PubMed
PulseAugur coverage of PubMed — every cluster mentioning PubMed across labs, papers, and developer communities, ranked by signal.
- subsidiary of National Center for Biotechnology Information 100%
- subsidiary of United States National Library of Medicine 100%
- used by Gotit.pub 70%
- used by arXivLabs 70%
- used by SciFact 70%
- used by Influence Flower 60%
- uses Gotit.pub 60%
- used by graph attention network 60%
- competes with CiteSeerX 60%
- used by WikiCSSH: Extracting Computer Science Subject Headings from Wikipedia 60%
- used by CatalyzeX Code Finder for Papers 50%
9 day(s) with sentiment data
-
Chinese AI Model Releases Delayed on Weekends, Inference Engines Lagging
A Reddit post on the r/LocalLLaMA subreddit discusses the release schedule of models from China, noting that publications are not typically made on weekends. The post also humorously points out that inference engines ar…
-
AI coding assistants shift developer focus from problem-solving to review
A developer reflects on how AI coding assistants like Claude Code have transformed their daily workflow, shifting focus from intricate problem-solving to reviewing and accepting AI-generated solutions. While this change…
-
MCP servers enhance Claude Desktop with file, GitHub, and database access
The ModelContextProtocol (MCP) allows users to integrate various servers with Claude Desktop, enhancing its capabilities. Three key MCP servers are highlighted: a filesystem server for direct project file access, a GitH…
-
TRON framework uses biological networks to improve AI architecture search
Researchers have developed TRON (TRansfer Of Natural networks), a novel neuroevolution framework that leverages biological protein-protein interaction (PPI) networks as architectural priors for artificial neural network…
-
Anthropic's Claude AI expands with valuable code plugins and data connectors
Anthropic's Claude AI is expanding its capabilities with a growing ecosystem of plugins, with over 500 available in its marketplace as of late 2026. While many plugins function well, a recent analysis highlights a curat…
-
GraphRAG framework enhances gene-expression analysis with LLMs
Researchers have developed Graph-Based Over-Representation Retrieval-Augmented Generation (GBOR-RAG), a novel framework designed to enhance the interpretation of gene-expression studies. This system constructs a unified…
-
AI agents struggle with relevant PubMed retrieval for claim verification
A new research paper explores the effectiveness of language agents in biomedical claim verification, finding that agents capable of formulating their own PubMed queries significantly outperform those with fixed retrieva…
-
New AI agent automates iterative literature research across multiple sources
Researchers have developed Optimist Deep Research, an open-source agent designed to automate the process of literature research. Unlike traditional systems that perform a single retrieval step, this agent iteratively re…
-
New EHR analysis frameworks discover disease trajectories and improve forecasting · 2 sources tracked
Two research papers explore advanced methods for analyzing longitudinal electronic health records (EHRs) to discover disease trajectories and forecast temporal endpoints. The first paper introduces a graph-enhanced fram…
-
New benchmark VL-DocIR targets vision-based long document retrieval challenges
Researchers have introduced VL-DocIR, a new benchmark designed to improve vision-based long document information retrieval. This benchmark addresses the limitations of current systems that focus on short documents by si…
-
New fractional heat kernel improves graph learning with minimal training data
Researchers have developed a novel fractional heat-kernel framework for semi-supervised graph learning, designed to improve performance even with limited training data. This method combines nonlocal propagation with sus…
-
New method constructs diverse decision sources for improved pseudo-label learning
Researchers have developed a method to improve pseudo-label learning by constructing more informative decision sources. Instead of relying on multiple identical models, this approach modifies the internal structure of a…
-
AI tools lack clarity: 70% of descriptions fail to explain usage
A recent analysis of 46 popular MCP servers on Smithery revealed significant shortcomings in their tool descriptions. Approximately 69% of the 1,118 tools examined failed to specify their intended use, and 45% did not d…
-
Redpine Science platform enhances AI literature access and accuracy
Redpine Science, a new platform providing AI models and agents access to peer-reviewed literature via an API and the Model Context Protocol, has been evaluated using a four-quadrant approach. The evaluations show that a…
-
New BioStudyBench benchmark tests AI agents on post-cutoff biomedical studies
Researchers have introduced BioStudyBench, a new benchmark designed to evaluate AI agents' ability to replicate findings from post-cutoff biomedical studies. This benchmark consists of 25 tasks derived from studies publ…
-
New BioStudyBench benchmark tests AI agents on post-cutoff biomedical studies
A new benchmark called BioStudyBench has been developed to evaluate AI agents' ability to replicate findings from biomedical studies published after their knowledge cutoffs. The benchmark consists of 25 tasks derived fr…
-
New framework allows frozen AI models to learn from deployment experience
Researchers have developed a novel framework called FMEE (Frozen Models, Evolving Expertise) that enables large language models (LLMs) and vision-language models (VLMs) to learn from real-world deployment data without r…
-
New RL system TrustMed-RL advances evidence-grounded clinical diagnosis
Researchers have developed TrustMed-RL, a novel long-horizon reinforcement learning system designed for evidence-grounded clinical diagnosis. This system, trained on rare-disease cases from PubMed and annotated image pa…
-
New benchmark improves biological literature retrieval for model organisms
Researchers have developed a new retrieval benchmark for Dictyostelium, a model organism in cell and developmental biology, to address the challenges of sparse literature and organism-specific terminology. The benchmark…
-
O-Funnel library offers lossless data extraction from evolving documents
Researchers have developed O-Funnel, a new Python library designed to extract data from heterogeneous and evolving documents without manual pattern writing. O-Funnel separates structural capture from value extraction, t…