data extraction
5 notes, newest first.
Self-prompting and cross-model consensus enable reproducible data extraction from scientific literature with large language models
The study explores the ability of large language models (LLMs) to extract contextualized information from research articles efficiently. The authors present four workflows that demonstrate LLMs can perform well in data…
Self-prompting and cross-model consensus enable reproducible data extraction from scientific literature with large language models
The paper investigates the performance of large language models (LLMs) in extracting contextualized information from research articles, finding that while LLMs can perform well with expert-curated prompts, they may…
Stealing Reasoning Traces from Proprietary LLM APIs
Researchers have identified a vulnerability in the way large language model providers handle their models' step-by-step reasoning. This vulnerability allows for the decryption of encrypted reasoning traces from one…
Stealing Reasoning Traces from Proprietary LLM APIs
Researchers have found a vulnerability in the way large language model providers handle encrypted reasoning traces. This vulnerability allows for decryption of these traces across different models within the same…
Finding H. pylori in the Fine Print: Evidence-Linked Multi-Agent Case Finding from Gastric Biopsy Reports
Researchers evaluated a system called nMAS that can automatically extract information about Helicobacter pylori infection from gastric biopsy reports. The system had an accuracy of 98.61% in classifying four binary…
