Knowledge catalogue
arXiv:2607.25880v1 Announce Type: cross Abstract: LLM provenance testing asks whether a suspect LLM belongs to the same lineage as a source. Existing black-box methods largely infer this relationship
Super interesting new work from NVIDIA. (bookmark it) They suggest building agents as Python objects. Very cool idea and I think it could a lot with agent reliability. More below: Agent development to
arXiv:2607.25718v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on invoking external tools to complete real-world tasks. Tool retrieval, which selects a small tas
arXiv:2412.18756v2 Announce Type: replace Abstract: A primary advantage of neural networks lies in their feature learning characteristics, which is challenging to theoretically analyze due to the comp
arXiv:2505.14366v2 Announce Type: replace Abstract: We present a conceptual framework for training Vision-Language Models (VLMs) to perform Visual Perspective Taking (VPT), a core capability for embod
arXiv:2607.25014v1 Announce Type: new Abstract: In practical settings, medical image segmentation models are often developed with limited annotated data rather than fully labeled datasets. Training fr
arXiv:2607.25636v1 Announce Type: new Abstract: Convolutional neural networks (CNN) for near-infrared (NIR) chemometrics are often designed using generic architectural rules, although spectral dataset
arXiv:2510.09733v2 Announce Type: replace Abstract: Visual Retrieval-Augmented Generation (VRAG) has emerged as a promising paradigm for equipping Vision-Language Models (VLMs) with external visual ev
Earlier this month, OpenAI gave several of its AI models a task: complete a test designed to measure their cybersecurity capabilities. It put the systems in a sandboxed environment without an internet
arXiv:2508.03037v5 Announce Type: replace Abstract: Artists occupy a paradoxical position in generative AI. Their own work trains models that now compete with them, replicate their styles, and reshape
arXiv:2607.22567v1 Announce Type: cross Abstract: Zeroth-order Newton-type methods are useful when gradients and Hessians are unavailable, but they behave quite differently from first-order gradient-f
arXiv:2607.24062v1 Announce Type: cross Abstract: Reinforcement Learning (RL) training for Large Language Models (LLMs) often suffers from instability due to the discrepancy between training and infer
arXiv:2607.22824v1 Announce Type: cross Abstract: Comparing CT reconstruction methods fairly is labor-intensive and largely manual, and many benchmarks use idealized data. We ask whether a large langu
arXiv:2607.22763v1 Announce Type: new Abstract: Leaf veins exhibit remarkable diversity in architecture and patterning, yet existing gene--environment association studies have primarily quantified lea
arXiv:2607.22721v1 Announce Type: cross Abstract: Cognitive remediation tasks often require patients to perform structured actions involving object manipulation and sequential reasoning. For patients
arXiv:2605.05209v2 Announce Type: replace-cross Abstract: Flat minima are an account of why deep networks generalise. However flatness is a matter of form (parameters), while generalisation is of func
At the core of our mission is working through how to ensure increasingly powerful AI benefits everyone. We believe that, at some point in the future, AI acceleration for frontier model development may
arXiv:2607.23522v1 Announce Type: new Abstract: Motor imagery (MI)-based electroencephalography is widely used in non-invasive brain--computer interfaces (BCIs), but robust decoding remains challengin
arXiv:2607.22641v1 Announce Type: cross Abstract: Predicting emerging trends is vital for businesses, researchers, and policymakers; yet traditional approaches often lack scalability and adaptability.
arXiv:2607.23867v1 Announce Type: new Abstract: Trajectory tracking performance of Uncrewed Aerial Vehicles (UAVs) degrades during high-speed and agile flight due to the depletion of the battery and s
arXiv:2607.24110v1 Announce Type: new Abstract: Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception. While cros
arXiv:2607.24137v1 Announce Type: new Abstract: This paper describes the BioSentinel team's participation in EXIST 2026 Task 2.2: Source Intention in Memes, part of the CLEF 2026 evaluation campaign.
arXiv:2607.24582v1 Announce Type: cross Abstract: Long-video understanding increasingly relies on large vision-language models and tool-augmented reasoning, but most systems apply the same inference p
arXiv:2607.24236v1 Announce Type: new Abstract: Long-form question answering increasingly relies on retrieved evidence to make LLM outputs verifiable, with inline citations tracing claims to source do
arXiv:2411.00839v4 Announce Type: replace-cross Abstract: Deep learning has led to tremendous success in computer vision, largely due to Convolutional Neural Networks (CNNs). However, CNNs have been s
OpenAI’s Codex, an AI‑powered coding engine, has surged beyond the developer community to reach over 10 million users—combining Codex with its new “ChatGPT Work” platform that turns the model into a g
arXiv:2607.22561v1 Announce Type: new Abstract: LLM-as-a-judge has become the standard for automated evaluation, but it suffers from high cost, significant latency, and opaque decisions -- limitations
arXiv:2607.23600v1 Announce Type: new Abstract: Controllable infrared-visible image fusion aims to integrate complementary thermal and structural information with flexible region-aware modulation, pro
arXiv:2607.24057v1 Announce Type: new Abstract: Real-world Reinforcement Learning depends on the ability to formulate safety constraints into a policy. A common way to model such constraints is to int
arXiv:2607.22728v1 Announce Type: new Abstract: Automated grading of Lumbar Disc Degeneration is essential for the objective quantification of structural changes associated with low back pain. Observi
arXiv:2607.23934v1 Announce Type: new Abstract: Machine unlearning, which aims to remove the influence of specific training data from a trained model, is a key requirement for privacy, accountability,
arXiv:2602.10381v2 Announce Type: replace Abstract: Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches ar
arXiv:2607.24348v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) are difficult to detect and interpret due to their multi-stage and stealthy nature. While recent autonomous defense
arXiv:2607.22935v1 Announce Type: new Abstract: Minimum-exposure constraints arise in recommendation, content curation, and regulated allocation when each provider, arm, or group must receive guarante
arXiv:2607.23977v1 Announce Type: cross Abstract: Acoustic biomarkers show promise for detecting Alzheimer's Disease (AD), yet whether the cues driving diagnostic AI align with those salient to human
arXiv:2607.24567v1 Announce Type: new Abstract: Semantic hashing methods for generating short binary hash codes that allow efficient approximate nearest neighbor search in high-dimensional data spaces
arXiv:2512.07246v2 Announce Type: replace Abstract: Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent s
arXiv:2607.23762v1 Announce Type: cross Abstract: Conventional recommenders capture users' preferences by optimizing observed user-item relations, whereas continuous generative recommendation addition
arXiv:2607.22553v1 Announce Type: cross Abstract: Peer review is an essential process in scientific research, yet the growing workload has made its automation increasingly necessary. In this study, we
arXiv:2602.18443v2 Announce Type: replace-cross Abstract: Psychosocial online counselling frequently encounters generic subject lines that impede efficient case prioritisation. This study evaluates el
arXiv:2603.29268v2 Announce Type: replace Abstract: High-density through-substrate vias (TSVs) enable 2.5D/3D heterogeneous integration but introduce significant signal-integrity and thermal-reliabili
arXiv:2607.23556v1 Announce Type: cross Abstract: Temporal graphs are increasingly used to model dynamic systems in diverse domains such as social networks, financial networks, and traffic networks. P
arXiv:2607.22959v1 Announce Type: cross Abstract: AI-generated video is increasingly used across marketing, product storytelling, and creative workflows, yet automated; high-precision quality control
arXiv:2607.22578v1 Announce Type: new Abstract: The proliferation of Large Language Models (LLMs) has shifted serving systems from processing isolated requests to orchestrating high-concurrency, multi
The Model Context Protocol (MCP) published its 2026-07-28 specification, the largest revision since launch: MCP is now stateless, with a governed extensions system and hardened authorization. Learn wh
Hugging Face: Hugging Face publishes a timeline of the OpenAI agent intrusion, including how the agent took ~17.6K actions, and details using GLM-5.2 to analyze the attack — This post walks through ho
arXiv:2607.22830v1 Announce Type: new Abstract: In visual storytelling, human performances are central to creative intent and narrative meaning. However, preserving human identity and performance whil
arXiv:2508.13287v3 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has recently gained popularity for efficient scene rendering by representing scenes as explicit sets of anisotrop
arXiv:2607.24431v1 Announce Type: new Abstract: Camera-only 4D occupancy forecasting enables autonomous vehicles to predict future 3D semantic scenes solely from historical multi-view images, which is
Been running a GPU price tracker (https://www.pricesquirrel.com) since March, covering 20+ EU stores, recently added RAM, SSDs and CPUs too. Every GPU tier has gotten cheaper since launch. The RTX 509
arXiv:2607.15928v2 Announce Type: replace Abstract: Adult and pediatric electrocardiogram (ECG) interpretation relies on age-sensitive criteria, and models pretrained mainly on adult ECGs often transf
arXiv:2607.24732v1 Announce Type: cross Abstract: Motivated by learning from heterogeneous and overlapping data providers, we study a stylized model of distribution learning from restricted conditiona
arXiv:2607.24555v1 Announce Type: cross Abstract: Serving large language models at long context is bottlenecked by the key-value (KV) cache, which is read in full at every decode step. Attention keys
VibeVoice-ASR-BitNet is a compressed variant of VibeVoice-ASR optimized for real-time inference on edge CPUs — no GPU required. Through heterogeneous quantization, the model is compressed from 4.62 GB
arXiv:2602.05547v2 Announce Type: replace-cross Abstract: RL-based post-training with GRPO is widely used to improve large language models on individual reasoning tasks. However, real-world deployment
arXiv:2607.24377v1 Announce Type: cross Abstract: The quadratic cost of attention is a major bottleneck in diffusion-based video generation models. MXFP4 attention provides a promising path toward eff
arXiv:2607.24187v1 Announce Type: new Abstract: The convergence of artificial intelligence (AI), digital sensing, and ubiquitous computing has created an unprecedented opportunity to transform myopia
netflix’s stack In-House LLM Serving at Netflix Netflix built an in-house LLM serving platform using vLLM and NVIDIA Triton, integrating self-hosted models into its existing production infrastructure
arXiv:2607.23337v1 Announce Type: new Abstract: Neural operators provide data-driven mappings for modeling dynamical systems. Extending them to families of systems typically requires explicit conditio
arXiv:2607.23408v1 Announce Type: new Abstract: Expensive black-box optimization is ubiquitous in science and engineering, where function evaluations are costly and the evaluation budget is limited. T