Search: “tools”

This post presents a humorous prompt requesting AI image generation of an anachronistic scenario—a medieval knight at the 1346 Battle of Crécy taking a selfie with a silly expression for social media.

We just overhauled our built in Notion skill to take advantage of the new ntn CLI! Check out the docs: https://hermes-agent.nousresearch.com/docs/user-guide/skills/bundled/productivity/productivity-no

arXiv:2603.27517v3 Announce Type: replace-cross Abstract: AI agent frameworks connecting large language model (LLM) reasoning to host execution surfaces -- shell, filesystem, containers, and messaging

arXiv:2512.11855v2 Announce Type: replace-cross Abstract: Enforcing exact symmetry in machine learning models often yields significant gains in scientific applications, serving as a powerful inductive

arXiv:2605.14266v1 Announce Type: new Abstract: Integration of artificial intelligent (AI) agents in higher education is transforming teaching, learning and administrative processes. Although existing

arXiv:2605.14322v1 Announce Type: new Abstract: Language agents are increasingly deployed in complex professional workflows, with tutoring emerging as a particularly high-stakes capability that remain

arXiv:2605.15198v1 Announce Type: cross Abstract: Visual reasoning, often interleaved with intermediate visual states, has emerged as a promising direction in the field. A straightforward approach is

b9172 is a release of llama.cpp that includes binaries for macOS, Linux, Android, Windows, and openEuler platforms with support for various hardware configurations including CPU, Vulkan, CUDA, ROCm, O

arXiv:2605.14883v1 Announce Type: cross Abstract: Mild traumatic brain injury (mTBI) is a prevalent condition that remains difficult to diagnose in its early stages. Oculomotor dysfunction is a well-e

arXiv:2605.14555v1 Announce Type: cross Abstract: Current methods for creating drum loop audio in digital music production, such as using one-shot samples or resampling, often demand non-trivial effor

arXiv:2602.18435v2 Announce Type: replace Abstract: Clustering is widely used for unsupervised structure discovery, yet it offers limited insight into how reliable each individual assignment is. Diagn

arXiv:2605.14799v1 Announce Type: new Abstract: In recent years, computer vision has witnessed remarkable progress, fueled by the development of innovative architectures such as Convolutional Neural N

arXiv:2603.24586v2 Announce Type: replace-cross Abstract: As LLMs are increasingly used as judges in code applications, they should be evaluated in realistic interactive settings that capture partial

arXiv:2605.14495v1 Announce Type: cross Abstract: Multimedia verification requires not only accurate conclusions but also transparent and contestable reasoning. We propose a contestable multi-agent fr

arXiv:2605.15079v1 Announce Type: new Abstract: Croissant has emerged as the metadata standard for machine learning datasets, providing a structured, JSON-LD-based format that makes dataset discovery,

arXiv:2602.08874v2 Announce Type: replace Abstract: Long-context LLMs can infer objectives that are not stated explicitly. This capability is useful for reasoning over documents, code, retrieved evide

arXiv:2605.14249v1 Announce Type: new Abstract: We present EnergyLens, an end-to-end framework for energy-aware large language model (LLM) inference optimization. As LLMs scale, predicting and reducin

arXiv:2605.15085v1 Announce Type: cross Abstract: Nowadays refinery optimization utilizes sheer amounts of data, which can be handled with modern Linear Programming (LP) software, but the interpreting

arXiv:2605.15181v1 Announce Type: new Abstract: Modern image editing models produce realistic results but struggle with abstract, multi step instructions (e.g., ``make this advertisement more vegetari

arXiv:2605.14475v1 Announce Type: new Abstract: Interpreting ultra-high-resolution (UHR) remote sensing images requires models to search for sparse and tiny visual evidence across large-scale scenes.

arXiv:2602.06718v2 Announce Type: replace-cross Abstract: Citations provide the basis for trusting scientific claims; when they are invalid or fabricated, this trust collapses. With the advent of Larg

arXiv:2605.15157v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are prone to compounding errors in dexterous manipulation, where high-dimensional action spaces and contact-rich d

arXiv:2605.14355v1 Announce Type: new Abstract: As AI agents improve, the central question is no longer whether they can solve isolated well-defined financial tasks, but whether they can reliably carr

arXiv:2605.14259v1 Announce Type: new Abstract: Applying Large Language Models (LLMs) to heterogeneous enterprise systems is hindered by hallucinations and failures in multi-hop, n-ary reasoning. Exis

arXiv:2605.14352v1 Announce Type: new Abstract: Elections represent a crucial milestone in a nation's ongoing development. To better understand the political rhetoric from various movements, ranging f

arXiv:2605.14831v1 Announce Type: new Abstract: One of the bottlenecks on the way towards recursively self-improving systems is the challenge of interestingness: the ability to prospectively identify

arXiv:2602.12105v2 Announce Type: replace-cross Abstract: We propose a system for differentiating through solutions to geometry processing problems. Our system differentiates a broad class of geometri

arXiv:2605.14828v1 Announce Type: cross Abstract: Existing clustering methods for functional data often prioritize partitioning accuracy over interpretability, making it challenging to extract meaning

arXiv:2605.13873v1 Announce Type: cross Abstract: Web accessibility aims to ensure that web content and services are usable by people with diverse abilities. In recent years, Large Language Models (LL

arXiv:2605.14552v1 Announce Type: new Abstract: Recent advances in generative models have empowered impressive layered image generation, yet their success is largely confined to graphic design domains

arXiv:2605.14421v1 Announce Type: cross Abstract: We introduce MemLineage, a defense for LLM agent memory that attaches both cryptographic provenance and LLM-mediated derivation lineage to every entry

arXiv:2605.15172v1 Announce Type: cross Abstract: Backdoor attacks pose a serious security threat to large language models (LLMs), which are increasingly deployed as general-purpose assistants in safe

Grok, through a standard subscription, now offers multiple AI capabilities beyond text chat, including image generation, web search via X, and image-to-video conversion. This represents an expansion o

arXiv:2605.14240v1 Announce Type: new Abstract: The recent large-scale emergence of LLMs has left an open space for dealing with their consequences, such as plagiarism or the spread of false informati

PipelineIQ is a Databricks solution that leverages data analytics and AI to provide predictive sales intelligence, enabling sales teams to forecast pipeline outcomes and identify actionable opportunit

arXiv:2605.14002v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) embedded in agentic frameworks have transformed information retrieval from static, long context question answering into op

arXiv:2605.14991v1 Announce Type: cross Abstract: Ovarian cancer is the most lethal gynecologic malignancy: around 60% of patients are diagnosed at an advanced stage, with an associated 5-year surviva

arXiv:2605.14502v1 Announce Type: cross Abstract: Power electronics systems are increasingly exposed to cyber threats due to their integration with digital controllers and communication networks. Howe

Retrieval-Augmented Generation (RAG) is a technique that enhances large language models (LLMs) by enabling them to access and utilize external knowledge sources during response generation. This likely

arXiv:2605.14075v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized natural language processing. Understanding their internal mechanisms is crucial for developing more i

arXiv:2511.13026v3 Announce Type: replace Abstract: Self-reflection mechanisms that rely on purely text-based rethinking processes perform well in most multimodal tasks. However, when directly applied

arXiv:2507.07776v3 Announce Type: replace Abstract: Unrestricted adversarial attacks aim to fool computer vision models without being constrained by ell_p-norm bounds to remain imperceptible to humans

arXiv:2605.14440v1 Announce Type: new Abstract: Partially Observable Markov Decision Processes (POMDPs) are the standard framework for decision-making under uncertainty. While sampling-based methods s

In just a short few months, we have witnessed several artificial intelligence technology events that deserve the overused “unprecedented” descriptor: a highly complex supply chain attack by TeamPCP, A

arXiv:2605.14824v1 Announce Type: new Abstract: Topological clustering, and its main algorithm ToMATo, is a clustering method from Topological Data Analysis (TDA) which has been applied successfully i

arXiv:2605.14607v1 Announce Type: new Abstract: Any new medium, once it emerges, is used for more than the transmission of overt content alone. The information it carries typically operates on two lev