Knowledge catalogue
arXiv:2607.28971v1 Announce Type: cross Abstract: Contrastive learning is widely used for user modeling in large-scale recommender systems, where standard in-batch negatives implicitly assume universa
arXiv:2607.28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cros
arXiv:2607.29596v1 Announce Type: cross Abstract: Vision-language-action models (VLAs), which leverage the cognition of multimodal information to infer physical-world actions, provide a generalized so
arXiv:2607.29044v1 Announce Type: new Abstract: Inline notes and collected commentaries are important forms of scholarly communication that evolved within the Confucian exegetical tradition, yet have
arXiv:2607.28855v1 Announce Type: cross Abstract: Dense 3D sensors in various real-world fields produce point clouds that are geometrically redundant for real-time processing. In this paper, we propos
arXiv:2605.05627v2 Announce Type: replace-cross Abstract: Sustainable forest management relies on precise species composition mapping, yet traditional ground surveys are labour-intensive and geographi
arXiv:2607.29473v1 Announce Type: new Abstract: The deployment of deep neural networks for visual affordance segmentation on wearable robots poses may prove critical, due to some conflicting aspects o
Most companies still rent AI by the token, build on someone else’s roadmap, and hope the next model release does not disrupt their systems. At ODSC AI West 2026, @Prof_OZ, Head of AI Developer Educati
arXiv:2607.15776v2 Announce Type: replace Abstract: OWL ontologies provide a formal knowledge representation framework that enables semantic reasoning, and have been widely adopted across domains such
arXiv:2511.00847v5 Announce Type: replace-cross Abstract: The widespread adoption of Large Language Models (LLMs) through Application Programming Interfaces (APIs) induces a critical vulnerability: th
arXiv:2607.29066v1 Announce Type: cross Abstract: Deception detection has critical implications for legal proceedings, law enforcement, and online security. Although human judgment is limited in accur
arXiv:2607.28993v1 Announce Type: cross Abstract: World Action Models (WAMs) have emerged as a promising paradigm by jointly modeling robot actions and future visual dynamics. However, their reliance
arXiv:2607.28666v1 Announce Type: new Abstract: Enterprise AI programmes stall at a rate that is widely quoted and poorly explained. This paper measures the mechanism. Six document-heavy workflows of
This is a wild result. Locus, the automated research system from @intology, post-trained Qwen3 base models that beat the official human-tuned Qwen3 1.7B Instruct release. SoTA on PostTrainBench! The m
arXiv:2603.11257v2 Announce Type: replace Abstract: Cardiac and lung ultrasound are technically demanding because operators must identify patient-specific intercostal acoustic windows and then navigat
arXiv:2507.21799v2 Announce Type: replace-cross Abstract: The empirical success of deep learning has spurred its application to the radio-frequency (RF) domain, leading to significant advances in Deep
Katherine Hamilton / Wall Street Journal: Visa plans to acquire Israeli company BioCatch, which uses AI to detect fraud and distinguish legitimate users from attackers in real time, for $2.4B in cash
arXiv:2604.04468v2 Announce Type: replace Abstract: Evaluating retail strategies before deployment is difficult, as outcomes are determined across multiple stages, from seller-side persuasion through
arXiv:2603.09161v2 Announce Type: replace-cross Abstract: Learning effective netlist representations is fundamentally constrained by the scarcity of labeled datasets, as real designs are protected by
Lily Hay Newman / Wired: Experts say US law is unprepared for rogue AI agents and models, as recent OpenAI and Anthropic incidents raise questions over legal liability and repercussions — Both major A
Illustrators have spent years sounding the alarm about generative artificial intelligence startups training their models on artists' work without permission. They've pointed out how the practice is ta
Top eight misconceptions about OpenAI’s amazing new Astra math results. 1. Expertise in one domain does not at all guarantee expertise in all or even most domains. There is an important, principled re
Hot take on OpenAI’s Astra: - Obviously impressive - But math is different from most other problems in that it is more amenable to to formal verification and synthetic data. How well it works in open-
Some things to note: 1) AI is getting very good at math and science. 2) Two years ago LLMs could not do basic math consistently 3) According to @polynoamial this cost less than $2000 in current API co
We are going to see a lot of vertically focused AI native companies accelerate. Routers, open-source models and specialized post-training enabled by companies like @FireworksAI_HQ have all made dramat
arXiv:2607.28528v1 Announce Type: new Abstract: The rapid growth of large language models (LLMs) has resurrected age-old questions in sociolinguistics and world Englishes, such as who decides what cou
arXiv:2511.22078v2 Announce Type: replace Abstract: Many real-world scenarios involving streaming information can be represented as temporal graphs, where data flows through dynamic changes in edges o
arXiv:2607.28065v1 Announce Type: new Abstract: Wind turbine blade defect detection remains highly challenging in real-world inspection scenarios due to limited on-site data and the subtle visual char
arXiv:2607.28019v1 Announce Type: new Abstract: User foundation models have demonstrated strong results in e-commerce and social recommendation, but most industrial deployments assume environments whe
arXiv:2607.28292v1 Announce Type: new Abstract: Large Language Models (LLMs) deployed in dynamic financial environments face a critical challenge: maintaining factual accuracy as market conditions, re
arXiv:2602.16111v2 Announce Type: replace-cross Abstract: Online media platforms track the share of impressions associated with content attributes, or prevalence, to evaluate trade-offs and set guardr
arXiv:2607.28119v1 Announce Type: new Abstract: In this paper, we draw a comparison between linguists in training, a trained linguist, and annotations generated by large language models (LLMs) to find
arXiv:2505.04999v2 Announce Type: replace-cross Abstract: Learning robot control policies from demonstrations typically requires action-labeled expert data, which is expensive to collect through teleo
arXiv:2507.05113v3 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) are susceptible to backdoor attacks, where adversaries poison training data to implant backdoor into the victim mo
arXiv:2607.27756v1 Announce Type: cross Abstract: Spoken dialog systems are typically designed for clean, dyadic interactions in which a single user and an assistant take turns speaking. Real-world so
arXiv:2607.28359v1 Announce Type: new Abstract: The Persian discourse marker hala ('now') exhibits remarkable multifunctionality, extending far beyond its temporal adverbial role to encompass a variet
arXiv:2606.18997v2 Announce Type: replace Abstract: Uncovering the true informational architecture of real-world complex systems requires disentangling how their components uniquely store, redundantly
arXiv:2607.27558v1 Announce Type: new Abstract: Recovering Parametric CAD sequences from raster-format 2D Computer-Aided Design (CAD) drawings accumulated prior to digital transformation is important
arXiv:2607.28035v1 Announce Type: new Abstract: Irregular multivariate time series are widely encountered in applications such as healthcare monitoring, human activity recognition, and environmental s
arXiv:2607.28293v1 Announce Type: new Abstract: While depth sensors have the potential to complement RGB data for affordance segmentation in wearable robots, their usage seems to remain underexplored.
arXiv:2607.28311v1 Announce Type: cross Abstract: Query optimization of Basic Graph Patterns (BGP) SPARQL queries over Knowledge Graphs (KG) requires accurate cardinality estimation. Recently publishe
arXiv:2607.27635v1 Announce Type: cross Abstract: Wearable sensors continuously capture fine-grained multivariate time-series data, providing opportunities to model behavioural patterns associated wit
Hugging Face's @ClementDelangue asked on CNN whether they will take legal action against OpenAI if they don't get the $100M commitment: 'We don't want to ... obviously we're a tiny startup with like 2
arXiv:2607.28124v1 Announce Type: new Abstract: As forecasts increasingly drive decisions in fields such as energy, transportation, and healthcare, understanding the historical data behind these predi
arXiv:2209.00546v5 Announce Type: replace-cross Abstract: Signed and directed networks are ubiquitous in real-world applications. However, there has been relatively little work proposing spectral grap
One of our big findings in our study at Procter and Gamble was that AI blurred the lines between jobs. Now OpenAI has a similar finding. Organizational boundaries are becoming porous, the walls thinni
arXiv:2607.27210v1 Announce Type: new Abstract: The exponential growth of scholarly publications requires automated tools for effective information synthesis. However, simple, single-shot prompting me
arXiv:2410.13174v3 Announce Type: replace-cross Abstract: The integration of artificial intelligence (AI) into medical imaging has advanced clinical diagnostics but poses challenges in managing model
arXiv:2503.12287v2 Announce Type: replace Abstract: High-precision, tight-clearance assembly demonstrations are indispensable for training tactile-aware robotic foundation models, yet their acquisitio
arXiv:2607.28391v1 Announce Type: new Abstract: World Action Models (WAMs) combine future-state prediction with robot action generation, but existing approaches largely rely on visual futures. Visual
This is not optional, things are getting chaotic now, and not dealing with this change won't make it go away. Plus, this could be a huge boost for both individual satisfaction & firm performance if do
arXiv:2607.27767v1 Announce Type: new Abstract: Graph neural networks (GNNs) can operate on large graphs but become infrastructure-sensitive at the scale of millions of nodes and typically require sca
arXiv:2511.12268v3 Announce Type: replace-cross Abstract: Early detection of oral cancer and potentially malignant diseases is a major challenge in low-resource settings due to the scarcity of annotat
arXiv:2607.28442v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled new possibilities for 3D question answering (3D-QA), a ke
arXiv:2512.05254v2 Announce Type: replace Abstract: As concerns around data privacy in machine learning grow, the ability to unlearn, or remove, specific data points from trained models becomes increa
arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver
arXiv:2607.27598v1 Announce Type: cross Abstract: Hasse clustering is an algorithm that extracts common patterns in sequential data and represents them in graphical forms. As the number of expected cl
arXiv:2607.27859v1 Announce Type: cross Abstract: Incentive programs are central to user acquisition in decentralized finance, but many reward systems rely on raw volume, transaction count, and wallet
arXiv:2607.26908v1 Announce Type: new Abstract: In many domains such as Palliative Care, Credit Assignment and Recommender Systems, predictions may causally influence the outcomes they predict. This p
Answer from OpenAI @emollick re ARC-AGI-3: human testers scored ~48% (ARC uploaded testers logs to HuggingFace some time ago, I believe). re GDPval: it’s close to saturated now, so we’re mostly lookin