Knowledge catalogue
arXiv:2605.22242v1 Announce Type: new Abstract: Weather and climate forecasts are inherently uncertain due to chaotic dynamics, imperfect initial conditions, and incomplete representation of the under
Anusha Shah / Reuters: Delivery Hero says it received a takeover offer from Uber for €33 per share, a discount of 1.76% from Delivery Hero's close on Friday — German food delivery service Delivery Her
Dina Bass / Bloomberg: Dell says it has 5,000 clients for its AI Factory, a product line of servers with Nvidia chips, software, and services, including 1,000 new clients last quarter — Dell Technolog
arXiv:2605.22346v1 Announce Type: cross Abstract: Two of the most widely used methods for analysing graph data, Adjacency Spectral Embedding and Laplacian Spectral Embedding, often produce different r
arXiv:2605.22266v1 Announce Type: new Abstract: Federated learning enables collaborative training across distributed clients with heterogeneous data, but such heterogeneity often leads to unstable upd
arXiv:2605.21542v1 Announce Type: new Abstract: Country-level temporal panels are widely used in empirical analysis. Researchers often need to audit how different entities respond to historical signal
arXiv:2605.22531v1 Announce Type: new Abstract: There is a gap between the theoretical foundations of disentanglement and the practice of modern representation learning. Existing theoretical framework
arXiv:2605.22593v1 Announce Type: new Abstract: While deep ensembles are widely considered to be the default method for uncertainty quantification in deep learning, their effectiveness for graph-struc
arXiv:2605.22438v1 Announce Type: cross Abstract: Shilling is the use of artificial bids to make competition appear stronger and push prices upward. We study repeated first-price auctions in which shi
Nous Research conducted a large-scale deployment of Hermes today using isolated virtual machines and shared memory infrastructure via honchodotdev for team coordination. The post highlights enthusiasm
arXiv:2605.22454v1 Announce Type: new Abstract: Data rehearsal has emerged as a leading approach for mitigating catastrophic forgetting in Continual Reinforcement Learning (CRL). However, existing wor
arXiv:2605.21494v1 Announce Type: new Abstract: Overparametrized models can exhibit an excellent generalization performance, although they should be prone to overfitting according to classical statist
arXiv:2605.21648v1 Announce Type: new Abstract: We develop a mean-field theory of dropout as a perturbation of critical signal propagation at the edge of chaos. Dropout shifts the perfect-alignment fi
arXiv:2605.21539v1 Announce Type: new Abstract: We propose DualOptim+, a novel optimization framework for improving machine unlearning in large language models. It introduces a base state to capture c
During his second term, Trump will have cut 2 of the US most powerful innovation and wealth creation engines: 1. skilled legal immigration 2. (non-defense) research budgets We won't see the effect of
arXiv:2605.21951v1 Announce Type: new Abstract: Achieving self-evolution in intelligent agents requires the continual accumulation of new knowledge across changing task sequences without forgetting pr
arXiv:2605.21993v1 Announce Type: cross Abstract: Ranking systems used in decision-support settings should not only order candidates but also expose evidence that can be independently checked. We stud
arXiv:2605.22385v1 Announce Type: new Abstract: Explaining graph neural networks (GNNs) has become more and more important recently. Higher-order interpretation schemes, such as GNN-LRP (layer-wise re
arXiv:2605.21563v1 Announce Type: new Abstract: Recent reviews find that the vast majority of published healthcare federated learning (FL) studies never reach real-world deployment. We developed an em
arXiv:2605.22286v1 Announce Type: new Abstract: Text-based counseling is an important interface for AI mental-health support, where transcripts may be used to monitor depression severity and flag sess
arXiv:2605.22506v1 Announce Type: cross Abstract: Federated learning faces increasing threats from model poisoning attacks, which harms its application to improve privacy. Existing defense methods typ
arXiv:2602.10445v3 Announce Type: replace-cross Abstract: Generative Recommendation (GR) has excelled by framing recommendation as next-token prediction. This paradigm relies on Semantic IDs (SIDs) to
arXiv:2605.21903v1 Announce Type: cross Abstract: The integration of machine learning with domain-specific physics is transforming the design, monitoring, and control of electricity systems, where dat
arXiv:2605.21568v1 Announce Type: new Abstract: In this work, we extend the Equilibrium Propagation framework to skew-gradient systems and show an equivalence between deep Energy-Based Models and Hami
This post from Elon Musk's X account appears to be commentary on or engagement with content from @Erdayastronaut, likely discussing impressive or striking photographs, with Musk expressing enthusiasm
arXiv:2605.22304v1 Announce Type: cross Abstract: Integrating new data into knowledge graphs (KG) typically involves different tasks that are executed within workflows or pipelines There are many poss
arXiv:2510.11339v2 Announce Type: replace Abstract: Real-world graph typically evolve via a series of events, modeling dynamic interactions between objects across various domains. For dynamic graph le
Every 'self-evolving agent' paper this year has mutated text: prompts, skill files, workflow graphs, memory schemas. MOSS from USTC & HKUST argues this is the wrong layer. The thing that actually brea
arXiv:2605.22613v1 Announce Type: new Abstract: Recent LLM-guided evolutionary search methods have shown that iterative program mutation can discover strong algorithms, but they typically optimize eac
arXiv:2605.21994v1 Announce Type: new Abstract: GraphRAG conditions language models on subgraphs retrieved from knowledge graphs, encoded via message-passing GNNs. Because these encoders entangle node
arXiv:2605.21552v1 Announce Type: new Abstract: Confidence calibration for classification models is vital in safety-critical decision-making scenarios and has received extensive attention. General con
arXiv:2605.22243v1 Announce Type: new Abstract: Predictive modelling is important for health data analysis and data-driven clinical decision-making. However, predictive studies are challenging to desi
arXiv:2605.21614v1 Announce Type: cross Abstract: Worked examples are step-by-step solutions to problems in a specific domain, offered to students to acquire domain-specific problem-solving skills. Th
arXiv:2605.21617v1 Announce Type: new Abstract: Inference from interaction maps, such as centromere identification from genome-wide chromosome conformation capture techniques -- notably Hi-C -- can be
arXiv:2605.22537v1 Announce Type: new Abstract: Reinforcement learning methods such as GRPO have seen great popularity in LLM post-training. In GRPO, models produce completions to a set of prompts, wh
arXiv:2605.22596v1 Announce Type: new Abstract: Robotic tasks are typically specified by a tuple of factors, such as the object to be grasped, the obstacles to be avoided, the color of the target, and
arXiv:2605.22779v1 Announce Type: cross Abstract: Production systems generate millions of log lines daily, yet most anomaly detectors operate at the session or window-level, flagging groups of lines r
arXiv:2505.20349v2 Announce Type: replace-cross Abstract: Data-driven modeling of fluid dynamics has advanced rapidly with neural PDE solvers, yet a fair and strong benchmark remains fragmented due to
arXiv:2605.22795v1 Announce Type: cross Abstract: We propose and analyze a conservative drifting method for one-step generative modeling. The method replaces the original displacement-based drifting v
arXiv:2511.02043v4 Announce Type: replace Abstract: Attention is a fundamental building block of large language models (LLMs), so there have been many efforts to implement it efficiently. For example,
arXiv:2602.03067v3 Announce Type: replace Abstract: Entropic optimal transport (EOT) via Sinkhorn iterations is widely used in modern machine learning, yet GPU solvers remain inefficient at scale. Ten
Jordan Robertson / Bloomberg: FOIA lawsuit documents show hackers who breached SolarWinds potentially had access to all “treasury.gov” email addresses from July 6, 2020 to October 12, 2020 — New detai
Alexandra Alter / New York Times: For publishers, pirated audiobooks made with AI on YouTube are a growing issue: removal is cumbersome, and some are hiring tech companies to take them down — Illegal,
Francis Fukuyama on the U.S. as a declining power: American decline is a direct product of Trump's rise since 2016. It is as if Trump had decided to do everything in his power to weaken the United Sta
arXiv:2605.21541v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) remain vulnerable to transfer-based targeted attacks, where perturbations optimized on open-source surrogate
arXiv:2605.22124v1 Announce Type: cross Abstract: This is a verbatim copy of a technical report I wrote in 2017-2018 to obtain the law of the iterated logarithm using the guarantee on the wealth of an
arXiv:2605.22188v1 Announce Type: new Abstract: GPUs have significantly accelerated first-order methods for large-scale optimization, especially in continuous optimization. However, this success has n
arXiv:2605.22340v1 Announce Type: new Abstract: Single-cell RNA sequencing (scRNA-seq) provides high-dimensional profiles of cellular states, enabling data-driven modeling of cellular dynamics over ti
I can see this appears to be a Reddit post from r/ChatGPT with a casual, meme-style title that includes Hindi text ('हेलिकॉप्टर' meaning 'helicopter') and suggests the poster was testing language swit
@GaryMarcus Can't agree more. OpenAI seems struggling to build any successful product after ChatGPT. Codex is promising but it's still early, and it's following Claude Code. It's questionable whether
@GaryMarcus I don't understand why the people running the AI companies are held to a much lower standard. In early 2025 Sam Altman wrote 'we are now confident we know how to build AGI.' As predictions
@GaryMarcus If OpenAI gets bailed out, I will lobby with all of my effort to ensure whatever political faction was responsible gets voted out. I'm about to become a single issue voter over AI because
I can't create a knowledge base entry for this content without understanding what it actually discusses. The title alone is ambiguous and potentially inflammatory, and without accessing the Reddit thr
arXiv:2605.22507v1 Announce Type: new Abstract: We propose a new framework for generative modeling based on a discrete-time stochastic control formulation of measure transport. Adapting classic result
arXiv:2602.18141v2 Announce Type: replace Abstract: Long-range graph tasks are challenging for Graph Neural Networks (GNNs): global mechanisms such as attention or rewiring schemes can be computationa
ForgeFlash is a minimalist frontend interface designed for Stable Diffusion WebUI Forge that emphasizes simplified workflows inspired by Fooocus while maintaining direct access to essential advanced c
Last year I deepfaked my kid's stuffed animal to make it look like his plush deer was on vacation. It was an experiment to see if I could re-create the events depicted in a Gemini ad Google was runnin
GPT-5.5 Pro is a very solid fact checker. I can throw entire chapters at it and it will hunt down every key reference accurately. The only real annoyance is that it loves nuance, so returns a lot of “
arXiv:2512.11587v2 Announce Type: replace Abstract: Even for the gradient descent (GD) method applied to neural network training, understanding its optimization dynamics, including convergence rate, i
arXiv:2605.21502v1 Announce Type: cross Abstract: Graph neural networks (GNNs) are increasingly used to model biological systems, yet the reliability of post-hoc explanation methods for recovering mea