Knowledge catalogue
arXiv:2604.20403v1 Announce Type: new Abstract: Fault location in distribution grids is critical for reliability and minimizing outage durations. Yet, it remains challenging due to partial observabili
arXiv:2506.02618v2 Announce Type: replace-cross Abstract: Understanding and predicting articulated actions is important in robot learning. However, common architectures such as MLPs and Transformers l
arXiv:2604.20146v1 Announce Type: cross Abstract: Grounded Multimodal Named Entity Recognition (GMNER) aims to extract named entities and localize their visual regions within image-text pairs, serving
arXiv:2505.02242v2 Announce Type: replace Abstract: Diffusion models have recently emerged as the dominant approach in visual generation tasks. However, the lengthy denoising chains and the computatio
arXiv:2604.20003v1 Announce Type: cross Abstract: The integration of single-cell proteomic data is often hindered by the fragmented nature of targeted antibody panels. To address this limitation, we i
arXiv:2604.19777v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit a well-documented positional bias when processing long input contexts: information in the middle of a context win
arXiv:2604.20169v1 Announce Type: new Abstract: We propose Semantic-Fast-SAM (SFS), a semantic segmentation framework that combines the Fast Segment Anything model with a semantic labeling pipeline to
arXiv:2604.20436v1 Announce Type: cross Abstract: Generative AI (GenAI) is reshaping software engineering by shifting development from manual coding toward agent-driven implementation. While vibe codi
This article by Ethan Mollick likely discusses emerging capabilities and implications of GPT-5.5, OpenAI's next-generation language model, exploring how it represents advancement in AI technology and
arXiv:2604.20688v1 Announce Type: cross Abstract: Storm surge forecasting remains a critical challenge in mitigating the impacts of tropical cyclones on coastal regions, particularly given recent tren
arXiv:2604.20727v1 Announce Type: cross Abstract: Training large foundation models for agentic tasks is increasingly impractical due to the high computational costs, long iteration cycles, and rapid o
arXiv:2604.19803v1 Announce Type: new Abstract: Agentic AI is rapidly transforming the way research is conducted, from prototyping ideas to reproducing results found in the literature. In this paper,
arXiv:2407.17395v5 Announce Type: replace Abstract: Machine Learning research, including work promoting fair or equitable algorithms, often relies on the concept of a data-generating probability distr
arXiv:2504.19239v2 Announce Type: replace-cross Abstract: Quantum neural networks hold promise for tackling computationally challenging tasks that are intractable for classical computers. However, the
arXiv:2511.03690v2 Announce Type: replace-cross Abstract: Agents are now used widely in the process of software development, but building production-ready software engineering agents is a complex task
arXiv:2502.11478v3 Announce Type: replace-cross Abstract: In high-noise environments such as factories, subways, and busy streets, capturing clear speech is challenging. Throat microphones can offer a
Codex is OpenAI's AI model designed to understand and generate code, helping developers automate programming tasks and improve productivity. This guide from OpenAI likely outlines ten practical workpl
arXiv:2604.20231v1 Announce Type: new Abstract: Connected autonomous vehicles (CAVs), which represent a significant advancement in autonomous driving technology, have the potential to greatly increase
arXiv:2601.20144v3 Announce Type: replace Abstract: Tool-calling agents are increasingly deployed in real-world customer-facing workflows. Yet most studies on tool-calling agents focus on idealized se
arXiv:2604.19757v1 Announce Type: cross Abstract: This paper presents a transparent screening framework for estimating inference and training impacts of current large language models under limited obs
arXiv:2604.17172v2 Announce Type: replace-cross Abstract: The rapid growth of large language models (LLMs) has made GPU communication a critical bottleneck. While prior work reduces communication volu
arXiv:2604.20398v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel at function-level code generation, project-level tasks such as generating functional and visually aesthetic mul
arXiv:2604.20213v1 Announce Type: new Abstract: Accurate segmentation of maxillary sinus in panoramic X-ray images is essential for dental diagnosis and surgical planning; however, this task remains r
Codex is OpenAI's AI model specialized in understanding and generating code across multiple programming languages. Based on OpenAI's documentation, it likely explains Codex's capabilities for code com
arXiv:2507.08540v5 Announce Type: replace-cross Abstract: The proliferation of software vulnerabilities presents a significant challenge to cybersecurity, necessitating more effective detection method
Cognition AI's Chief Product Officer Walden Yan previously advised against building multi-agent systems, but the company has since changed its position based on evolving market conditions and technica
arXiv:2604.19465v1 Announce Type: cross Abstract: Understanding how complex systems respond to perturbations, such as whether they will remain stable or what their most sensitive patterns are, is a fu
arXiv:2602.04983v2 Announce Type: replace-cross Abstract: Purpose: To investigate whether an AI-based method can detect subtle inter-fraction changes in MR-Linac images acquired during radiotherapy an
arXiv:2511.07882v2 Announce Type: replace Abstract: Organisms in nature, such as Cephalopods and Pachyderms, exploit stiffness modulation to achieve amazing dexterity in the control of their appendage
This Databricks article examines whether Large Language Model agents can effectively optimize SQL join order, a critical query optimization problem in database systems. The analysis likely evaluates L
arXiv:2603.27889v2 Announce Type: replace Abstract: Framing theory posits that how information is presented shapes audience responses, but computational work has largely ignored audience reactions. Wh
ChargePoint has unveiled the ChargePoint Express Grid, powered by Eaton, a vehicle-to-everything capable solution that delivers up to 600 kW of power for passenger EVs and megawatt charging for heavy-
arXiv:2507.06321v2 Announce Type: replace Abstract: Collecting and annotating images for the purpose of training segmentation models is often cost prohibitive. In the domain of wildland fire science,
arXiv:2604.19741v1 Announce Type: new Abstract: We address the problem of generating a 3D-consistent, navigable environment that is spatially grounded: a simulation of a real location. Existing video
arXiv:2503.07259v2 Announce Type: replace-cross Abstract: The goal of creating intelligent, human-centered wearable systems for continuous activity understanding faces a fundamental trade-off: Egocent
CrowdStrike Holdings Inc. today expanded its Cloud Detection and Response service to Google Cloud Platform, adding runtime protection for Google workloads as attackers lean on artificial intelligence
arXiv:2501.10258v2 Announce Type: replace-cross Abstract: We present a novel universal gradient method for solving convex optimization problems. Our algorithm, Dual Averaging with Distance Adaptation
arXiv:2604.19658v1 Announce Type: new Abstract: Damage identification is a core task in structural health monitoring. In practice, however, its reliability is often compromised by confounding non-dama
arXiv:2603.04445v2 Announce Type: replace-cross Abstract: The rapid growth of large language models (LLMs) with diverse capabilities, costs, and domains has created a critical need for intelligent mod
arXiv:2510.09477v2 Announce Type: replace-cross Abstract: Set-based transformer models for amortized probabilistic inference and meta-learning, such as neural processes, prior-fitted networks, and tab
arXiv:2509.03726v2 Announce Type: replace-cross Abstract: Sampling from unnormalized target distributions, e.g. Boltzmann distributions mu_{ext{target}}(x) propto exp(-E(x)/T), is fundamental to many
arXiv:2602.11631v2 Announce Type: replace-cross Abstract: Accurate and efficient wavefield modeling underpins seismic structure and source studies. Traditional methods comply with physical laws but ar
arXiv:2411.16312v2 Announce Type: replace Abstract: Leveraging the overfitting property of deep neural networks (DNNs) is trending in video delivery systems to enhance video quality within bandwidth l
arXiv:2604.19054v1 Announce Type: new Abstract: The IEEE Low-Power Computer Vision Challenge (LPCVC) aims to promote the development of efficient vision models for edge devices, balancing accuracy wit
arXiv:2604.19357v1 Announce Type: new Abstract: The evaluation of machine learning models typically relies mainly on performance metrics based on loss functions, which risk to overlook changes in perf
arXiv:2604.19336v1 Announce Type: new Abstract: Online federated learning (OFL) has emerged as a popular framework for decentralized decision-making over continuous data streams without compromising c
arXiv:2604.03476v2 Announce Type: replace-cross Abstract: Optical Chemical Structure Recognition (OCSR) is critical for converting 2D molecular diagrams from printed literature into machine-readable f
arXiv:2604.19314v1 Announce Type: new Abstract: Recovering corrupted images is one of the most challenging problems in image processing. Among various restoration tasks, blind image deblurring has bee
arXiv:2604.18873v1 Announce Type: new Abstract: Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure,
arXiv:2508.06226v2 Announce Type: replace Abstract: Geometry problem solving (GPS) poses significant challenges for Multimodal Large Language Models (MLLMs) in diagram comprehension, knowledge applica
Speculative decoding is a technique that accelerates language model inference by using a smaller draft model to generate candidate tokens, which are then verified by a larger model, reducing latency w
arXiv:2410.16893v3 Announce Type: replace-cross Abstract: Bayesian optimization relies on iteratively constructing and optimizing an acquisition function. The latter turns out to be a challenging, non
arXiv:2604.19669v1 Announce Type: new Abstract: Enforcing constraint satisfaction in neural network outputs is critical for safety, reliability, and physical fidelity in many control and decision-maki
Anyscale Agent Skills is a framework built on Ray that enables developers to build AI agents more efficiently with improved debugging capabilities and workload optimization. The tool likely provides a
In the early days of generative AI, building safe and reliable business tools took massive engineering effort and a high tolerance for trial and error. We helped solve that with Vertex AI, our trusted
Traditional data catalogs were built as manual inventories for technical users, focusing on table structures rather than the deep context that AI agents need. When agents lack business semantics and d
LangChain is introducing new testing tools and capabilities that will help developers with test guidance, organization, and completion criteria—moving beyond just providing testing infrastructure to a
arXiv:2407.11107v3 Announce Type: replace-cross Abstract: Model predictive control (MPC) has played a more crucial role in various robotic control tasks, but its high computational requirements are co
OpenAI describes improvements and adaptations made to ChatGPT to better serve clinical and healthcare professionals. The work likely addresses how the model can be made more reliable, accurate, and us
arXiv:2602.01219v4 Announce Type: replace-cross Abstract: The attention operator in Transformers can be viewed as a two-layer fast-weight MLP, whose weights are dynamically instantiated from input tok