Knowledge catalogue
arXiv:2609.28372v1 Announce Type: cross Abstract: Consumers increasingly delegate purchasing decisions to Large Language Models (LLMs) acting as surrogate consumers. Using 'Tool-Lab,' an adaptation of
arXiv:2609.26820v1 Announce Type: cross Abstract: Physiological time series such as electrocardiograms (ECG) and electroencephalograms (EEG) exhibit complex temporal structure, substantial acquisition
arXiv:2409.13568v3 Announce Type: replace Abstract: Accurate delineation of agricultural field boundaries is essential for effective crop monitoring and resource management. However, competing methodo
arXiv:2609.27155v1 Announce Type: cross Abstract: With recent advancements in large language models (LLMs) and LLM-based agents, these agents are becoming increasingly autonomous and gaining broader a
arXiv:2604.06039v2 Announce Type: replace-cross Abstract: Value iteration-type methods have been extensively studied for computing a nearly optimal value function in reinforcement learning (RL). Under
arXiv:2601.22524v2 Announce Type: replace Abstract: Graph generation aims to sample discrete node and edge attributes while satisfying coupled structural constraints. Diffusion models for graphs often
arXiv:2609.28184v1 Announce Type: cross Abstract: Robotic operation in previously unseen environments requires both semantic understanding and reliable metric information. While vision--language model
arXiv:2609.26976v1 Announce Type: new Abstract: Learned context planning selects evidence atoms before an answer model reasons over them. We test whether this learned selection improves long-context m
arXiv:2609.27033v1 Announce Type: cross Abstract: Reward fine-tuning aims to update a pre-trained flow-based generative model to improve the downstream reward of its generated samples. Existing method
arXiv:2609.26244v1 Announce Type: cross Abstract: Accurately forecasting river runoff is key to managing water resources, controlling floods, and planning agriculture. This study examines the Ajichay
arXiv:2609.26274v1 Announce Type: new Abstract: The rapid evolution of generative AI (e.g., Sora, Hunyuan) makes it essential to develop effective detection strategies that can generalize across ever-
arXiv:2609.25833v1 Announce Type: new Abstract: Automatic fact-checking poses a significant challenge in Arabic natural language processing due to the scarcity of datasets and resources. In this manus
arXiv:2609.25891v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) often struggle with fine-grained visual perception when processing complete images, as critical evidence may on
arXiv:2609.25947v1 Announce Type: cross Abstract: Quantum circuit optimization replaces a circuit with an equivalent one of fewer gates and lower depth, reducing execution cost and error rate. We ask
arXiv:2609.25937v1 Announce Type: new Abstract: Frozen visual foundation models provide transferable features for visual place recognition, but fixed aggregation can suppress useful distinctions in ne
arXiv:2609.26300v1 Announce Type: new Abstract: Despite their strong performance, large language models (LLMs) are bottlenecked by KV cache memory traffic during long-context inference. Sparse attenti
arXiv:2609.24801v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in production systems, raising concerns about their exposure to adversarial manipulation throug
arXiv:2601.08450v2 Announce Type: replace-cross Abstract: Autoregressive speech synthesis often adopts a left-to-right order, yet generation order is a modelling choice. We investigate decoding order
arXiv:2609.25777v1 Announce Type: new Abstract: Accurate multi-step traffic forecasting remains challenging because observed traffic signals contain heterogeneous temporal dynamics with different char
arXiv:2505.13994v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy tra
arXiv:2601.06362v3 Announce Type: replace Abstract: Personalized large language models are often expected to follow explicit style instructions, yet we find that such instructions can undermine the us
arXiv:2609.26077v1 Announce Type: new Abstract: A Strassen-type algorithm has many realizations with the same exact product and multiplication count yet different fp8 error because basis changes resha
arXiv:2609.26756v2 Announce Type: new Abstract: X-ray is medicine's most widely used imaging modality, yet remains among its least quantitative. Unlike volumetric modalities like CT or MRI, X-ray coll
HEMA, a 100-year-old Dutch retailer, turned developer portal-hopping into instant answers by building HAL, an internal AI assistant on Amazon Bedrock AgentCore. Using Model Context Protocol (MCP), HAL
Full transcript: Minister Barrot, members of the Security Council, thank you for the invitation. As a French national who moved to the US 15 years ago, with a Brazilian wife and two American daughters
arXiv:2609.22691v1 Announce Type: new Abstract: An enduring and richly elaborated dichotomy in cognitive neuroscience is that of human behavior control mechanisms, divided into habitual versus goal-di
arXiv:2609.26620v1 Announce Type: new Abstract: Photographic composition aims to provide visual guidance for improving the framing, viewpoint, and spatial arrangement of an image. Early methods primar
In the quest to deploy artificial intelligence at scale, enterprises are discovering a basic truth: Model capability is no longer the only issue, but data access and control can determine success or f
arXiv:2609.25130v1 Announce Type: new Abstract: Memory systems for coding agents must decide, when a repository changes, which of their stored claims have become false. Content anchoring invalidates a
arXiv:2609.26672v1 Announce Type: new Abstract: Training vision-language-action (VLA) models for high-precision manipulation typically requires task-specific, high-quality data (e.g., teleoperation),
arXiv:2609.24090v1 Announce Type: new Abstract: Long-horizon autonomous intelligent systems rely on heterogeneous components such as large language models, databases, external APIs, and rule engines,
Interesting paper on agent memory stored as a linked markdown wiki. Lots of great ideas and insights if you work with LLM Wikis. Wikis are useful for agents because each page holds dense text and the
arXiv:2609.26384v1 Announce Type: new Abstract: Medical image interpretation is high-volume and time-consuming, and while AI interpretation can reduce workload, fully autonomous deployment carries pot
arXiv:2606.14157v2 Announce Type: replace Abstract: Cities deliver basic services through mixed public-private facility networks, including schools, clinics, transit providers, and subsidized service
arXiv:2601.08358v2 Announce Type: replace Abstract: Even though the ocean covers the majority of the planet's surface, it remains the least explored ecosystem. As light and radio waves do not propagat
arXiv:2609.25756v1 Announce Type: new Abstract: Precision medical robotics demands adaptive decision-making under strict safety, interpretability, and execution constraints. Although recent Vision-Lan
arXiv:2609.25049v1 Announce Type: new Abstract: Large language models (LLMs) aligned for safety often suffer from over-refusal, incorrectly rejecting benign yet safety-related instructions. Prior stud
arXiv:2609.26617v1 Announce Type: cross Abstract: Clinical decision making heavily relies on predicting the disease progression trajectory by seeking to understand patient's health status which is cha
arXiv:2609.25334v1 Announce Type: new Abstract: Intrinsically disordered proteins (IDPs) differ from folded proteins in that they are dynamic, lack a stable three-dimensional conformation, and have lo
arXiv:2410.14948v2 Announce Type: replace Abstract: Medical multimodal large language models (MLLMs) can perform well on existing medical visual question answering (MedVQA) benchmarks, but their train
arXiv:2609.25597v1 Announce Type: new Abstract: The annotation used to select a segmentation threshold is part of the evaluation protocol, yet its effect is easily conflated with model quality. We exa
arXiv:2603.17043v2 Announce Type: replace Abstract: Physics-aware multimodal large language models (MLLMs) can localize and characterize two-dimensional (2D) material flakes from optical microscopy im
arXiv:2609.26355v1 Announce Type: new Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mat
arXiv:2608.24268v2 Announce Type: replace Abstract: This paper proposes methods to extract over 50 types of events from a Dutch historical corpus spanning the 17th and 18th centuries. The methods we p
arXiv:2609.26467v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide broad manipulation competence, but often struggle during the precision-critical stages that dominate contact
Hey everyone, I made a simple script called MOMOS to run Ollama and small LLMs directly on your Android phone using Termux. It automatically handles PRoot-Distro (Debian), installs Ollama, and lets yo
arXiv:2609.24130v1 Announce Type: new Abstract: LLM agents can change their own future behavior, raising a basic control question of which self-generated changes should be allowed to persist. We formu
arXiv:2609.26184v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into robotic control systems is enabling a new generation of autonomous agents capable of complex reason
arXiv:2609.26774v1 Announce Type: new Abstract: Vector Quantization (VQ) is fundamental to discrete visual tokenizers that power modern autoregressive and masked image generation models. While recent
arXiv:2603.01765v5 Announce Type: replace Abstract: Monocular depth foundation models generalize across diverse scenes, but recovering accurate metric depth consistent with a target sensor remains cha
arXiv:2609.26099v1 Announce Type: new Abstract: Anomalous video understanding aims to identify abnormal events in videos and interpret their semantic meanings beyond simple anomaly detection. Recent v
The next phase of artificial intelligence infrastructure will not be defined by a single graphics processing unit, chip architecture or model. Compute, memory, networking, packaging, power and softwar
arXiv:2609.25144v1 Announce Type: cross Abstract: Lepto-regression is defined as the machine learning process of constructing a Regression Tree of a target feature on itself. It is a novel, model-free
arXiv:2409.02244v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly being used as ad hoc therapists. While prior research has found that LLMs outperform human couns
arXiv:2609.26061v1 Announce Type: cross Abstract: Mixture-of-experts (MoE) models improve capacity with moderate overhead by sparsely activating experts per token. However, deploying MoE across resour
arXiv:2603.11323v2 Announce Type: replace Abstract: The simplicity and effectiveness of UNet architectures make them ubiquitous in image restoration, segmentation, and diffusion models. They are often
arXiv:2609.25498v1 Announce Type: cross Abstract: Deploying Large Language Models for runtime operational triage incurs prohibitive latency (>100-500 ms), high VRAM requirements (>4-8 GB), and excessi
arXiv:2609.25785v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as general-purpose robotic manipulation policies. However, in dexterous hand manipulation, contact forc
arXiv:2609.26117v1 Announce Type: new Abstract: Human-centric audio-visual generation spans several closely related tasks: animating a person from driving speech, jointly generating speech and video f
arXiv:2609.25638v1 Announce Type: new Abstract: Foundation vision models provide strong generic representations, yet high class-level retrieval accuracy does not necessarily imply that an embedding re