1 Announce Type: cross Abstract: In online clustering problems, there is often a large amount of uncertainty over possible cluster assignments that cannot be resolved until more data
arXiv:2604.14862v1 Announce Type: new Abstract: Constrained decoding has been widely adopted for structured generation with large language models (LLMs), ensuring that outputs satisfy predefined forma
arXiv:2604.13180v1 Announce Type: new Abstract: Recent advances in agentic AI have enabled increasingly autonomous workflows, but existing systems still face substantial challenges in achieving reliab
arXiv:2604.14474v1 Announce Type: new Abstract: Traditional esports scouting workflows rely heavily on manual video review and aggregate performance metrics, which often fail to capture the nuanced de
arXiv:2604.14163v1 Announce Type: new Abstract: Maritime distress communications transmitted over very high frequency (VHF) radio are safety-critical voice messages used to report emergencies at sea.
arXiv:2604.13474v1 Announce Type: cross Abstract: We propose a novel end-to-end privacy-preserving framework, instantiated by three efficient protocols for different deployment scenarios, covering bot
arXiv:2602.13529v2 Announce Type: replace-cross Abstract: Federated learning (FL) enables collaborative training across organizational silos without sharing raw data, making it attractive for privacy-
arXiv:2604.14648v1 Announce Type: new Abstract: Video outpainting aims to expand the visible content of a video beyond the original frame boundaries while preserving spatial fidelity and temporal cohe
arXiv:2604.14865v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly exposed to adaptive jailbreaking, particularly in high-stakes Chemical, Biological, Radiological, and Nucl
arXiv:2603.16869v2 Announce Type: replace Abstract: We introduce SegviGen, a framework that repurposes native 3D generative models for 3D part segmentation. Existing pipelines either lift strong 2D pr
arXiv:2604.15271v1 Announce Type: new Abstract: Reliable uncertainty estimation is critical for medical image segmentation, where automated contours feed downstream quantification and clinical decisio