Search: “concepts”

arXiv:2503.00992v2 Announce Type: replace Abstract: In this paper we leverage psychological methods to investigate LLMs' conceptual mastery in applying rules. We introduce a novel procedure to match t

Mozilla Corp. rolled out updates today to its popular Firefox browser, updating an artificial intelligence assistant called Smart Window, currently in beta, that lets users check answers, summarize op

arXiv:2608.16273v1 Announce Type: cross Abstract: Foresight-England (Foresight-E) is the first national-scale generative foundation model of electronic health records (EHRs), developed as a research p

arXiv:2603.15427v2 Announce Type: replace-cross Abstract: Robots are increasingly deployed across diverse domains and designed for multi-purpose operation. As robotic systems grow in complexity and op

arXiv:2608.15022v1 Announce Type: new Abstract: Language models hold latent quantities in a form they can report on, and more of a quantity is present in that form when the task requires reusing it fl

arXiv:2608.15400v1 Announce Type: new Abstract: Large Language Models (LLMs) are notorious for struggling with assessing their own uncertainty, detecting knowledge conflicts, or recognizing when probl

arXiv:2608.16424v1 Announce Type: new Abstract: Generative modeling has shown increasing promise for predicting cellular perturbation effects under chemical compound treatments. Existing approaches ei

arXiv:2608.16281v1 Announce Type: new Abstract: Autonomous operation in GNSS-denied environments requires heterogeneous mapping pipelines to maintain a consistent spatial reference. This paper present

arXiv:2608.14835v1 Announce Type: new Abstract: Dynamic scene graphs (DSGs) capture spatio-temporal interactions across videos as langlesubject, predicate, objectrangle triplets, and underpin downstre

arXiv:2608.15802v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection remains challenging for image classifiers, especially when near-OOD samples lie close to in-distribution (ID) class

arXiv:2608.16318v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence (GenAI) have substantially improved the ability of large language models (LLMs) to generate and

arXiv:2608.15834v1 Announce Type: new Abstract: Tool-calling LLM agents navigate unfamiliar codebases with a handful of generic primitives for listing, reading and searching files (ls, cat, grep). A k

arXiv:2303.07152v3 Announce Type: replace-cross Abstract: Achieving optimal statistical performance while ensuring the privacy of personal data is a challenging yet crucial objective in modern data an

arXiv:2602.12381v2 Announce Type: replace Abstract: Recent generative models produce near-photorealistic images, challenging the trustworthiness of photographs. Synthetic image detection (SID) methods

arXiv:2608.15832v1 Announce Type: new Abstract: As AI systems become increasingly capable of autonomous action, determining whether an agent is technically capable of performing an action is insuffici

arXiv:2608.16868v1 Announce Type: cross Abstract: A language model's output does not by itself provide verifiable evidence about the internal computation that produced it. We study computational prove

arXiv:2608.15193v1 Announce Type: cross Abstract: As large language model (LLM) agents are increasingly adopted in scientific research, external knowledge bases, knowledge graphs, and long-term memory

arXiv:2505.04608v5 Announce Type: replace-cross Abstract: Responsibly deploying artificial intelligence (AI) / machine learning (ML) systems in high-stakes settings arguably requires not only proof of

arXiv:2608.14841v1 Announce Type: new Abstract: Long-document visual question answering (VQA) over documents of tens to hundreds of pages mixing text, tables, charts, and figures typically follows ret

arXiv:2608.13900v1 Announce Type: cross Abstract: Large language model (LLM) agents are evolving from conversational assistants into autonomous systems that execute long-horizon tasks through reasonin

arXiv:2608.14352v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents are increasingly used for complex tasks such as software testing and cybersecurity assessment. While these age

If you're running Ollama, llama.cpp, or vLLM behind nginx or HAProxy for more than a single user, you've probably hit this: nginx treats a 10-token prompt and a 10k-token prompt as identical 'one requ

🆕 Context Engineering in 2026: Compaction, Memory & Cost https://www.youtube.com/watch?v=WP3hjUXd918 @Whats_AI, @samridhivaid and @omar_solano1 return! This workshop is about engineering the context w

arXiv:2608.14031v1 Announce Type: new Abstract: We present a demonstration showcasing the Autonomy Testbed for Multi-purpose Orbiting Systems (ATMOS), a planar spacecraft-analog robot designed for har

arXiv:2511.08001v3 Announce Type: replace Abstract: To facilitate effective, safe deployment in the real world, individual robots must reason about interactions with other agents, which often occur wi

arXiv:2608.13684v1 Announce Type: new Abstract: This paper describes a neurosymbolic architecture for learning to assemble novel structures using evidence from embodied conversations and task demonstr

arXiv:2608.14221v1 Announce Type: new Abstract: Autoformalization is commonly framed as translating natural-language mathematical statements into machine-verifiable formal languages such as Lean 4. Ho

arXiv:2608.13944v1 Announce Type: cross Abstract: This paper examines a use of AI in creative practice as an interpretive sounding board for human-generated material, rather than the more familiar pat

arXiv:2608.13607v1 Announce Type: new Abstract: Frontier LLMs are updated frequently and typically outperform their predecessors in aggregate. But aggregate gains say little about individual samples:

arXiv:2608.13974v1 Announce Type: new Abstract: Interpreting the emotional responses triggered by images is central to achieving emotional intelligence. Compared with natural images, visual art is int

Some thoughts on Dario’s post: 1. Dario does not actually address Gavin Baker’s account of what he said – something he could easily deny if it were inaccurate. 2. Dario claims his critics live in a “b

arXiv:2608.14309v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) can generate pathological descriptions from histological images, but gigapixel Whole Slide Images (WSIs) exceed

Here are the gems the AI picked: 1. Sperm whales may have collectively learned how to evade whalers. Within a few years, the success rate of whalers’ harpoons reportedly fell by 58%, suggesting that i

arXiv:2608.12388v1 Announce Type: cross Abstract: The emergence of orientation selectivity in the primary visual cortex (V1) remains a central question in computational neuroscience. Shirazi's Bayes-M

arXiv:2603.04243v3 Announce Type: replace Abstract: Cerebral small vessel disease (CSVD) markers, specifically enlarged perivascular spaces (EPVS) and lacunae, present a unique challenge in medical im

Hey everyone, I'm trying to get a better sense of where classic ML fits in the current landscape, dominated by LLMs and deep learning. Are supervised and unsupervised learning still considered importa

arXiv:2608.13396v1 Announce Type: new Abstract: Shape and force sensing have long been critical bottlenecks in the development of compact capstan-driven continuum surgical robots, primarily due to the

arXiv:2602.01910v2 Announce Type: replace Abstract: Smart-home sensor-based behavioral monitoring holds significant potential for healthcare, independent living, and early detection of functional or c

arXiv:2608.12806v1 Announce Type: cross Abstract: The exceptional generation capabilities of text-to-image diffusion models have raised copyright concerns, particularly the unauthorized reproduction o

arXiv:2608.13316v1 Announce Type: cross Abstract: Foundation models (FMs) trained on large-scale accelerometer data have been proposed as general-purpose feature extractors for health monitoring, but

arXiv:2608.12377v1 Announce Type: cross Abstract: Brains and large language models (LLMs) are fundamentally different memory systems, but they can be compared through shared functional questions: wher

arXiv:2608.13023v1 Announce Type: new Abstract: Relational Deep Learning (RDL) models multi-tabular databases as temporal heterogeneous graphs to enable end-to-end representation learning. However, pr

arXiv:2608.13545v1 Announce Type: cross Abstract: Modern language models are trained on heterogeneous web-scale text corpora. Consequently, studying knowledge and skill acquisition is difficult, as pr

arXiv:2608.12671v1 Announce Type: new Abstract: Multi-layer transformers form the critical component of essentially all large language models (LLMs) in use today. Because of their ubiquity and computa

arXiv:2608.13039v1 Announce Type: new Abstract: The paper introduces the ante-hoc Explainable AI methodology to assess the global feature importance of the Machine Learning models used for heat demand

arXiv:2608.12851v1 Announce Type: new Abstract: Self-improving LLM agents convert successful trajectories into persistent cross-task state. An unsafe success can thereby become reusable policy after i