Knowledge catalogue
arXiv:2604.23190v1 Announce Type: cross Abstract: Automating repository-level software engineering tasks is a foundational challenge for autonomous code agents, largely due to the difficulty of config
arXiv:2604.23696v1 Announce Type: new Abstract: Haptic feedback has been a long-missed feature in robotic-assisted surgery, one that would allow surgeons to perceive tissue properties and apply contro
arXiv:2603.18563v2 Announce Type: replace Abstract: As autonomous AI agents increasingly mediate online platform markets, a fundamental question emerges: do these markets generate stable strategic out
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:2604.23653v1 Announce Type: cross Abstract: Reliable agricultural data is essential for food security, land-use planning, and economic resilience, yet in Palestine, such data remains difficult t
arXiv:2604.07533v2 Announce Type: replace-cross Abstract: Time Slotted Channel Hopping (TSCH) is a widely adopted Media Access Control (MAC) protocol within the IEEE 802.15.4e standard, designed to pr
arXiv:2604.23296v1 Announce Type: cross Abstract: Aspect Sentiment Quad Prediction (ASQP) has seen significant advancements, largely driven by the powerful semantic understanding and generative capabi
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:2510.24832v2 Announce Type: replace Abstract: Using Reinforcement Learning with Verifiable Rewards (RLVR) to optimize Large Language Models (LLMs) can be conceptualized as progressively editing
arXiv:2604.24339v1 Announce Type: cross Abstract: Recent advances in Vision-Language Models (VLMs) have benefited from Reinforcement Learning (RL) for enhanced reasoning. However, existing methods sti
arXiv:2604.24109v1 Announce Type: new Abstract: Semi-supervised learning (SSL) has become a promising solution to alleviate the annotation burden of deep learning-based medical image segmentation mode
arXiv:2604.24720v1 Announce Type: new Abstract: Indonesian marketplace reviews mix standard vocabulary with slang, regional loanwords, numeric shorthands, and emoji, making lexicon-based sentiment too
arXiv:2604.23747v1 Announce Type: cross Abstract: Recent mixed-policy optimization methods for LLM reasoning that interleave or blend supervised and reinforcement learning signals report improvements
arXiv:2512.20562v2 Announce Type: replace-cross Abstract: We study the problem of learning a low-degree spherical polynomial of degree ell_0 = Theta(1) ge 1 defined on the unit sphere in RR^d by train
arXiv:2506.18493v2 Announce Type: replace Abstract: Customizing image generation remains a core challenge in controllable image synthesis. For single-concept generation, maintaining both identity pres
arXiv:2604.24594v1 Announce Type: cross Abstract: As large language models (LLMs) evolve into agentic problem solvers, they increasingly rely on external, reusable skills to handle tasks beyond their
// Skill Retrieval Augmentation for Agentic AI // Great read for AI devs. (bookmark it) It's on finding efficient ways to incorporate skills for agents. The work introduces Skill Retrieval Augmentatio
arXiv:2604.24449v1 Announce Type: cross Abstract: Training machine learning models for robotic tactile sensing requires vast amounts of data, yet obtaining realistic interaction data remains a challen
arXiv:2604.23309v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) aims to describe the difference between two remote sensing images. While recent methods have explored vid
arXiv:2604.22782v1 Announce Type: cross Abstract: Serving transformer language models with high throughput requires caching Key-Values (KVs) to avoid redundant computation during autoregressive genera
arXiv:2507.09245v2 Announce Type: replace Abstract: The Swa-bhasha Resource Hub provides a comprehensive collection of data resources and algorithms developed for Romanized Sinhala to Sinhala translit
arXiv:2601.16746v3 Announce Type: replace-cross Abstract: LLM agents have demonstrated remarkable capabilities in software development, but their performance is hampered by long interaction contexts,
arXiv:2509.14635v2 Announce Type: replace Abstract: Understanding and reasoning about entire software repositories is an essential capability for intelligent software engineering tools. While existing
arXiv:2603.26380v2 Announce Type: replace Abstract: The attention mechanism has been the core component in modern transformer architectures. However, the computation of standard full attention scales
arXiv:2604.23623v1 Announce Type: new Abstract: Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit st
arXiv:2601.04204v2 Announce Type: replace-cross Abstract: The scalability of high-quality online education is hindered by the high costs and slow cycles of manual content creation. Despite advancement
arXiv:2602.11318v3 Announce Type: replace Abstract: In machine learning, 'ground truth' refers to the assumed correct labels used to train and evaluate models. However, the foundational 'ground truth'
arXiv:2604.22767v1 Announce Type: cross Abstract: Ethical discourse on AI in healthcare has focused predominantly on back-end concerns such as bias, fairness and explainability, while the front-end in
arXiv:2601.15485v2 Announce Type: replace-cross Abstract: Federal research funding shapes the direction, diversity, and impact of the US scientific enterprise. Large language models (LLMs) are rapidly
arXiv:2503.09101v4 Announce Type: replace-cross Abstract: Uniform manifold approximation and projection (UMAP) is among the most popular neighbor embedding methods. The method samples pairs of point i
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: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:2603.11831v2 Announce Type: replace Abstract: The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate
arXiv:2505.15957v4 Announce Type: replace-cross Abstract: With advancements in large audio-language models (LALMs), which enhance large language models (LLMs) with auditory capabilities, these models
arXiv:2604.23245v1 Announce Type: cross Abstract: The use of Machine Learning (ML) for data-driven decision-making often relies on access to sensitive datasets, which introduces privacy challenges. Tr
arXiv:2507.04503v2 Announce Type: replace Abstract: Accurate localization using visual information is a critical yet challenging task, especially in urban environments where nearby buildings and const
arXiv:2604.22789v1 Announce Type: cross Abstract: Organizations deploying AI-enabled Intelligent Transportation Systems face fragmented governance: ISO/IEC 42001 demands a certifiable management syste
arXiv:2604.23505v1 Announce Type: cross Abstract: Uncertainty in large language model (LLM)-based systems is often studied at the level of a single model output, yet deployed LLM applications are comp
arXiv:2312.08410v5 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel
arXiv:2502.03669v3 Announce Type: replace-cross Abstract: AI methods, such as generative models and reinforcement learning, have recently been applied to combinatorial optimization (CO) problems, espe
arXiv:2604.22893v1 Announce Type: cross Abstract: Traditional data valuation methods based on ``row-count imes quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that
arXiv:2604.23953v1 Announce Type: cross Abstract: Blind omnidirectional image quality assessment (BOIQA) presents a great challenge to the visual quality assessment community, due to different storage
arXiv:2604.22872v1 Announce Type: new Abstract: Autonomous vehicles (AVs) rely on real-time perception systems to understand road environments and ensure safe navigation. However, implementing reliabl
arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s
When an LLM acts happy (“EUREKA!”) or sad (“I have failed…”), is that meaningless mimicry, or does it reflect something “real”? We don’t know if LLMs are conscious. But they increasingly seem to exhib
arXiv:2604.22774v1 Announce Type: cross Abstract: Accurate transcription of handwritten mathematics is crucial for educational AI systems, yet current benchmarks fail to evaluate this capability prope
arXiv:2604.23256v1 Announce Type: cross Abstract: Symbolic regression discovers mathematical formulas from data. Some methods fix a tree of operators, assign learnable weights, and train by gradient d
arXiv:2501.13400v3 Announce Type: replace-cross Abstract: In the field of deep learning-based computer vision, YOLO is revolutionary. With respect to deep learning models, YOLO is also the one that is
arXiv:2604.23536v1 Announce Type: new Abstract: Diffusion models have achieved unprecedented success in text-aligned generation, largely driven by Classifier-Free Guidance (CFG). However, standard CFG
arXiv:2604.24470v1 Announce Type: new Abstract: Unsupervised automatic readability assessment (ARA) methods have important practical and research applications (e.g., ensuring medical or educational ma
arXiv:2604.22657v1 Announce Type: new Abstract: Accurate identification of individual farm animals in group-housed environments is a cornerstone of precision livestock management. However, current ind
arXiv:2604.22256v1 Announce Type: cross Abstract: Goal recognition aims to infer an agent's goal from observations of its behaviour. In realistic settings, recognition can benefit from exploiting hier
arXiv:2604.22569v1 Announce Type: cross Abstract: Machine learning-based malware detectors are increasingly vulnerable to adversarial examples. Traditional defenses, such as one-shot adversarial train
arXiv:2604.22639v1 Announce Type: cross Abstract: Malware development and detection have undergone significant changes in recent years as modern concepts, such as machine learning, have been used for
arXiv:2510.21236v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have evolved into AI agents that interact with external tools and environments to perform complex tasks. The Mode
arXiv:2510.16853v3 Announce Type: replace-cross Abstract: Autonomous AI agents capable of complex planning and action mark a shift beyond today's generative tools. As these systems enter political and
arXiv:2604.22517v1 Announce Type: new Abstract: Evaluating LLM-generated business ideas is often harder to scale than generating them. Unlike standard NLP benchmarks, business idea evaluation relies o
arXiv:2505.01380v2 Announce Type: replace Abstract: Robot swarms navigating through unknown obstacle environments are an emerging research area that faces challenges. Performing tasks in such environm
arXiv:2604.22199v1 Announce Type: cross Abstract: Autonomous robots operating in open environments need the ability to continuously handle tasks that are not covered by predefined local methods. Howev
arXiv:2604.22202v1 Announce Type: new Abstract: Symmetry detection is a fundamental problem in computer vision, and symmetries serve as powerful priors for downstream tasks. However, existing learning