arXiv:2511.17056v1 Announce Type: new Abstract: Electronic health records (EHRs) form an invaluable resource for training clinical decision support systems. To leverage the potential of such systems in high-risk applications, we need large, structured tabular datasets on which we can build transparent feature-based models. While part of the EHR already contains structured information (e.g. diagnosis codes, […]
SAM 3: Segment Anything with Concepts
arXiv:2511.16719v1 Announce Type: cross Abstract: We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short noun phrases (e.g., “yellow school bus”), image exemplars, or a combination of both. Promptable Concept Segmentation (PCS) takes such prompts […]
Stochastic neutral fractions and the effective population size
arXiv:2502.05062v2 Announce Type: replace-cross Abstract: The dynamics of a general structured population is modelled using a general stochastic differential equation (SDE) with an infinite decomposability property. This property allows the population to be divided into an arbitrary number of allelic components, also known as stochastic neutral fractions. When demographic noise is small, a fast-slow principle […]
The Belief-Desire-Intention Ontology for modelling mental reality and agency
arXiv:2511.17162v1 Announce Type: new Abstract: The Belief-Desire-Intention (BDI) model is a cornerstone for representing rational agency in artificial intelligence and cognitive sciences. Yet, its integration into structured, semantically interoperable knowledge representations remains limited. This paper presents a formal BDI Ontology, conceived as a modular Ontology Design Pattern (ODP) that captures the cognitive architecture of agents […]
Revisiting Multimodal KV Cache Compression: A Frequency-Domain-Guided Outlier-KV-Aware Approach
arXiv:2511.16786v1 Announce Type: cross Abstract: Multimodal large language models suffer from substantial inference overhead since multimodal KV Cache grows proportionally with the visual input length. Existing multimodal KV Cache compression methods mostly rely on attention score to reduce cache size, which makes them are incompatible with established efficient attention kernels (e.g., FlashAttention) and ignores the […]
Fairness Evaluation of Large Language Models in Academic Library Reference Services
arXiv:2507.04224v3 Announce Type: replace-cross Abstract: As libraries explore large language models (LLMs) for use in virtual reference services, a key question arises: Can LLMs serve all users equitably, regardless of demographics or social status? While they offer great potential for scalable support, LLMs may also reproduce societal biases embedded in their training data, risking the […]
Live-SWE-agent: Can Software Engineering Agents Self-Evolve on the Fly?
arXiv:2511.13646v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are reshaping almost all industries, including software engineering. In recent years, a number of LLM agents have been proposed to solve real-world software problems. Such software agents are typically equipped with a suite of coding tools and can autonomously decide the next actions to form complete […]
ResearStudio: A Human-Intervenable Framework for Building Controllable Deep-Research Agents
arXiv:2510.12194v2 Announce Type: replace Abstract: Current deep-research agents run in a ”fire-and-forget” mode: once started, they give users no way to fix errors or add expert knowledge during execution. We present ResearStudio, the first open-source framework that places real-time human control at its core. The system follows a Collaborative Workshop design. A hierarchical Planner-Executor writes […]
SRA-CP: Spontaneous Risk-Aware Selective Cooperative Perception
arXiv:2511.17461v1 Announce Type: new Abstract: Cooperative perception (CP) offers significant potential to overcome the limitations of single-vehicle sensing by enabling information sharing among connected vehicles (CVs). However, existing generic CP approaches need to transmit large volumes of perception data that are irrelevant to the driving safety, exceeding available communication bandwidth. Moreover, most CP frameworks rely […]