Knowledge catalogue
GLM-5.2 achieved token generation speeds of 318 tokens per second, surpassing the previously reported 280 tokens per second benchmark, with indications that further performance improvements are possib
arXiv:2606.24168v1 Announce Type: cross Abstract: Automated diabetic retinopathy (DR) grading from colour fundus photographs can achieve strong predictive performance, but clinical interpretation requ
arXiv:2606.24834v1 Announce Type: new Abstract: LLM-based dialogue assistants have become mainstream tools for software developers, yet current evaluation benchmarks focus exclusively on functional co
arXiv:2606.24784v1 Announce Type: new Abstract: High-resolution aerial imagery has recently emerged as a complementary modality for automated driving perception and has shown potential to improve bird
arXiv:2606.24649v1 Announce Type: new Abstract: Recent advancements have explored agentic zero-shot 3D understanding by reformulating it as video keyframe understanding with Multimodal Large Language
arXiv:2606.24143v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts guided by teacher feedback and is becoming increasingly important for large language m
arXiv:2606.24392v1 Announce Type: new Abstract: Existing ECG report generation is tightly coupled -- interpretation and reporting fused end-to-end, so errors propagate without stage-level recourse --
arXiv:2512.15503v3 Announce Type: replace-cross Abstract: Vehicular platooning promises transformative improvements in transportation efficiency and safety through the coordination of multi-vehicle fo
arXiv:2606.23712v1 Announce Type: cross Abstract: Audio-visual speech enhancement (AVSE) exploits visual cues such as lip movements to recover speech in noisy environments. Recent work introduced diff
arXiv:2606.24055v1 Announce Type: new Abstract: Sentiment analysis in Twitter datasets is important because it enables monitoring public opinion on products and analysis of political and social moveme
arXiv:2606.24042v1 Announce Type: new Abstract: Recommender systems often induce filter bubbles and semantic homogenization by monolithically optimizing for immediate user engagement. Standard single-
arXiv:2606.24844v1 Announce Type: new Abstract: One-step diffusion editors are fast because they avoid inversion and iterative optimization, but a single transport update must be aggressive enough to
arXiv:2606.23939v1 Announce Type: cross Abstract: Variable projection is a classical technique for separable nonlinear least-squares problems, in which variables that enter linearly are eliminated exa
arXiv:2606.23707v1 Announce Type: cross Abstract: EEG spatial super-resolution (EEGSR) in real deployments is challenged by random channel missingness, unstable electrode quality, and changing visible
arXiv:2602.02899v2 Announce Type: replace Abstract: Decentralized training is often regarded as inferior to centralized training because the consensus errors between workers are thought to undermine c
arXiv:2606.24219v1 Announce Type: new Abstract: Stochastic quantum neural networks (SQNNs) encode neuronal activations as qubits, synaptic topology as entanglement, and neural noise through a Lindblad
arXiv:2606.24194v1 Announce Type: cross Abstract: Conversational product search assistants offer a more expressive, natural, and interactive alternative to traditional keyword-based product search. Wi
arXiv:2606.23915v1 Announce Type: new Abstract: Practice often treats automatic metrics for attribution in LLM retrieval-augmented generation as interchangeable. We audit eight automatic scorers -- le
arXiv:2606.24130v1 Announce Type: cross Abstract: Traditional time-domain prediction of vessel motions in irregular waves usually relies on superposing responses from many regular-wave components, whi
arXiv:2601.03509v2 Announce Type: replace Abstract: We study continual skill acquisition in open-ended embodied environments where an agent must construct, refine, and reuse an expanding library of ex
arXiv:2606.24099v1 Announce Type: new Abstract: Algorithms have become central to scientific research in the era of artificial intelligence (AI). Although algorithm mentions in papers are often used t
arXiv:2606.23758v1 Announce Type: cross Abstract: Domain generalization learns from multiple source domains to generalize to unseen target domains. However, it often neglects the realistic case of lab
arXiv:2606.23693v1 Announce Type: new Abstract: Text-to-SQL enables users to query databases using natural language by generating executable SQL queries. Recent methods have increasingly adopted Large
arXiv:2606.24007v1 Announce Type: cross Abstract: Continual learning remains a major challenge for modern deep networks, partly because commonly used optimizers lack inherent mechanisms for continual
arXiv:2606.24390v1 Announce Type: cross Abstract: Standardized assessment of uterine MRI remains challenging due to anatomical variability, observer dependence, and the lack of workflow-integrated aut
arXiv:2403.04890v4 Announce Type: replace Abstract: In this paper, we propose a modified version of the MedQA-USMLE dataset, named MEDQA-OPEN, which contains open-ended medical questions without optio
arXiv:2606.24876v1 Announce Type: new Abstract: Generating explorable 3D scenes from a single image requires strong generative priors and accurate geometric representations suitable for downstream use
arXiv:2603.04560v2 Announce Type: replace Abstract: Recent works use a neuro-symbolic framework for general manipulation policies. The advantage of this framework is that -- by applying off-the-shelf
arXiv:2606.24234v1 Announce Type: new Abstract: Autonomous robotic inspection in maritime environments presents unique challenges for Visual Place Recognition (VPR) due to cross-scene perceptual shift
arXiv:2311.16707v2 Announce Type: replace-cross Abstract: Dense prediction is a fundamental requirement for many medical vision tasks such as medical image restoration, registration, and segmentation.
arXiv:2606.23880v1 Announce Type: new Abstract: From climate teleconnections to gene regulation, modern time-series datasets encompass tens or hundreds of interacting variables, making causal discover
arXiv:2606.23881v1 Announce Type: new Abstract: Knowledge-Based Visual Question Answering (KB-VQA) requires grounding visual queries to external knowledge beyond directly observable content in images.
arXiv:2603.19957v2 Announce Type: replace-cross Abstract: Pathology reports are structured, multi-granular documents encoding diagnostic conclusions, histological grades, and ancillary test results ac
Clem Delangue, CEO of Hugging Face, expressed strong confidence in the future dominance of local and open-source AI solutions over proprietary alternatives. The statement reflects optimism about the c
arXiv:2606.24621v1 Announce Type: cross Abstract: This paper introduces a categorical account of infinitesimal causality in Frobenius Markov categories equipped with tangent-bundle semantics. IDC capt
The FFASR Leaderboard is a benchmarking platform introduced by Hugging Face for evaluating Automatic Speech Recognition (ASR) systems on real-world performance metrics. It provides a standardized eval
It's a bird, it's a plane, it's a JEPA! Congrats on that great work that brought SIGReg and JEPAs to the sky--in the real world! Check out the paper! https://arxiv.org/abs/2606.23444 What should a wor
arXiv:2606.23745v1 Announce Type: cross Abstract: We present JEDEL, a framework for generating synthesis-ready DNA-encoded libraries (DELs) directly from three-dimensional pharmacophore representation
arXiv:2606.23877v1 Announce Type: cross Abstract: Jupyter Notebooks are an increasingly popular coding environment used across many domains, especially in Python-based data science and scientific comp
arXiv:2606.16428v2 Announce Type: replace-cross Abstract: Effective personalized AI-assisted learning demands systems that can not only generate accurate learner-specific educational materials, but al
arXiv:2606.19910v2 Announce Type: replace Abstract: Training automated pronunciation assessment often relies on labeled learner errors or non-native corpora that are costly to collect. We propose a li
arXiv:2606.24585v1 Announce Type: new Abstract: While the validity of LLMs' use in the legal context remains subject to ethical and legal debate, legal professionals are already experimenting with per
arXiv:2606.24340v1 Announce Type: new Abstract: In recent years, the Internet of Things (IoT) paradigm has been shifting toward batteryless, energy-harvesting architectures. Sustaining reliable operat
arXiv:2606.24375v1 Announce Type: new Abstract: Detecting anomalies in industrial objects is an important topic for increasing production efficiency. More complex objects often require the analysis of
arXiv:2505.02281v3 Announce Type: replace-cross Abstract: This paper explores the performance of a random Gaussian smoothing zeroth-order (ZO) scheme for minimising quasar-convex (QC) and strongly qua
arXiv:2602.15245v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL)-based biomechanical simulations have the potential to revolutionise HCI research and interaction design, but curre
arXiv:2606.24087v1 Announce Type: new Abstract: Reconstructing continuous speech from scalp electroencephalography (EEG) remains fundamentally challenging. EEG provides a weak, spatially diffuse, and
arXiv:2606.24450v1 Announce Type: cross Abstract: Perceiving physical contact is fundamental to dexterous manipulation. While robots often rely on dedicated hardware tactile sensors, humans exhibit a
arXiv:2606.24129v1 Announce Type: new Abstract: For a wheelchair user, a standard blue line on a map is often a broken promise. While platforms like OpenStreetMap (OSM) successfully capture where a pa
Clem Delangue, CEO of Hugging Face, announced a news update alongside Durga Malladi, likely regarding new developments, products, or initiatives from the company. The post was shared on X (formerly Tw
arXiv:2606.24353v1 Announce Type: new Abstract: Bird's-eye view (BEV) perception fuses multi-camera images into a unified top-down representation for autonomous driving. Despite recent progress, state
pretty sick that i get to work with Jake every day on making continual learning + memory accessible at scale for every single agent one common thread here is...the Trace a large part of Continual Lear
arXiv:2606.24561v1 Announce Type: new Abstract: Quadratic unconstrained binary optimization (QUBO)-based quantum computed tomography (CT) casts reconstruction as a binary quadratic problem for quantum
arXiv:2606.24437v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) architectures improve inference-time scaling by organizing multiple LLM agents into layered reasoning pipelines. However, existi
arXiv:2606.24338v1 Announce Type: new Abstract: Despite rapid progress, embodied reasoning under real-world variability remains challenging. Existing approaches rely on demonstration-driven sequential
arXiv:2606.24138v1 Announce Type: new Abstract: Generating explicit 3D city assets from a single satellite image is important for digital twins, urban simulation, and geospatial intelligence. Unlike s
arXiv:2606.24820v1 Announce Type: new Abstract: LLM agents solve repository-level coding tasks through multi-turn tool use, but utilize half their budget on locating faults before editing. Dedicated l
arXiv:2604.00208v2 Announce Type: replace Abstract: Comparing internal representations is a central goal in neuroscience and machine learning, but standard linear alignment metrics (Representational S
arXiv:2606.24350v1 Announce Type: new Abstract: Legged robots rely on accurate ground interaction awareness to traverse variable terrains, such as slippery surfaces. Existing slip detection methods of
Dong Cao / Bloomberg: Sources: Zhipu is considering a multibillion-dollar Hong Kong share sale after its stock surged 2,000% since its January IPO, pushing its market cap above $128B — Chinese artific