Knowledge catalogue
arXiv:2604.22762v1 Announce Type: cross Abstract: Contemporary product analytics systems require users to pose explicit queries, such as writing SQL, configuring dashboards, or constructing funnels, b
arXiv:2604.24665v1 Announce Type: cross Abstract: This paper investigates whether source trustworthiness shapes Turkish evidential morphology and whether large language models (LLMs) track this sensit
arXiv:2604.24512v1 Announce Type: new Abstract: As LLM agents transition to autonomous digital coworkers, maintaining deterministic goal-directedness in non-linear multi-turn conversations emerged as
arXiv:2604.22989v1 Announce Type: cross Abstract: Recent medical multimodal foundation models are built as multimodal LLMs (MLLMs) by connecting a CLIP-pretrained vision encoder to an LLM using LLaVA-
arXiv:2601.14952v2 Announce Type: replace-cross Abstract: While large language models now handle million-token contexts, their capacity for reasoning across entire document repositories remains largel
arXiv:2603.04751v2 Announce Type: replace Abstract: Integrating web search tools has significantly extended the capability of LLMs to address open-world, real-time, and long-tail problems. However, ev
arXiv:2604.23277v1 Announce Type: cross Abstract: Long-context large language models remain computationally expensive to run and often fail to reliably process very long inputs, which makes context co
arXiv:2604.22990v1 Announce Type: cross Abstract: Subtle visual anomalies such as hairline cracks, sub-millimeter voids, and low-contrast inclusions are structurally atypical yet visually ambiguous, m
arXiv:2604.22779v1 Announce Type: cross Abstract: Enabling large language models (LLMs) to appropriately abstain from answering questions beyond their knowledge is crucial for mitigating hallucination
arXiv:2604.23957v1 Announce Type: new Abstract: Proactive watermarking offers a promising approach for deepfake tamper detection and localization in short-form videos. However, existing methods often
arXiv:2604.23000v1 Announce Type: new Abstract: In behavioral cloning (BC), policy performance is fundamentally limited by demonstration data quality. Real-world datasets contain trajectories of varyi
arXiv:2603.20806v2 Announce Type: replace Abstract: Multi-label fundus diagnosis requires features that capture both fine-grained lesions and large-scale retinal structure. Many multi-scale medical vi
arXiv:2604.23276v1 Announce Type: cross Abstract: PDF documents contain critical visual elements such as figures, tables, and forms whose accurate extraction is essential for document understanding an
arXiv:2604.24222v1 Announce Type: cross Abstract: Large Language Models (LLMs) excel at general code generation, but their performance drops sharply in enterprise settings that rely on internal privat
arXiv:2604.23129v1 Announce Type: cross Abstract: Knowledge workers face increasing challenges in synthesizing information from multiple documents into structured conceptual understanding. This proces
arXiv:2504.20018v2 Announce Type: replace-cross Abstract: Vector search plays a crucial role in many real-world applications. In addition to single-vector search, multi-vector search becomes important
arXiv:2604.24472v1 Announce Type: cross Abstract: Multi-behavior recommendation aims to predict user conversions by modeling various interaction types that carry distinct intent signals. Recently, gen
arXiv:2510.01409v2 Announce Type: replace Abstract: System logs represent a valuable source of Cyber Threat Intelligence (CTI), capturing attacker behaviors, exploited vulnerabilities, and traces of m
arXiv:2604.23974v1 Announce Type: new Abstract: Fake news generally refers to false information that is spread deliberately to deceive people, which has detrimental social effects. Existing fake news
Open-source vector database startup Qdrant Solutions GmbH today announced three new enterprise-grade capabilities on its cloud service to address performance, availability and compliance requirements
arXiv:2604.22758v1 Announce Type: cross Abstract: Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. T
arXiv:2604.23255v1 Announce Type: cross Abstract: Research shows that dialogue, the interactive process through which participants articulate their thinking, plays a central role in constructing share
arXiv:2604.22939v1 Announce Type: cross Abstract: While the next-token prediction (NTP) paradigm enables large language models (LLMs) to express their intrinsic knowledge, its sequential nature constr
arXiv:2511.01490v2 Announce Type: replace Abstract: As synthetic data becomes widely used in language model development, understanding its impact on model behavior is crucial. This paper investigates
arXiv:2604.24658v1 Announce Type: new Abstract: Scientific publication compresses a branching, iterative research process into a linear narrative, discarding the majority of what was discovered along
arXiv:2603.29957v3 Announce Type: replace-cross Abstract: Recent advances in reasoning Large Language Models (LLMs) have primarily relied on upfront thinking, where reasoning occurs before final answe
arXiv:2602.19019v2 Announce Type: replace Abstract: Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without a
arXiv:2604.01644v2 Announce Type: replace Abstract: Natural language provides an intuitive way to express spatial intent in geospatial applications. While existing localization methods often rely on d
arXiv:2604.22756v1 Announce Type: cross Abstract: Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges reg
arXiv:2604.22436v1 Announce Type: new Abstract: The rapid growth of AI agent ecosystems is transforming how complex tasks are delegated and executed, creating a new challenge of identifying suitable a
arXiv:2604.22413v1 Announce Type: cross Abstract: Graph Transformers can mix information globally, but this flexibility also creates failure modes: some tasks require long-range communication while ot
arXiv:2502.00955v2 Announce Type: replace Abstract: Monte Carlo Tree Search (MCTS) based methods provide promising approaches for generating synthetic data to enhance the self-training of Large Langua
arXiv:2604.22534v1 Announce Type: cross Abstract: Feature engineering for Electronic Health Records (EHR) is complicated by irregular observation intervals, variable measurement frequencies, and struc
arXiv:2604.21952v1 Announce Type: cross Abstract: This work presents a multi-layered methodology for efficiently accelerating multimodal foundation models (MFMs). It combines hardware and software co-
arXiv:2604.22565v1 Announce Type: cross Abstract: Large Language Models (LLMs) can reason well, yet often miss decisive evidence when it is buried in long, noisy contexts. We introduce HiLight, an Evi
arXiv:2508.10695v2 Announce Type: replace-cross Abstract: Personalization is crucial for enhancing both the effectiveness and user satisfaction of language technologies, particularly in information-se
arXiv:2603.02709v2 Announce Type: replace-cross Abstract: We propose a novel framework for sensory-aware sequential recommendation that enriches item representations with linguistically extracted sens
Describe Seattle: I want to live near the sea and I want to live near the forest and I want to live near the mountains and I want to live near a café and I want to live near a library and I want to li
Here is a very common problem when building complex agents. Long-horizon agents (in particular) fail in two ways: the decision-maker can't decompose well, or the skill library goes stale. This new res
Google Cloud Next ‘26 took place this week in Las Vegas, and the energy was incredible as we welcomed over 32,000 leaders, developers, and partners to explore the Agentic Era with us. Across three key
arXiv:2604.20846v1 Announce Type: cross Abstract: Next point-of-interest (POI) recommendation requires modeling user mobility as a spatiotemporal sequence, where different behavioral factors may evolv
arXiv:2604.20862v1 Announce Type: new Abstract: The automation system for Course of Action (CoA) planning is an essential element in future warfare. As maneuver speeds increase, surveillance ranges ex
arXiv:2604.21724v1 Announce Type: new Abstract: Large token-indexed lookup tables provide a compute-decoupled scaling path, but their practical gains are often limited by poor parameter efficiency and
arXiv:2604.21573v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables spatially resolved gene profiling but remains expensive and low-throughput, limiting large-cohort studies and routi
arXiv:2604.20987v1 Announce Type: new Abstract: Long horizon interactive environments are a testbed for evaluating agents skill usage abilities. These environments demand multi step reasoning, the cha
arXiv:2604.21890v1 Announce Type: new Abstract: Event extraction identifies the central aspects of events from text. It supports event understanding and analysis, which is crucial for tasks such as in
arXiv:2502.09795v3 Announce Type: replace Abstract: Planetary exploration using aerial assets has the potential for unprecedented scientific discoveries on Mars. While NASA's Mars helicopter Ingenuity
arXiv:2604.21133v1 Announce Type: new Abstract: We present GRISP (Guided Recurrent IRI Selection over SPARQL Skeletons), a novel SPARQL-based question-answering method over knowledge graphs based on f
arXiv:2604.21027v1 Announce Type: new Abstract: Electronic health record (EHR) question answering is often handled by LLM-based pipelines that are costly to deploy and do not explicitly leverage the h
arXiv:2604.21453v1 Announce Type: new Abstract: Visual Active Tracking (VAT) aims to control cameras to follow a target in 3D space, which is critical for applications like drone navigation and securi
arXiv:2604.21794v1 Announce Type: new Abstract: Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and or
arXiv:2604.21637v1 Announce Type: new Abstract: Where and how language models (LMs) are deployed determines who can benefit from them. However, there are several challenges that prevent effective depl
arXiv:2604.21536v1 Announce Type: cross Abstract: Sequential recommender systems have achieved significant success in modeling temporal user behavior but remain limited in capturing rich user semantic
arXiv:2604.21728v1 Announce Type: new Abstract: Pretrained vision-language models such as CLIP exhibit strong zero-shot generalization but remain sensitive to distribution shifts. Test-time adaptation
arXiv:2604.21284v1 Announce Type: new Abstract: MemPalace is an open-source AI memory system that applies the ancient method of loci (memory palace) spatial metaphor to organize long-term memory for l
arXiv:2604.21144v1 Announce Type: cross Abstract: Situated dialogue requires speakers to maintain a reliable representation of shared context rather than reasoning only over isolated utterances. Curre
arXiv:2604.20273v1 Announce Type: new Abstract: We present ActuBench, a multi-agent LLM pipeline for the automated generation and evaluation of advanced actuarial assessment items aligned with the Int
arXiv:2604.20263v1 Announce Type: cross Abstract: Virtual cell modeling predicts molecular state changes under genetic perturbations in silico, which is essential for biological mechanism studies. How
arXiv:2604.20795v1 Announce Type: new Abstract: This paper presents a hybrid architecture for intelligent systems in which large language models (LLMs) are extended with an external ontological memory
arXiv:2509.25844v3 Announce Type: replace Abstract: When people query Vision-Language Models (VLMs) but cannot see the accompanying visual context (e.g. for blind and low-vision users), augmenting VLM