Knowledge catalogue
arXiv:2608.18083v1 Announce Type: new Abstract: Understanding language requires tracking entities across discourse - i.e., knowing where things are and how they change, even when not explicitly stated
arXiv:2608.18881v1 Announce Type: new Abstract: Autoregressive perception models trained to localize visual entities under the open-vocabulary setting are mostly trained using Supervised fine-tuning (
arXiv:2608.18311v1 Announce Type: cross Abstract: Federated multimodal models often assume every site has every modality, although hospitals differ in access to EHRs, chest radiographs, and ECGs. We s
arXiv:2608.18136v1 Announce Type: new Abstract: Conversational agents now act for end users through tools while holding access to customer databases and internal policy documents that a caller can rea
arXiv:2608.18097v1 Announce Type: new Abstract: We present FrenchNews-7, a cross-publisher France-based French-language news editorial desk classification benchmark combining a large multi-outlet corp
arXiv:2502.00735v4 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly integrated into audio-based applications, growing concerns have emerged regarding their vulne
arXiv:2608.19055v1 Announce Type: new Abstract: Music-driven character animation enables and enhances transformative applications in entertainment and interactive education. However, synthesizing real
We are thrilled to announce that Google has been recognized as a Leader for the third year in a row in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms (CNAP). We believe this
arXiv:2608.18887v1 Announce Type: new Abstract: The epileptogenic zone (EZ) is the brain region that generates seizures in an individual, and is the target of epilepsy surgery. Localizing the EZ from
arXiv:2608.18777v1 Announce Type: new Abstract: Graph generation models have advanced significantly with deep learning, yet they remain limited in scalability, flexibility, and ability to model underl
arXiv:2608.19066v1 Announce Type: cross Abstract: This paper proposes a lightweight, plug-and-play framework that improves robustness to viewpoint shifts in Vision-Language-Action (VLA) policies witho
arXiv:2607.10476v2 Announce Type: replace Abstract: Large language models (LLMs) have emerged as a powerful tool for retrieving knowledge through seamless, human-like interactions. Despite their advan
I've been building AgentGraph Studio, a visual editor for designing multi-agent workflows and exporting them as runnable Python code. One thing I wanted to verify was whether the generated code actual
arXiv:2608.19177v1 Announce Type: new Abstract: Ground Penetrating Radar (GPR) is a widely adopted non-destructive sensing technology for subsurface inspection in civil and transportation engineering.
arXiv:2608.19124v1 Announce Type: cross Abstract: Astrolinguistics -- communication with minds that categorize reality differently from ours -- has been purely speculative since Freudenthal's Lincos (
arXiv:2608.19006v1 Announce Type: new Abstract: Hate speech is a real and timely threat that affects a large portion of online users, especially youth and minority groups. While building reliable and
arXiv:2608.18138v1 Announce Type: cross Abstract: In recent years, the rapid development of language models has transformed the field of Natural Language Processing through a wide range of application
arXiv:2608.19127v1 Announce Type: cross Abstract: A gradient-boosted ensemble predicts by summing one leaf value per tree. Read those values as coordinates rather than as intermediate results, and eve
Links: Preprint: https://doi.org/10.5281/zenodo.22028087 Entropic Scree Function v1.0.0 / GitHub: https://github.com/tjleestjohn/Entropic-Scree TL;DR: Standard PCA fundamentally fractures non-linear d
arXiv:2608.18982v1 Announce Type: new Abstract: Bioassay activity prediction is often data-limited because drug-discovery datasets rely on time-consuming and expensive wet-lab experiments for data gen
arXiv:2608.18716v1 Announce Type: new Abstract: Diagnosing faults in rotating machinery is essential for ensuring the reliability of industrial processes. Random convolutional kernel-based Time Series
arXiv:2608.18094v1 Announce Type: cross Abstract: Large pretrained language models have demonstrated remarkable capabilities across diverse languages, yet critically underrepresented low-resource lang
arXiv:2608.18109v1 Announce Type: new Abstract: Narrative Entropy (S_n) is a proposed quantitative descriptor within the Bulut Doctrine, intended to capture the rate at which a narrative text imposes
arXiv:2608.18531v1 Announce Type: new Abstract: Industrial explainable-recommendation systems built on LLMs incur a substantial serving cost: each request triggers an LLM generation, with latency in t
arXiv:2608.19188v1 Announce Type: new Abstract: Dual-arm robotic grasping is essential for manipulating large, heavy, and geometrically complex objects that cannot be reliably handled using a single m
arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying tran
arXiv:2511.12850v2 Announce Type: replace Abstract: Topic models are often judged by the consistency of their outputs across repeated runs, implicitly assuming that repeatable topic output is a succes
arXiv:2608.18317v1 Announce Type: new Abstract: Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction m
arXiv:2608.18104v1 Announce Type: new Abstract: Large language model (LLM)-based agents are increasingly becoming self-evolving systems that persist across interactions, maintain memories, use tools,
arXiv:2608.18933v1 Announce Type: cross Abstract: Large language model (LLM) based agents have demonstrated remarkable proficiency in automated software issue resolution, yet they often struggle to re
arXiv:2608.18144v1 Announce Type: cross Abstract: Modal auxiliaries such as must, should, and have to mark necessity and obligation within the contexts of speaker authority and interpersonal stance. W
arXiv:2608.18504v1 Announce Type: new Abstract: Universal multimodal retrieval aims to support diverse instruction-aware retrieval tasks, demanding both efficient corpus-scale matching and fine-graine
arXiv:2608.18825v1 Announce Type: cross Abstract: Medical automatic speech recognition (MedASR) requires adaptation to specialised terminology, limited annotated clinical data, and multilingual use ca
arXiv:2608.18628v1 Announce Type: cross Abstract: Aligned vision-language models (VLMs) are designed to balance grounded visual reasoning with safe generation behavior. However, we observe a striking
arXiv:2608.19063v1 Announce Type: new Abstract: PSMA and FDG PET/CT visualise complementary biological information in prostate cancer. Combining both tracers could capture heterogeneous tumour phenoty
arXiv:2608.17184v1 Announce Type: new Abstract: Job Safety Analysis (JSA) and pre-task planning can benefit from prior incident records, yet historical accident data is often stored as unstructured na
arXiv:2608.17684v1 Announce Type: new Abstract: Self-evolving agents turn experience into reusable skills, workflows, or memories, but post-evolution accuracy alone does not show whether learned behav
arXiv:2608.17911v1 Announce Type: new Abstract: As LLM agents operate across structured workflows and sessions, preserving long-term history does not ensure that later contexts can recover relevant ev
arXiv:2608.16919v1 Announce Type: cross Abstract: Recent advances in large language models and agent-based recommendation frameworks have introduced new opportunities for more flexible and context-awa
arXiv:2608.17060v1 Announce Type: new Abstract: Distinguishing a genuine foul from a simulated dive in football remains one of the sport's most contested fine-grained recognition problems, especially
arXiv:2608.17234v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used to interact with screenshots, scanned documents, diagrams, and other visually grounded
arXiv:2608.17366v1 Announce Type: new Abstract: Merging finetuned models combines specialized capabilities without joint training or access to the original data. Most methods operate by linear arithme
arXiv:2604.06474v2 Announce Type: replace Abstract: Deep research with Large Language Model (LLM) agents is emerging as a powerful paradigm for multi-step information discovery, synthesis, and analysi
arXiv:2608.18034v1 Announce Type: new Abstract: Academic surveys play a central role in organizing rapidly expanding scholarly literature, yet their construction requires extensive paper analysis, coh
arXiv:2608.17567v1 Announce Type: cross Abstract: Pretrained molecular language models are increasingly used as molecular encoders for learning structure-property relationships. However, their practic
arXiv:2505.22104v2 Announce Type: replace Abstract: Shielding has emerged as a promising approach for ensuring safety of AI-controlled autonomous systems. The algorithmic goal is to compute a shield,
arXiv:2507.15240v2 Announce Type: replace Abstract: For classification with imbalanced class frequencies, i.e., imbalanced classification (IC), standard accuracy is known to be misleading as a perform
arXiv:2608.17247v1 Announce Type: new Abstract: Personalized agents must decide whether retrieved user memory should be used, ignored, updated, or queried before it affects a current task. We use this
arXiv:2608.17103v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) have achieved remarkable performance in node classification tasks, motivating growing interest in methods capable of expl
arXiv:2607.16660v2 Announce Type: replace-cross Abstract: The increasing adoption of Large Language Models (LLMs) as AI components in modern software systems introduces distinct security risks to the
arXiv:2608.17425v1 Announce Type: new Abstract: Effective segmentation of multi-modal MRI is central to improving neural network accuracy in brain tumor recognition. Existing methods typically compres
Hermes now leverages NVIDIA's SkillEvaluator on skill installs, checking for PII, leaked secrets, Unicode smuggling, licensing and security issues before you confirm. We pointed it at our own bundled
arXiv:2507.06185v2 Announce Type: replace-cross Abstract: In July 2025, 18 academic manuscripts on arXiv contained hidden instructions that manipulated AI-assisted peer review (indirect prompt injecti
arXiv:2608.18028v1 Announce Type: new Abstract: Initialization-free bundle adjustment (InitFree BA) aims to recover camera poses and scene structure directly from image observations, avoiding the geom
arXiv:2608.17393v1 Announce Type: new Abstract: Reinforcement learning for coding agents increasingly relies on long-running agent harnesses to manage tool integration, repository contexts, and execut
arXiv:2509.10818v2 Announce Type: replace Abstract: When consequential decisions depend on knowledge that exists nowhere in writing, LLMs hallucinate not from retrieval failure but from model absence.
arXiv:2608.17519v1 Announce Type: new Abstract: Vision-based surgical skill assessment has shown strong in-domain results, yet a fundamental question remains unasked: do these models learn transferabl
arXiv:2608.17704v1 Announce Type: new Abstract: Monitoring nature restoration at scale is an important but difficult ecological problem. Deep learning methods to analyze satellite image time series (S
arXiv:2606.13113v2 Announce Type: replace-cross Abstract: Underactuated spacecraft faces controllability limitations and heightened sensitivity to environmental disturbances, complicating attitude man
arXiv:2608.16966v1 Announce Type: new Abstract: In modern intelligent transportation systems, it is essential to accurately estimate vehicle positions, especially in mixed traffic conditions where bot