Research separate from news
A preprint is a signal, not a finished product or an independently confirmed result. We therefore track research papers separately and show the actual state of supporting evidence for each one.
A significant claim from a single source is published only after further confirmation.
A research approach to evaluating and learning new policies in bandit problems. It combines historical data from the target domain and other domains, addressing limited-data scenarios, deterministic policy logging, and new actions that existing methods could not handle.
A research paper introduces a method for evaluating the causal impact of machine learning models on real outcomes (patient survival, criminal recidivism) in high-risk domains. It uses data from earlier randomized trials to bound the effect of a new model using assumptions about…
A research paper presents a taxonomy of 14 domain capabilities and 91 LLM subskills, organized into three layers based on cognitive science. An analysis of 15 934 papers from 2023–2025 found that research focuses primarily on linguistic-semantic competence (22.3 %) and reasoning (21.3 %), while six…
The new MA-DAR method addresses the integration of new facts with historical knowledge in continual learning. It eliminates representation conflicts (normalization dominance and semantic blurring) through alignment on a shared manifold and adaptive routing. It improves performance on four benchmark suites.
Researchers introduced Sharpness-Guided Equilibrium Sampling (SGS), a method for addressing the problem of imbalanced data in deep learning. The method dynamically adjusts class sampling during training based on class frequency and loss sharpness. On the CIFAR-100 dataset, it achieved an improvement of 10.85 points in accuracy…
An arXiv preprint describes MissHyper, a model for forecasting from clinical data. The hypergraph approach restores temporal patient context before message passing. Tests on MIMIC-III, MIMIC-IV, and PhysioNet 2012 show improvements over the baseline.
An arXiv paper introduces ACE (Adaptive Complementary Enhancement) for training graph neural networks on coarsened graphs. It addresses information loss during coarsening under heterophily through node feature reconstruction and structural regularization. The code is available on GitHub.
A research paper introduces SCOPE, a schema induction benchmark drawn from 24 sources focused on information extraction and event extraction, and SCION, a reference pipeline for constructing schemas. SCION achieves the highest F1 score among the methods compared, including LLM-only approaches. Code and data are publicly…
A research paper theoretically analyzes why adaptive out-of-distribution detectors degrade themselves during operation. The authors model memory bank degradation as a generalized Pólya urn and prove that the detector collapses when the slope's reproduction number exceeds one. They propose certified…
An arXiv research paper introduces MotifRole-Diff to improve discrete diffusion for molecular graph generation. Rather than uniform masking, it assigns masking rates according to empirically measured reconstruction difficulty. On the QM9 benchmark, it increased validity from 0.905 to 0.944; on…
A scientific paper from arXiv proposes a methodological framework for systematically integrating AI into product line development processes. Its effectiveness was validated through industrial case studies.
The article on arXiv introduces the FSE model for Named Entity Recognition with continual learning. The architecture combines a fast expert for filtering token spans and a slow expert for classifying entities. The "length-decay negative sampling" method addresses class imbalance. Results on datasets…
OpenAI has published research showing that ChatGPT users take on work tasks outside their formal role, which the company says blurs the boundaries between positions.
The startup Encord is experimenting with a headset from Zander Labs that measures brain waves to create higher-quality training datasets for robotic models. The aim is to demonstrate whether biological signals indicating errors and attention can improve training for physical manipulation.
A research paper introduces GH-ESD for automated error discovery in object detection and segmentation. It combines LLMs with Vision Language Models and achieves a Precision@10 of 0.73 (compared with 0.63 for the baseline).
Researchers at Cornell Tech are developing optical technology for transferring AI model parameters using QR-code-like patterns of light. The aim is to reduce the energy demands of AI systems in data centers, autonomous vehicles, and robotics. The development was presented at the IEEE/JSAP symposium.
A research paper on ABBEL, a framework that enables language models to work efficiently with long sequences of interactions. Rather than retaining the entire history, it proposes maintaining supervised "belief states" (states of knowledge). It addresses the problem of traditional summarization reducing quality, particularly on tasks such as…
A paper on arXiv mathematically proves that low-rank decomposition and quantization – two common methods for compressing language models – are not mutually independent, as previously assumed. According to the authors, combining them leads to a significant drop in performance; they propose the DAM method to mitigate this loss.
AI Radar monitors Czech and international sources every day, looking for changes that truly deserve attention.
The result is a quick overview of what has actually changed in the AI world, rather than another stream of articles.
Use the CS/EN switch to read the same Radar in Czech or English. English content is published after its translation has been checked, so new and older items may appear later.
Each row represents one event — not one article. At a glance, you can see its significance, credibility and main point.
Illustrative example, not a current news item.
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The detail page contains a fuller summary, its significance and original sources. Practical impact appears in the detail and the For individuals and For businesses views. An AI Flash item reaches the main selection only after it has been expanded and meets the publication rules.
We first summarize each event in the same way for everyone. Based on those same facts, we then explain what the change means for your own use and what it could mean for how a company operates.
Today’s briefing is the same for everyone. Pages For individuals and For businesses can be found in the main navigation — they select only events relevant to the given use case.
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