Knowledge catalogue
arXiv:2605.26352v1 Announce Type: new Abstract: Retrieval is increasingly moving from one-shot matching toward interactive reasoning, where language agents iteratively inspect evidence, reformulate qu
arXiv:2605.27314v1 Announce Type: new Abstract: Reactive control is often considered insufficient for multi-objective tasks because conflicting objectives give rise to local minima. We argue this limi
arXiv:2605.27299v1 Announce Type: cross Abstract: Modern intrusion detection systems generate thousands of alerts daily, but alert fatigue severely limits security operations effectiveness due to too
arXiv:2605.26971v1 Announce Type: new Abstract: The proliferation of Reinforcement Learning from Verifiable Rewards (RLVR) datasets has exacerbated provenance collapse due to unclear lineage among exi
arXiv:2605.26862v1 Announce Type: new Abstract: Accurate road segmentation from aerial imagery is fundamental to many geospatial applications. However, existing datasets often suffer from limited scen
Robinhood Markets Inc. today opened its trading and banking platforms to artificial intelligence agents, launching a beta Agentic Trading product and a virtual Agentic Credit Card that can place stock
Robinhood is opening its trading platform to AI agents. In an announcement on Wednesday, Robinhood says traders can now create a separate account for an AI agent and add a specific amount of money, al
arXiv:2605.26452v1 Announce Type: cross Abstract: Safe reinforcement learning (RL) for robotic systems requires policies that improve task performance while satisfying state and input constraints duri
arXiv:2506.03627v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across various tasks by effectively utilizing a prompting strategy. Howe
Roku's redesigned home screen now features larger advertisements that remain visible at all times, and this persistent ad placement has proven more effective in generating revenue. The first major hom
This article discusses implementing role-based access control (RBAC) systems that work for both human users and AI agents, likely addressing how to manage permissions and authentication in environment
arXiv:2605.26241v1 Announce Type: new Abstract: Success in generative modeling across language, image, and video demonstrates that large, well-curated datasets are the key driver for building capable
arXiv:2605.26702v1 Announce Type: cross Abstract: Reliable watermarking of panoramic imagery is fundamentally challenged by arbitrary 3D rotations. As panoramas are defined on the sphere, they natural
arXiv:2504.02993v2 Announce Type: replace-cross Abstract: In this paper, we aim to mitigate congestion in traffic management systems by guiding travelers along system-optimal (SO) routes. However, we
arXiv:2605.26632v1 Announce Type: new Abstract: Diffusion Transformers (DiT) achieve strong performance in image generation but incur substantial inference costs. While prior work has reduced this cos
arXiv:2601.22476v2 Announce Type: replace-cross Abstract: Floorplanning determines the coordinate and shape of each module in Integrated Circuits. With the scaling of technology nodes, in floorplannin
Dreamverse is an AI video generation engine that produces 30 seconds of 1080p video in 4.5 seconds on a single GPU , making it significantly faster than existing systems like Sora. It provides a creat
Sakana AIのオフィスが入居する麻布台ヒルズなどを運営する森ビルのウェブメディア「HILLS LIFE DAILY」に、Sakana AIリサーチサイエンティストのカラーヌワット・タリンへのインタビュー記事が掲載されました。 麻布台ヒルズのデジタルサイネージで上映中の浮世絵風画像生成プロジェクトを起点に、 日本文化を理解するAIモデルの可能性について語っています。約12,000枚の浮世絵でフ
Jordan Novet / CNBC: Salesforce reports Q1 revenue up 13% YoY to 11.13B, vs. 11.05B est., Agentforce annual recurring revenue up 205% to $1.2B, and forecasts Q2 revenue below est. — Salesforce reporte
arXiv:2605.26640v1 Announce Type: cross Abstract: We study the sample complexity of policy gradient for log-growth control -- the problem of learning, from observed state transitions, a feedback gain
arXiv:2605.27006v1 Announce Type: new Abstract: Sampling from learned high-dimensional distributions is a foundational computational problem. We introduce U-turn chains: Markov chains obtained by iter
DigitalOcean introduced a unified batch inference solution designed to enable scalable and cost-efficient AI model inference workloads. The offering allows users to process multiple inference requests
arXiv:2509.24935v2 Announce Type: replace-cross Abstract: Scalability has driven recent advances in generative modeling, yet its principles remain underexplored for adversarial learning. We investigat
arXiv:2605.27134v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown rapid progress in mobile GUI navigation. This paper presents a systematic study of data scaling, benchmarking,
arXiv:2602.09038v2 Announce Type: replace-cross Abstract: LLMs have recently shown strong potential in enhancing node-level tasks on text-attributed graphs (TAGs) by providing explanation features. Ho
arXiv:2605.26282v1 Announce Type: new Abstract: Model-based reinforcement learning (RL) can be effectively supported at scale through the use of world models. However, in practice, scaling such approa
arXiv:2605.27009v1 Announce Type: new Abstract: Predicting human olfactory perception from molecular structure has seen remarkable progress, yet these approaches require explicit chemical structure at
arXiv:2605.26538v1 Announce Type: new Abstract: Style transfer with pre-trained diffusion models has advanced rapidly, but a core question remains underexplored: where in the model should style inject
arXiv:2605.26340v1 Announce Type: new Abstract: Autonomous research agents produce competitive solutions and professional-looking manuscripts, yet their outputs contain verifiability failures undetect
arXiv:2605.27032v1 Announce Type: new Abstract: Accurate pancreas segmentation is critical for early cancer diagnosis, where annotation scarcity necessitates Semi-Supervised Learning (SSL). However, d
arXiv:2512.04868v2 Announce Type: replace-cross Abstract: Knowledge-based conversational question answering (KBCQA) confronts persistent challenges in resolving coreference, modeling contextual depend
arXiv:2509.26619v3 Announce Type: replace-cross Abstract: Many static benchmarks are beginning to saturate: as models rapidly improve, they achieve near-perfect scores on fixed test sets, leaving litt
arXiv:2605.26548v1 Announce Type: cross Abstract: Large language models (LLMs) now support automated software security tasks, including vulnerability discovery and proof-of-concept (PoC) generation. E
arXiv:2510.19420v2 Announce Type: replace-cross Abstract: Multi-Agent Systems (MAS) have become a prevalent paradigm for Large Language Model (LLM) applications. However, the complex multi-agent desig
arXiv:2605.26788v1 Announce Type: cross Abstract: Large language models (LLMs) achieve impressive performance when a task is fully specified in a single turn, yet the same models lose up to 39% of tha
arXiv:2601.07737v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in mainstream visual understanding tasks, but their ability
arXiv:2506.07813v2 Announce Type: replace-cross Abstract: Arbitrary-scale image super-resolution aims to upsample images to any desired resolution, offering greater flexibility than traditional fixed-
arXiv:2605.27298v1 Announce Type: new Abstract: Charts effectively convey quantitative information, but the underlying data are often locked in image form, hindering reuse and analysis. Manually digit
arXiv:2605.26690v1 Announce Type: cross Abstract: Protein sequence optimization under tight oracle budgets requires methods that explore vast combinatorial spaces while making each evaluation informat
Yohei Nakajima discusses the emergence of self-improving AI agents, likely exploring how autonomous agents can iteratively enhance their capabilities and performance through feedback loops and learnin
arXiv:2605.26744v1 Announce Type: new Abstract: Human motion generation has made tremendous progress in recent years, with state-of-the-art approaches surpassing ground truth data in leading evaluatio
arXiv:2510.06843v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have exhibited impressive capabilities across diverse application domains. Recent work has explored Multi-LLM Age
arXiv:2605.26132v1 Announce Type: new Abstract: Can post-trained large language models (LLMs) further improve themselves using only unlabeled prompts, without external teachers or feedback from tools?
arXiv:2605.27322v1 Announce Type: new Abstract: We introduce interaction SSD, an extension of Supervised Semantic Differential that models how semantic meaning varies across moderators such as groups,
arXiv:2605.27155v1 Announce Type: cross Abstract: Testing object detectors in safety-critical domains requires semantically meaningful probes beyond pixel-level corruptions. We present SemProbe, a too
arXiv:2605.27080v1 Announce Type: new Abstract: Appearance-based gaze estimation always suffers from poor generalization due to limited annotated samples and insufficient dataset diversity. Leading ap
arXiv:2605.26324v1 Announce Type: cross Abstract: Learned physics simulators are often evaluated by one-step or short-horizon prediction error, but these metrics can miss failures in temporal composit
arXiv:2605.26239v1 Announce Type: new Abstract: In this work, we study Cooperative Spatial Intelligence, the ability of decentralized embodied agents to coordinate effectively under dynamic environmen
arXiv:2605.26571v1 Announce Type: new Abstract: Federated learning enables collaborative model training without sharing raw data, but its performance can degrade substantially under heterogeneous clie
arXiv:2605.27294v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems can respond incorrectly even when the correct passage was retrieved. The model must still read the retrieve
arXiv:2605.26186v1 Announce Type: cross Abstract: Functionality-correct repository setup aims to configure execution environments (e.g., dependencies, build scripts) to successfully execute a reposito
arXiv:2601.04275v2 Announce Type: replace-cross Abstract: Machine unlearning aims to selectively remove the influence of specific training samples to satisfy privacy regulations such as the GDPR's 'Ri
arXiv:2605.27030v1 Announce Type: new Abstract: Test-Time Scaling (TTS) enhances the reasoning capabilities of large language models by allocating additional inference compute to explore the solution
arXiv:2509.15121v2 Announce Type: replace-cross Abstract: We investigate a WIMP dark matter (DM) candidate in the form of a singlino-dominated lightest supersymmetric particle (LSP) within the Z_3-sym
Delta Weight Sync (DWS) is a technique for efficiently distributing and synchronizing large language models with trillions of parameters across distributed systems using Hugging Face's TRL (Transforme
arXiv:2603.14864v2 Announce Type: replace Abstract: In e-commerce, LLM agents show promise for shopping tasks such as recommendations, budget management, and bundle deals, where accurately capturing u
arXiv:2605.27276v1 Announce Type: new Abstract: Humans are the bottleneck in building and improving AI. Both the models and the agents that wrap them are written, tuned, and corrected by people. The l
arXiv:2605.26973v1 Announce Type: cross Abstract: Neural networks are known to develop latent representations that are aligned, namely structurally similar across networks trained with different archi
arXiv:2605.26509v1 Announce Type: new Abstract: Gaussian processes (GPs) provide a principled Bayesian framework for uncertainty estimation, but their computational complexity severely limits scalabil
arXiv:2605.26135v1 Announce Type: new Abstract: Unsupervised anomaly detection is widely used in transaction fraud detection where labels are scarce. Isolation Forest (IF) is among the most popular cl