Phi Llm
PulseAugur coverage of Phi Llm — every cluster mentioning Phi Llm across labs, papers, and developer communities, ranked by signal.
4 day(s) with sentiment data
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Build In-House HIPAA Compliant Voice Agent with LiveKit
This article provides a guide on building a HIPAA-compliant voice agent that operates entirely in-house, ensuring that Protected Health Information (PHI) remains within the user's control. It details the process of sett…
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AI security: Multi-layered approach to prevent sensitive data leakage
Organizations must implement a multi-layered security strategy to prevent sensitive data from being sent to third-party AI tools. This involves identifying and classifying data such as PII, PHI, secrets, and intellectua…
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Research: AI model safety outcomes predictable from first token, not deliberation
A new research paper challenges the assumption that "thinking tokens" in reasoning models inherently improve safety. The study found that the refusal or compliance outcome of models like GPT-OSS, Qwen, Olmo, and Phi is …
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Study: Post-training boosts LLMs for medical coding
A new study explores the effectiveness of post-training techniques for large language models (LLMs) in the domain of International Classification of Diseases (ICD) coding. The research indicates that while LLMs may perf…
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NeuraDebugger-Micro: 1.1B parameter model excels at code debugging
A new 1.1 billion parameter model called NeuraDebugger-Micro has been released, specifically designed for debugging code rather than general code generation. Developed by the Iranian team at Neuracoder and available on …
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InferBench app simplifies local LLM performance testing
A new open-source desktop application called InferBench has been released to help users determine which large language models (LLMs) can run on their local GPUs and at what speed. The tool automates the process of downl…
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SHIELD: A Diverse Clinical Note Dataset and Distilled Small Language Models for Enterprise-Scale De-identification
Researchers have introduced SHIELD, a new dataset comprising 1,394 clinical notes with over 10,000 identified Protected Health Information (PHI) spans. This dataset aims to address the limitations of older benchmarks by…
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Tiamat launches APIs for PHI scrubbing and text summarization
Tiamat has released a suite of APIs designed to assist developers in their projects. These APIs offer functionalities such as scrubbing Personally Identifiable Information (PHI) from text and summarizing content. The re…
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New MEDS dataset maps LLM math reasoning, bias, and attitudes
Researchers have introduced MEDS (Math Education Digital Shadows), a new dataset designed to evaluate how large language models perform in mathematics and identify potential biases. MEDS comprises 28,000 personas across…
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Python client developed to prevent PHI leakage in LLM prompts
A concise 67-line Python script has been developed to help users prevent Protected Health Information (PHI) from being included in their Large Language Model (LLM) prompts. This tool aims to enhance privacy and security…
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Scrubber and Presidio compared in 5-case PHI benchmark
A comparative benchmark evaluated Scrubber and Presidio, two tools designed for identifying and redacting Protected Health Information (PHI). The analysis focused on five specific case studies to assess their effectiven…
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LLMs show categorical perception and optimized data selection
Researchers have developed a new framework for optimizing data selection in large language models, adapting data weighting to specific tasks and models using efficient proxies. Another study investigates categorical per…
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Stealthy Backdoor Attacks against LLMs Based on Natural Style Triggers
Researchers have developed a new defense mechanism called Tail-risk Intrinsic Geometric Smoothing (TIGS) to protect large language models from backdoor attacks. TIGS operates during inference without requiring model upd…