Knowledge catalogue
arXiv:2604.23912v1 Announce Type: new Abstract: Learning low-dimensional representations from multi-view relational data is challenging when underlying geometries differ across views. We propose Bary-
This post from Cristobal Valenzuela, a notable AI researcher and co-founder of Runway ML, uses the colloquial phrase 'He is a goat' (an acronym meaning 'Greatest Of All Time') to express acclaim for s
However, older versions have a critical CVE, so you do need to upgrade! If you use uv (thanks to @charliermarsh) you can pop this in your pyproject to work around it: ``` [tool.uv] override-dependenci
I know the litellm team have a *lot* going on, & I have no desire to increase their workload even more… But if you're a litellm user, this is a critical issue to know about - it currently force downgr
arXiv:2602.01386v2 Announce Type: replace-cross Abstract: Generative AI (GenAI) tools are rapidly transforming knowledge work, making AI literacy a critical priority for organizations. However, resear
I'm speechless at Google signing a deal to use our AI models for classified tasks. Frankly, it is shameful. For HR, I'm not speaking on behalf of Google but in my personal capacity, quoting public inf
arXiv:2604.24662v1 Announce Type: cross Abstract: Identifying the dynamical state variables of a system from high-dimensional observations is a central problem across physical sciences. The challenge
arXiv:2604.23865v1 Announce Type: cross Abstract: Foundation models of brain activity promise a new frontier for in silico neuroscience by emulating neural responses to complex stimuli across tasks an
arXiv:2509.20237v2 Announce Type: replace Abstract: Backchannels and fillers are important linguistic expressions in dialogue, but often treated as 'noise' to be bypassed in modern transformer-based l
This resource explains techniques for creating videos with consistent characters and voices in Runway, likely covering the use of reference materials, character sheets, and specific prompting strategi
arXiv:2604.23403v1 Announce Type: cross Abstract: This paper proposes a new method to improve the training efficiency of deep convolutional neural networks. During training, the method evaluates score
arXiv:2508.19068v2 Announce Type: replace Abstract: Single-Pixel Imaging (SPI) enables the reconstruction of objects using a single detector through sequential illuminations with structured light patt
arXiv:2503.20066v2 Announce Type: replace-cross Abstract: Dense reconstruction and differentiable rendering are fundamental tightly connected operations in 3D vision and computer graphics. Recent neur
arXiv:2604.24608v1 Announce Type: cross Abstract: Large Language Models (LLMs) have recently been explored as fine-grained zero-shot re-rankers by leveraging attention signals to estimate document rel
arXiv:2604.24737v1 Announce Type: cross Abstract: We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different so
Conditional diffusion models appear capable of compositional generalization, i.e., generating convincing samples for out-of-distribution combinations of conditioners, but the mechanisms underlying thi
arXiv:2604.22848v1 Announce Type: new Abstract: Recent times have seen an increase in demand of high quality Digital Elevation Models (DEMs) for the lunar surface, because they are highly important fo
arXiv:2604.22854v1 Announce Type: cross Abstract: Transformer architectures, including nnFormer,have demonstrated promising results in volumetric medical image segmentation by being able to capture lo
arXiv:2604.24332v1 Announce Type: new Abstract: Fast Adversarial Training (FAT) has proven effective in enhancing model robustness by encouraging networks to learn perturbation-invariant representatio
arXiv:2412.07160v3 Announce Type: replace Abstract: To equip artificial intelligence with a comprehensive understanding towards a temporal world, video and 4D panoptic scene graph generation abstracts
arXiv:2407.14974v2 Announce Type: replace-cross Abstract: Machine learning models are known to learn spurious correlations, i.e., features having strong relations with class labels but no causal relat
arXiv:2604.24167v1 Announce Type: new Abstract: Implicit neural representations (INRs) are increasingly being used as tools to map coordinates to signals, encompassing applications from neural fields
arXiv:2604.24586v1 Announce Type: new Abstract: Single-image point cloud reconstruction must infer complete 3D geometry, including occluded parts, from a single RGB image. While diffusion-based recons
arXiv:2604.22868v1 Announce Type: cross Abstract: Visual planning represents a crucial facet of human intelligence, especially in tasks that require complex spatial reasoning and navigation. Yet, in m
arXiv:2604.23974v1 Announce Type: new Abstract: Fake news generally refers to false information that is spread deliberately to deceive people, which has detrimental social effects. Existing fake news
arXiv:2510.11541v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) has demonstrated its ability to enhance Large Language Models (LLMs) by integrating external knowledge so
arXiv:2604.04353v2 Announce Type: replace-cross Abstract: Although HCI research papers offer valuable design insights, designers often struggle to apply them in design workflows due to difficulties in
arXiv:2604.23842v1 Announce Type: cross Abstract: Neologisms and emerging slang are central to daily conversation, yet challenging for non-native speakers (NNS) to interpret and use appropriately in c
arXiv:2604.23985v1 Announce Type: new Abstract: In autoregressive large language models (LLMs), temporal straightening offers an account of how the next-token prediction objective shapes representatio
arXiv:2604.24036v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have enhanced grounding capabilities in general scenes, their robustness in crowded scenes remains undere
arXiv:2512.20562v2 Announce Type: replace-cross Abstract: We study the problem of learning a low-degree spherical polynomial of degree ell_0 = Theta(1) ge 1 defined on the unit sphere in RR^d by train
Should we care about AI happiness? In our new research, we find evidence of functional AI wellbeing across several independent measures. We find which AI models are happiest, how to make them happier,
arXiv:2604.23996v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a prevalent backbone for large vision-language models (VLMs), yet how modality-specific signals should guide expert
arXiv:2401.07669v2 Announce Type: replace Abstract: Adapting CLIP for videos has gained popularity due to its semantic and rich representation. While CLIP is a good starting point, it typically underg
arXiv:2512.10959v2 Announce Type: replace Abstract: We introduce StereoSpace, a diffusion-based framework for monocular-to-stereo synthesis that models geometry purely through viewpoint conditioning,
arXiv:2604.22843v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has been proposed to mitigate hallucinations in large language models (LLMs), where generated outputs may be fact
arXiv:2402.19088v5 Announce Type: replace-cross Abstract: Live languages continuously evolve to integrate the cultural change of human societies. This evolution manifests through neologisms (new words
arXiv:2604.23623v1 Announce Type: new Abstract: Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit st
arXiv:2604.22951v1 Announce Type: new Abstract: Natural language data follows a power-law distribution, with most knowledge and skills appearing at very low frequency. While a common intuition suggest
This year's AI Accelerator winners shipped agents for finance teams, application security, and real estate. They built with $8M in credits and hands-on mentorship from Vercel, @awscloud, @OpenAI, @Ant
arXiv:2602.19019v2 Announce Type: replace Abstract: Generative AI models pose a significant challenge to intellectual property (IP), as they can replicate unique artistic styles and concepts without a
arXiv:2312.08410v5 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel
What's new in pip 26.1 - lockfiles and dependency cooldowns! Richard Si describes an excellent set of upgrades to Python's default pip tool for installing dependencies. This version drops support for
arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s
arXiv:2604.23709v1 Announce Type: new Abstract: Single image dehazing is often constrained by a trade-off between restoration quality and computational efficiency. While efficient, CNN networks strugg
arXiv:2604.22557v1 Announce Type: cross Abstract: The emergence of large-scale pretrained foundation models has transformed computer vision, enabling strong performance across diverse downstream tasks
At #ICLR? Don’t miss @realDanFu 👇 Latent & Implicit Thinking Workshop (LIT) 🕐 Workshop at 1:30 PM BRT (local) Exploring what comes after chain-of-thought and how models may actually reason. 🔗 https://
Amazon Quick Flows enables users to build automations for repetitive or routine tasks using simple, everyday language prompts , with no technical expertise required. The service uses an AI-powered UI
arXiv:2604.22618v1 Announce Type: new Abstract: Self-supervised learning in healthcare has largely relied on invariance-based objectives, which maximize similarity between different views of the same
arXiv:2604.22636v1 Announce Type: cross Abstract: Predicting customers' long-term revenue from sparse and irregular transaction data is central to marketing resource allocation in non-contractual sett
arXiv:2512.20831v2 Announce Type: replace Abstract: Real-world sequential decision-making often involves parameterized action spaces that require both, decisions regarding discrete actions and decisio
arXiv:2604.22529v1 Announce Type: new Abstract: Self-supervised learning has achieved remarkable success in learning visual representations from clean data, yet remains challenging when clean observat
arXiv:2603.24350v2 Announce Type: replace-cross Abstract: A key challenge to understanding self-awareness has been a principled way of quantifying whether an intelligent system has a concept of a 'sel
arXiv:2604.22724v1 Announce Type: new Abstract: Imitation learning is a well-established approach for machine-learning-based control. However, its applicability depends on having access to demonstrati
arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th
This article likely discusses techniques for building web applications that integrate OpenAI's APIs while maintaining user privacy through filtering mechanisms. It probably covers implementation strat
It just takes a little time and care to engage with the work of new folks in the field -- but it can make a big difference :D On a more personal note, I'm grateful to @jeremyphoward for helping me bre
arXiv:2601.11719v3 Announce Type: replace Abstract: Self-supervised learning, in the context of foundation model training, is a powerful pre-training method for learning feature representations withou
Google and Kaggle are offering a free five-day AI Agents Intensive course running June 15–19, 2026. The course teaches 'vibe coding' to create programs using natural language, with hands-on projects t
last week we dropped a super comprehensive guide on runtime requirements for long running agents! this week i'll be diving into each requirement and runtime capability that meets it, here's the lineup