Knowledge catalogue
arXiv:2609.02315v1 Announce Type: cross Abstract: A single sentence often expresses multiple valid relational triplets, which makes Open Information Extraction (OpenIE) fundamentally a multi-output ta
arXiv:2609.02252v1 Announce Type: cross Abstract: In trajectory planning for autonomous driving, hybrid planning architectures are often realized as a collection of disparate modules, each with its ow
arXiv:2609.02288v1 Announce Type: new Abstract: Diffusion MRI requires repeated k-space acquisitions over multiple diffusion-encoding directions, making acquisition time dependent on both spatial and
arXiv:2609.02659v1 Announce Type: cross Abstract: The pairwise independent correlation gap is the ratio of the maximum expected value of a set function under arbitrary dependence to that under pairwis
arXiv:2609.02796v1 Announce Type: new Abstract: Sign language processing systems have traditionally operated at the sentence level, ignoring critical discourse phenomena fundamental to sign language c
arXiv:2609.02885v1 Announce Type: new Abstract: Recent web agents use world models for test-time action selection by sampling candidate actions, predicting the resulting web states, and ranking them w
arXiv:2609.02111v1 Announce Type: cross Abstract: Dermatology artificial intelligence (AI) models are predominantly trained on light-skinned, cancer-focused image collections, yet they are increasingl
arXiv:2609.01794v1 Announce Type: new Abstract: How do learners avoid overgeneralizations such as Tom laughed me without explicit negative evidence? Constructionists have posited two proposals that de
arXiv:2511.20251v2 Announce Type: replace Abstract: Modern text-to-image models produce impressive visual results from richly specified prompts, yet their behavior under long prompts remains insuffici
arXiv:2609.02685v1 Announce Type: cross Abstract: RAG has become the de facto method for incorporating new, corpus-specific knowledge into an instruction following LLM (Instruct LLM). Although RAG-bas
arXiv:2506.00290v2 Announce Type: replace Abstract: This paper introduces DLM-One, a score-distillation-based framework for one-step sequence generation with continuous diffusion language models (DLMs
arXiv:2609.02170v1 Announce Type: new Abstract: Advertising recommendation requires continuously tuning complex system parameters while balancing commercial returns and user experience. Recent work ha
arXiv:2609.02811v1 Announce Type: new Abstract: Predictive models are increasingly used in robotics for state estimation, planning, control, and policy evaluation, yet they are often judged by open-lo
arXiv:2609.02163v1 Announce Type: new Abstract: Information-theoretic measures derived from autoregressive language models are widely used to characterize the expectations that shape human reading, bu
arXiv:2606.17350v2 Announce Type: replace-cross Abstract: Recent advances in large language models (LLMs) have enabled the generation of high-quality prose, yet whether these models are capable of gen
arXiv:2609.02275v1 Announce Type: cross Abstract: Large language models are trained to model conditional distributions over text, yet it remains inadequately understood whether they capture the full d
arXiv:2609.02766v1 Announce Type: new Abstract: Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text, and tables are arguably the format in which most physical
arXiv:2609.02059v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved strong performance on structured visual understanding tasks such as chart and document question a
Document extraction just got a new gear. ⚡️ Introducing Turbo mode for Extract, our fastest way yet to pull structured data from documents. It runs roughly 4× faster than our Cost Effective Tier at co
arXiv:2609.01888v1 Announce Type: new Abstract: Recent inference-time hallucination mitigation methods for large vision-language models (LVLMs) report strong gains on hallucination benchmarks. However
arXiv:2609.02299v1 Announce Type: new Abstract: Object detectors often degrade under domain shifts such as changes in lighting, weather, or occlusion. These shifts alter object appearance and expose a
arXiv:2609.02707v1 Announce Type: new Abstract: Does the door-in-the-face technique work on language models? In humans, a large request that is refused makes a smaller follow-up request more likely to
arXiv:2609.02528v1 Announce Type: new Abstract: Measuring the mass of powder, including falling particles, is a common task in industrial applications. While scales are effective for static measuremen
arXiv:2501.18143v2 Announce Type: replace Abstract: Min cut is an important graph partitioning method. However, current solutions to the min cut problem suffer from slow speeds, difficulty in solving,
arXiv:2408.02932v3 Announce Type: replace-cross Abstract: Clustering is a fundamental task in machine learning and data science, and similarity graph-based clustering is an important approach within t
arXiv:2609.02075v1 Announce Type: new Abstract: Industrial anomaly detection benefits from anomaly samples, yet newly deployed products typically provide only normal images, making anomaly samples dif
arXiv:2609.02797v1 Announce Type: cross Abstract: People increasingly use language models to support life decisions. Many such decisions involve a probabilistic forecast: How likely is a major life ev
arXiv:2511.11659v3 Announce Type: replace Abstract: To address insufficient accuracy in multi-scale segmentation for agricultural habitat recognition, this study proposes a Dynamic Weighted Feature Fu
arXiv:2603.06662v3 Announce Type: replace Abstract: Continual VideoQA with multimodal LLMs remains challenging because sequential adaptation induces task interference, while storing task-specific prom
arXiv:2609.02068v1 Announce Type: new Abstract: Probabilistic multivariate time series (MTS) forecasting is crucial for modeling complex dynamical systems. However, existing diffusion-based methods re
arXiv:2609.02783v1 Announce Type: new Abstract: Evaluating LLM agents is essential for guiding their development, yet it has grown prohibitively expensive: a single pass of a frontier model over an ag
arXiv:2602.02028v3 Announce Type: replace Abstract: Enabling artificial intelligence systems, particularly large language models, to update knowledge and flexibly apply it during reasoning remains a c
arXiv:2609.02839v1 Announce Type: new Abstract: Adverse weather conditions such as rain, haze, and snow significantly degrade image quality, posing challenges for both human perception and physical AI
arXiv:2609.01647v1 Announce Type: new Abstract: The creation of telescope bibliographies is a crucial part of assessing the scientific impact of observatories and ensuring reproducibility in astronomy
arXiv:2609.02309v1 Announce Type: new Abstract: GUI agents increasingly operate across websites, mobile apps, and desktop environments, yet the field still reports progress primarily through task succ
arXiv:2609.01792v1 Announce Type: cross Abstract: Passive acoustic monitoring of killer whales is particularly important for conservation of the endangered Southern Resident killer whale population, b
arXiv:2609.02677v1 Announce Type: cross Abstract: Modern portfolio management increasingly demands a balance between traditional risk-adjusted returns and strict Environmental, Social, and Governance
arXiv:2503.22411v2 Announce Type: replace Abstract: Is political incivility rising across democracies - and if so, why? Analysing approximately 13.8 million tweets from parliamentarians in 26 countrie
Learn how to embed individual Amazon Quick Sight visuals into a React application with per-user access control. This walkthrough uses Amazon Cognito authentication and a serverless AWS Lambda backend
arXiv:2609.01768v1 Announce Type: new Abstract: Artificial neural networks are often regarded as powerful yet opaque black boxes. Here, we demonstrate that learning in deep neural networks generates l
arXiv:2609.02133v1 Announce Type: new Abstract: Empathetic response generation requires models to decide not only what to say, but also how to respond to the previous speaker's affective situation. We
arXiv:2606.13081v2 Announce Type: replace-cross Abstract: Emotion significantly influences cognition, enhancing memory and learning under certain conditions. Drawing on this principle, emotion-augment
arXiv:2412.01865v5 Announce Type: replace-cross Abstract: BrainAGE is a promising imaging-derived biomarker of neurobiological ageing and disease risk, yet current approaches rely predominantly on T1-
arXiv:2511.12018v2 Announce Type: replace Abstract: Traffic safety analysis at signalized intersections is essential for reducing vehicle and pedestrian collisions, yet traditional crash-based studies
arXiv:2609.02285v1 Announce Type: cross Abstract: A long-held intuition in interpretability research is that representational entanglement, the sharing of structure between knowledge domains in a neur
arXiv:2609.01873v1 Announce Type: new Abstract: Multi-agent AI systems improve inference by spawning agents and synthesizing reports. But another agent is not another observation: apparently independe
CNBC: Equinix, whose stock is up 33% YTD, pushing its market cap to $100B, inks a deal with Nvidia to let customers run their AI models on the Together AI platform — Long before the era of the hypersc
arXiv:2603.24130v2 Announce Type: replace Abstract: This paper presents an equivariant filter (EqF) transformation approach for visual--inertial navigation. By establishing analytical links between Eq
arXiv:2609.01611v1 Announce Type: new Abstract: Frontier large language models can often recognize when they are being evaluated, a capability known as evaluation awareness. If models behave different
arXiv:2510.07277v2 Announce Type: replace Abstract: Diabetic Macular Edema (DME) is a leading cause of vision loss among patients with Diabetic Retinopathy (DR). While deep learning has shown promisin
arXiv:2503.17039v3 Announce Type: replace-cross Abstract: Automatic text summarization relies on automatic evaluation to quickly determine the quality of summarization models via automatic metrics and
arXiv:2609.02404v1 Announce Type: cross Abstract: Sparse mixture-of-experts (MoE) models use an independently parameterized router at each sparse layer to select experts for every token. Prior work ha
arXiv:2609.02097v1 Announce Type: new Abstract: The rapid progress of AIGC has made text-centric image manipulation increasingly accessible, creating new forensic challenges that require not only auth
arXiv:2609.01742v1 Announce Type: new Abstract: Anti-UAV systems increasingly fuse multiple sensors, yet their detection heads provide no per-modality reliability signal. This study evaluates whether
arXiv:2609.02155v1 Announce Type: new Abstract: The Johnson-Lindenstrauss (JL) lemma guarantees that a random projection of n points to m=O(arepsilon^{-2}log n) dimensions preserves pairwise squared d
arXiv:2609.02191v1 Announce Type: new Abstract: Human interventions at fault points can alter the diagnostic accuracy of multi-agent medical systems. We defined fault points as moments in AI agent con
arXiv:2511.04147v2 Announce Type: replace Abstract: Safe reinforcement learning (RL) aims to optimize long-term performance while adhering to safety requirements. However, many practical applications
Exciting day for NVIDIA and @huggingface. Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty. They allow every developer, startup, university,
arXiv:2609.01865v1 Announce Type: cross Abstract: Embedding-based code retrieval is a core component of coding agents and retrieval-augmented code generation, where retrieving correct code matters mor
arXiv:2509.06272v5 Announce Type: replace-cross Abstract: Swarm-based optimization algorithms have demonstrated remarkable success in solving complex problems, yet their widespread adoption remains li