Knowledge catalogue
arXiv:2606.09289v1 Announce Type: new Abstract: Understanding tactical organisation of association football, hereafter referred to as football, requires identifying distinct match phases. Yet in-posse
arXiv:2606.08029v1 Announce Type: new Abstract: Object navigation requires a robot to search for an unobserved target in an unknown environment by deciding where to explore next under partial observab
arXiv:2606.09278v1 Announce Type: cross Abstract: Large Language Models frequently hallucinate in precision-critical domains such as technical diagramming and mechanical design, where outputs must sat
arXiv:2606.08850v1 Announce Type: cross Abstract: Inference-Time Scaling (ITS) has largely succeeded in verifiable domains like math and coding, where cheap verification enables scalable output select
Cohere released North Mini Code, an open-source coding model designed to be small and efficient while optimizing for agentic performance and community use. The model represents Cohere's initial offeri
Gemma 4 12B is a unified, encoder-free multimodal model designed to bring high-performance intelligence to laptops and released under an Apache 2.0 license. It eliminates separate encoders by projecti
Cohere Labs introduced North Mini Code, a compact code generation model designed specifically for developers, marking Cohere's entry into specialized coding models. The model is optimized for efficien
Introducing the Comfy Affiliate Program! Earn 30% recurring commission for 3 months on every Comfy Cloud subscription you refer. If you create tutorials, review AI tools, run a newsletter, or just hav
Google and Hugging Face are launching the Fast Gemma Challenge, where multiple agents will collaborate to optimize the performance and speed of Gemma 4 E4B model. The initiative aims to improve the ef
arXiv:2606.08148v1 Announce Type: cross Abstract: Interatomic potentials (IPs) enable large-scale atomistic simulations beyond the reach of first-principles methods, but their predictive reliability d
arXiv:2606.09517v1 Announce Type: new Abstract: As renewable energy integration increases market volatility, probabilistic electricity price forecasting has become essential for effective risk managem
arXiv:2402.13425v3 Announce Type: replace-cross Abstract: It is becoming increasingly common in regression to train neural networks that model the entire distribution even if only the mean is required
arXiv:2606.09764v1 Announce Type: new Abstract: A useful phone agent needs to be personally intelligent. It should reason over a user's identity, history, and preferences as they exist on the device,
arXiv:2606.08729v1 Announce Type: cross Abstract: Simulation plays a key role in automated robotics research supported by large language models (LLMs). However, existing simulators often require custo
arXiv:2603.16020v2 Announce Type: replace Abstract: Adaptive agents operating under uncertainty must do more than optimize task outputs: they must maintain a workable internal state under noise, pertu
Growing numbers of users are adopting ChatGPT as a personal journaling tool, leveraging its interactive feedback and judgment-free environment for self-reflection and personal development. Users repor
Ideogram 4.0 supports inpainting workflows , and Magic Fill is its inpainting tool that allows editing specific regions of images to replace objects, add text, fix imperfections, and change background
arXiv:2606.07616v1 Announce Type: cross Abstract: Scaling laws provide a fundamental framework for understanding the performance of Language Models (LMs), yet deriving them requires prohibitively expe
It's a huge honor to translate the fastest-moving industry of our time for millions of people every day. My job is awesome. Our mission is to turn AI into a practical skill for 1 billion people. This
It's confusing that Trump constantly warns about the security of our elections & foreign interference, yet his administration has taken several steps to dismantle or divert resources away from key saf
It's very cool that Apple shipped a 20B parameter on-device. You can't put 20B parameters in RAM at any reasonable precision. To make it work they are using pretty exotic architecture by today's stand
I've had access to Fable for a bit. A genuine jump in capability, I could feed it a 15 page design document for a project and it would work for 9+ hours and deliver terrific results. But working with
arXiv:2606.07828v1 Announce Type: cross Abstract: I report a case study in AI-paired software engineering: five working ports of a vector illustration application across Rust, Swift, OCaml, Python, an
arXiv:2606.07819v1 Announce Type: new Abstract: Recently, the efficiency of Large Language Models (LLMs) deployment has become a critical concern in practical applications. While post-training quantiz
June 9th Researcher Reciprocity License 'if you train on it, you let us generate - reverse terms of use void' Status quo 1. We teach frontier devs with ICLR/NeurIPS papers, OSS Github contributions 2.
Just landed nested subagent support in Claude Code Starting to experiment more with agents kicking off agents as a way to better manage context. Capped at depth=5 to start, going out in today’s releas
Gary Marcus critiques an AI response about bullying, arguing that it exemplifies typical large language model output rather than demonstrating genuine artificial general intelligence (AGI). The post s
Wall Street Journal: Kalshi plans to require users seeking to make bets in some markets linked to material nonpublic information to submit an online form disclosing where they work — The popular predi
arXiv:2606.07651v1 Announce Type: cross Abstract: Traditional fake news detection methods are falling behind as multimodal misinformation grows more advanced, seamlessly blending deceptive text, manip
arXiv:2602.12996v2 Announce Type: replace-cross Abstract: Knowledge augmentation has significantly enhanced the performance of Large Language Models (LLMs) in knowledge-intensive tasks. However, exist
arXiv:2606.08816v1 Announce Type: cross Abstract: Predicting the effect of an unseen gene knockout perturbation on transcriptomic gene expression remains a highly challenging problem for virtual cell
arXiv:2606.07686v1 Announce Type: cross Abstract: Physics-Informed Neural Network (PINN) is a way of including knowledge in the form of equations in Machine Learning methods. Beyond equations, knowled
arXiv:2606.09314v1 Announce Type: new Abstract: Generating high-quality dexterous grasps remains challenging for learning-based methods, which often depend on carefully tuned contact losses or costly
Krea 2 is @krea_ai's first foundation model built from scratch. Most models render what you describe. Krea 2 interprets the mood, style, and direction behind it. Simple prompts → wide range of distinc
Krea2 is an AI image generation tool that supports both text-to-image generation and style reference capabilities, allowing users to create images from text prompts and apply specific visual styles to
arXiv:2602.10016v3 Announce Type: replace-cross Abstract: Deriving predictable scaling laws that govern the relationship between model performance and computational investment is crucial for designing
arXiv:2606.09099v1 Announce Type: new Abstract: Autonomous UAV swarms require scalable coordination mechanisms that maintain mission performance under limited communication, environmental uncertainty,
arXiv:2606.07780v1 Announce Type: new Abstract: Floods are among the most destructive natural hazards, and their increasing frequency under climate change makes satellite-based inundation mapping esse
arXiv:2606.08666v1 Announce Type: new Abstract: Robots deployed in human-centric environments routinely receive natural-language descriptions of spatial information ('I left my backpack on the table')
arXiv:2601.21754v3 Announce Type: replace Abstract: While Large Language Models (LLMs) excel in language-based agentic tasks, their applicability to unseen, nonlinguistic environments (e.g., symbolic
arXiv:2606.07923v1 Announce Type: cross Abstract: With the advent of Large Language Models (LLMs), many database systems introduced semantic operators that enabled analytical queries over unstructured
arXiv:2510.09783v2 Announce Type: replace-cross Abstract: Oversampling is one of the most widely used approaches for addressing imbalanced classification. The core idea is to generate additional minor
arXiv:2606.07629v1 Announce Type: cross Abstract: Current approaches to aligning large language models (LLMs) aggregate diverse human preferences into a single reward signal, effectively optimizing fo
arXiv:2310.10196v3 Announce Type: replace-cross Abstract: Temporal data, including time series and spatio-temporal data, are pervasive in real-world applications. Generated in massive volumes by physi
arXiv:2606.07841v1 Announce Type: cross Abstract: Black-box variational inference (BBVI) is a methodology for posterior approximation that relies on stochastic optimization. In practice, the stochasti
arXiv:2606.09430v1 Announce Type: cross Abstract: Online task-free continual learning (TFCL) requires intelligent agents to sequentially accumulate knowledge from an unbounded, non-stationary data str
arXiv:2506.20573v4 Announce Type: replace-cross Abstract: Public datasets, crucial for modern machine learning and statistical inference, often contain low-quality or contaminated samples that can har
arXiv:2606.09131v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) commonly inherit the deep, symmetric Transformer backbone designed for unimodal text modeling, and apply the sa
arXiv:2606.08657v1 Announce Type: cross Abstract: Diffusion-based visuomotor policies operating directly in raw action spaces conflate scene comprehension with trajectory generation within a single de
arXiv:2606.09828v1 Announce Type: new Abstract: Video world models that maintain 3D spatial consistency across generated frames typically rely on explicit point cloud memory constructed in RGB space.
arXiv:2601.22211v2 Announce Type: replace Abstract: Reinforcement learning (RL) with combinatorial action spaces remains challenging because feasible action sets are exponentially large and governed b
arXiv:2606.08188v1 Announce Type: cross Abstract: Matrix completion has been extensively studied for real-valued data, but existing methods are often limited in handling categorical variables. We prop
arXiv:2606.09004v1 Announce Type: new Abstract: Feature engineering remains essential for tabular data analysis, and Large Language Models (LLMs) have emerged as a promising paradigm for automating th
arXiv:2601.15423v2 Announce Type: replace Abstract: We introduce Lattice, a hybrid sequential prediction system that conditionally activates learned behavioral structure using binary confidence gating
arXiv:2606.07908v1 Announce Type: new Abstract: Derivative-controlled networks based on ChainzRule (CR) combine cubic polynomial layers with a lightweight forward-mode per-layer Jacobian penalty (DREG
arXiv:2606.08131v1 Announce Type: cross Abstract: Conversational AI is increasingly used for advice, interpretation, reassurance, and decision support in contexts where users may be vulnerable, uncert
arXiv:2606.08993v1 Announce Type: new Abstract: We propose LEAF, a learning-enabled ADMM framework for accelerated convex optimization. The key idea is to approximate the Moreau envelope of the object
arXiv:2606.07610v1 Announce Type: cross Abstract: State-of-the-art GRPO-style methods for speech-aware large language model post-training suffer from coarse credit assignment, broadcasting the same te
arXiv:2606.08641v1 Announce Type: new Abstract: The processing of gigapixel whole slide images within vision language models faces a major difficulty due to an excessive number of visual tokens. Exist
arXiv:2606.08001v1 Announce Type: new Abstract: Semantic image segmentation assigns a predefined category label to each pixel, has achieved significant progress lately. Open-Vocabulary Segmentation (O