Knowledge catalogue
arXiv:2606.14202v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have advanced Automatic Heuristic Design (AHD) by enabling heuristic generation through reasoning and code synthe
arXiv:2606.29914v1 Announce Type: new Abstract: Agent memory systems are increasingly evaluated against RAG and full-context baselines, but reported gains often mix changes in the memory method with c
arXiv:2606.29788v1 Announce Type: new Abstract: When a multimodal AI agent is asked to forget a fact, current memory systems usually delete the text entry and report success. We find that the fact can
arXiv:2606.29030v1 Announce Type: new Abstract: AI agents extend conventional large language model (LLM) applications by integrating language understanding with task execution, external tool use, and
arXiv:2606.28377v1 Announce Type: cross Abstract: HAR using Inertial Measurement Unit (IMU) sensors is vital for healthcare monitoring and rehabilitation. Despite deep learning advancements, major cha
arXiv:2606.28876v1 Announce Type: new Abstract: Long-context language models often conflate two different goals: compressing history into an efficient state, and maintaining reliable long-term memory.
arXiv:2606.30602v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate complex, distributed workflows. However, their inter-agent communication channels introduc
arXiv:2606.28622v1 Announce Type: new Abstract: Differentiable rendering has emerged as a powerful approach for 3D reconstruction and novel view synthesis. State-of-the-art differentiable rendering me
arXiv:2606.28399v1 Announce Type: new Abstract: The structure of human visual representations underpins our capacity for adaptive behaviour. While pretrained neural networks model human visual represe
arXiv:2606.28363v1 Announce Type: cross Abstract: Objective: To describe the architecture and design rationale of meta-pipe, an open-source large language model (LLM)-agent pipeline that integrates th
arXiv:2606.29038v1 Announce Type: cross Abstract: Metric aggregation divergence (MAD) is the silent inconsistency that arises when distinct pipeline stages in an agent-based model coupled with a multi
arXiv:2606.29697v1 Announce Type: new Abstract: For uncrewed aerial vehicles (UAVs), estimating six-degree-of-freedom (6-DoF) poses is essential for airspace situational awareness, target tracking, an
arXiv:2506.12697v3 Announce Type: replace-cross Abstract: Small-object detection in Unmanned Aerial Vehicle (UAV) imagery requires preserving weak local evidence while using broader context to separat
arXiv:2606.29462v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) inherit rich relational priors from their language backbones, yet often fail when asked to apply these relation
arXiv:2606.30182v1 Announce Type: new Abstract: AI models are rapidly improving at autonomous coding, as shown by benchmark progress and one-off demonstrations such as AI implementing a C compiler. Ho
arXiv:2606.29308v1 Announce Type: new Abstract: While text-guided image editing has made remarkable progress, it remains limited in structural portrait retouching. Textual descriptions struggle to con
arXiv:2606.29265v1 Announce Type: new Abstract: Reasoning large language models (LLMs) have recently made much progress in complex problem-solving, leveraging internal reasoning (or thought) to guide
arXiv:2606.29447v1 Announce Type: new Abstract: Over the past decade, interest in applying machine learning (ML) to automate forest monitoring has grown significantly. However, existing training datas
arXiv:2606.28697v1 Announce Type: cross Abstract: Pathology foundation models (PFMs) have demonstrated strong potential across clinical and scientific applications, yet their performance is often hind
arXiv:2602.13562v2 Announce Type: replace-cross Abstract: While reasoning models have achieved remarkable success in complex reasoning tasks, their increasing power necessitates stringent safety measu
arXiv:2602.21608v2 Announce Type: replace Abstract: Bangla-English code-mixing is widespread across South Asian social media, yet resources for implicit meaning identification in this setting remain s
arXiv:2606.29425v1 Announce Type: new Abstract: Existing multi-agent debate frameworks suffer from two critical limitations: they rely on static architectures where agent roles and coordination patter
arXiv:2606.28917v1 Announce Type: new Abstract: Lightweight Directory Access Protocol (LDAP) is a protocol that allows users to query and modify Active Directory (AD) data. By default, all users have
arXiv:2510.03142v2 Announce Type: replace-cross Abstract: Visual navigation policy is widely regarded as a promising direction, as it mimics humans by using egocentric visual observations for navigati
arXiv:2606.30575v1 Announce Type: new Abstract: The problem of autonomous navigation for UAV inspection remains challenging as it requires effectively navigating in close proximity to obstacles, while
arXiv:2507.23220v2 Announce Type: replace Abstract: Traditional topic models are effective at uncovering latent themes in large text collections. However, due to their reliance on bag-of-words represe
arXiv:2606.28373v1 Announce Type: cross Abstract: Model merging integrates the capabilities of multiple expert models to create strong models for multiple tasks without additional training, thereby re
arXiv:2606.30397v1 Announce Type: cross Abstract: The increasing integration of Electric Vehicles (EVs) has imposed a growing harmonic challenge on the power grid. For AC/DC Power Factor Correction (P
arXiv:2506.12078v2 Announce Type: replace-cross Abstract: Understanding the dynamic evolution of complex social phenomena requires both high-fidelity modeling of human behavior and large-scale simulat
arXiv:2606.28470v1 Announce Type: new Abstract: We demonstrate how emotional valence influences the order-dependent structure of children's recognition memory: correct recall of a sequence of emotiona
arXiv:2402.06359v2 Announce Type: replace Abstract: One of today's most pressing societal challenges is building AI systems whose behaviour, or the behaviour it enables within communities of interacti
arXiv:2606.28955v1 Announce Type: cross Abstract: Reinforcement learning agents can exploit misspecified reward signals to achieve high apparent returns while failing on the intended objective, a fail
arXiv:2602.20360v2 Announce Type: replace-cross Abstract: Flow-based generative methods offer a simple and effective framework for high-fidelity generation, yet pretrained flow models are rarely used
arXiv:2511.19119v2 Announce Type: replace Abstract: Spatial reasoning (SR), the ability to infer 3D spatial information from 2D inputs, is essential for real-world applications such as embodied AI and
arXiv:2606.30017v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting have demonstrated unprecedented success in novel view synthesis. However, the substantial inference and storage
arXiv:2512.16733v3 Announce Type: replace Abstract: Black-box AI (BBAI) systems, including foundation-model agents, are increasingly used for sequential decision making. Safe deployment requires metho
arXiv:2606.30406v1 Announce Type: new Abstract: Modern large language models (LLMs) rely on reinforcement learning during post-training to push specific capabilities, yet integrating multiple capabili
arXiv:2606.29237v1 Announce Type: cross Abstract: Robust robot autonomy depends on scene representations that remain stable enough to support localization, navigation, and downstream decision making i
arXiv:2606.30562v1 Announce Type: new Abstract: Hybrid attention models improve long-context efficiency by retaining only a subset of full-attention layers and replacing the remaining layers with line
arXiv:2606.29049v1 Announce Type: new Abstract: Knowledge Tracing (KT) is important for personalized education but traditionally suffers from two key limitations: a reliance on shallow ID-based repres
arXiv:2606.29531v1 Announce Type: cross Abstract: We propose MotionAtlas, a system for detailed captioning of motion-centric videos, comprising (1) a dedicated human-annotated benchmark, (2) a scalabl
arXiv:2606.29760v1 Announce Type: new Abstract: Blind image quality assessment (BIQA) is commonly built on two basic learning paradigms: regression and ranking. Regression calibrates absolute scores,
arXiv:2504.05184v4 Announce Type: replace-cross Abstract: Accurate segmentation of coronary Digital Subtraction Angiography (DSA) images is essential for diagnosing and treating coronary artery diseas
arXiv:2606.29469v1 Announce Type: new Abstract: While robust map maintenance has advanced significantly, existing studies have focused on specific tasks, especially dynamic object removal or change de
arXiv:2606.30528v1 Announce Type: new Abstract: Current generative models, including GANs and diffusion models, have reached an outstanding level of photorealism, posing significant risks to privacy a
arXiv:2606.28339v1 Announce Type: cross Abstract: Industrial 6G networks require ultra-reliable, low-latency, and energy-efficient connectivity in dynamic and blockage-prone environments, where conven
arXiv:2602.07913v2 Announce Type: replace Abstract: Multi-Agent Route Planning considers selecting vehicles, each associated with a single predefined route, such that route-level coverage utility is m
arXiv:2606.28925v1 Announce Type: cross Abstract: Tool and agent routing from natural-language prompts is naturally a set-valued prediction problem: a single query may require multiple agents, while o
arXiv:2606.30259v1 Announce Type: new Abstract: In contemporary societies, the threat of disinformation has reached alarming levels, exacerbated by the proliferation of electronic communication, socia
arXiv:2606.29215v1 Announce Type: cross Abstract: Block Diffusion Language Models (BD-LMs) improve diffusion-based text generation with KV caching and flexible-length generation. A natural next step i
arXiv:2508.02425v2 Announce Type: replace-cross Abstract: In physical human-robot collaboration (pHRC) settings, humans and robots collaborate directly in shared environments. Robots must analyze inte
arXiv:2606.29165v1 Announce Type: new Abstract: Continuum robots offer key advantages in navigating unstructured environments, but their safe operation requires accurate estimation of the external con
arXiv:2606.29797v1 Announce Type: cross Abstract: Machine learning network intrusion detection systems (IDS) rely on aggregate flow statistics that discard distributional structure, while established
arXiv:2606.29334v1 Announce Type: new Abstract: Gaze target estimation aims to predict the semantic object an observer fixates upon within an image, a task deeply rooted in the object-oriented nature
arXiv:2606.29755v1 Announce Type: new Abstract: Aiming at the problem that obstacle avoidance flexibility and formation integrity are difficult to coexist in multi-UAV formation motion in complex obst
arXiv:2606.28369v1 Announce Type: cross Abstract: Semantic search and recommendation of similar documents, such as news and reports about unusual environmental events (e.g., a dead whale washed ashore
arXiv:2606.28780v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are widely applied to visual document understanding. However, comprehending long documents remains an issue b
arXiv:2403.06728v2 Announce Type: replace Abstract: Radiology report generation (RRG) has attracted significant attention due to its potential to reduce the workload of radiologists. The performance o
arXiv:2507.02804v2 Announce Type: replace Abstract: Recent progress in large-scale reinforcement learning (RL) has notably enhanced the reasoning capabilities of large language models (LLMs), especial
arXiv:2506.08774v2 Announce Type: replace-cross Abstract: Different machine learning models can represent the same underlying concept in different ways. This variability is particularly valuable for i