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3,243 papers
We present Berna R7 v3, a 1.2B-parameter language model trained from scratch using the DNA-Kernel Plexus architecture — a novel approach in which neural capacity is allocated through dynamic, self-growing "cells" guided by a six-dimensional knowledge vector. Trained on 2.66B tokens (English, mathematics, and code) over...
REGISTRATION TIMING This record was created after the review was completed and is a retrospective registration. The review was not prospectively registered. The literature search was executed on 4 October 2026, and study selection, data extraction, risk-of-bias assessment and the meta-analyses were completed before thi...
Although vitrification has transformed assisted reproductive technology, it occurs during a critical developmental window characterized by extensive epigenetic remodeling and transcriptional recalibration; freeze-thaw procedures expose gametes and embryos to osmotic, cryoprotectant, oxidative, and mitochondrial stress,...
Company registers and forms record countries as free text: in any language, misspelled, abbreviated, historical, or not a place at all. CountryCode-Decide is a 74.7 MB open model (mmBERT-small, two heads, 8-bit ONNX) that maps such a string, read with its field and register, to an ISO 3166-1 alpha-2 or ISO 3166-2:US co...
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Generative models trained on the output of earlier models lose knowledge across generations, rare knowledge first. The remedies that work all bring in information from outside the loop – fresh human data, verifiers, curators – and the theory of model collapse treats that supply as given: a fixed archive, drawn from a f...
Evaluating whether scholarly research contributes to a Sustainable Development Goal (SDG) requires an interpretive framework that combines the goal definition, its targets, contribution criteria, and the document itself. Instruction-tuned large language models can instantiate this framework in context, producing a cons...
This dissertation asks whether compression can be made capability-aware by borrowing the unit of analysis from mechanistic interpretability, and presents the problem formulation, the gap identified in a targeted review of the compression and interpretability literatures, and the design of a first experiment measuring c...
This study examined the relationships between Data Availability Statement (DAS) categories, citation counts, and the evolution of research data-sharing practices. We analysed 653,490 research articles published between 2010 and 2025 in the ten open-access journals with the most DAS-containing articles, using PubMed Cen...
Web resources rarely carry the educational metadata that teachers use to judge whether a resource fits their lesson, and dedicated educational repositories that do carry it cover only a fraction of what teachers find through web search. Closing this gap in real time, at the point of search, requires classifiers that ar...
Large Language Model (LLM) workflows increasingly decompose knowledge-intensive generation into planning, role assignment, subtask execution, and synthesis. Although this structure may support specialization, it also adds coordination and computational overhead. We present a preliminary task-level comparison of a Direc...
Long-lived technical organizations depend on senior subject matter experts whose knowledge is only partially preserved in reports, publications, and archival metadata. Digital libraries preserve those records, but they rarely provide centralized, expert-scoped, question-answering access to the knowledge of people who l...
Evidence synthesis methods, such as systematic reviews (SR), require research teams to find, select, evaluate, and synthesize all available evidence to answer a specific research question in a reproducible and transparent, bias-reduced manner. Early in the process, teams must screen all unique titles and abstracts gath...
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A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
We’re giving developers, enterprises, scientists, and consumers access to Gemini 4 Argon, our latest frontier model.
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