named-entity recognition
PulseAugur coverage of named-entity recognition — every cluster mentioning named-entity recognition across labs, papers, and developer communities, ranked by signal.
5 day(s) with sentiment data
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LLM enhances Named Entity Recognition for Nepali tweets
Researchers have explored the use of Large Language Models (LLMs) to improve Named Entity Recognition (NER) for Nepali tweets, a task that is particularly challenging due to the low-resource nature of the language and t…
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New toolchain enables ML model development on AWS cloud FPGAs
Researchers have developed a new toolchain to facilitate the development of machine learning models on AWS cloud FPGA infrastructure using high-level languages. This system bridges Vitis HLS to the AFI workflow, address…
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Fine-tuned LLMs Gemma and Qwen compared to Encoder NER for information extraction
This article explores the effectiveness of fine-tuning local Large Language Models (LLMs) like Gemma and Qwen for specific tasks, comparing them against traditional encoder-based Named Entity Recognition (NER) models. T…
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New technique boosts performance of compressed transformer models
Researchers have developed a novel post-hoc embedding alignment technique to improve the performance of compressed transformer models. This method, called the Alignment Adapter (AlAd), uses a small feed-forward network …
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GoiBERT: Compact Vietnamese Language Models Achieve High Performance
Researchers have developed GoiBERT, a new family of compact Vietnamese language models designed for efficient deployment. These models, with 26M and 49M parameters, achieve strong performance across various benchmarks, …
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HealthcareNLP tutorial paper outlines future of NLP in medicine
A tutorial paper titled "HealthcareNLP: where are we and what is next?" was published on arXiv, offering a comprehensive overview of Natural Language Processing applications in the healthcare domain. The paper addresses…
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Timnit Gebru criticizes Bernie Sanders' AI associations
Timnit Gebru has criticized Bernie Sanders for his association with individuals who are perceived as anti-AI. Gebru pointed out Sanders' choice of allies and also expressed disapproval of Amy and Nermeen for allowing in…
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New framework enhances NER annotation quality for low-resource languages
Researchers have developed a scalable framework to improve the quality of Named Entity Recognition (NER) annotations, particularly for low-resource languages. This multi-step approach utilizes automated techniques, incl…
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AI models improve patient understanding of radiology reports via lay summaries
A new study published on arXiv explores methods for improving patient understanding of radiological reports by generating lay summaries. Researchers evaluated the effectiveness of Named Entity Recognition (NER) and Retr…
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New NE-R1 Framework Enhances Named Entity Recognition with Adaptive Retrieval
Researchers have introduced NE-R1, a new framework designed to improve Named Entity Recognition (NER) by adaptively using external knowledge. This approach combines retrieval-augmented generation with a reinforcement le…
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TWIX pipeline achieves top results in GutBrainIE benchmark for information extraction
Researchers have developed TWIX, a novel two-stage Information Extraction pipeline designed to address Named Entity Recognition (NER) and Relation Extraction (RE) tasks. This system was evaluated on the GutBrainIE bench…
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New method improves NER model robustness against noisy LLM labels
Researchers have developed a new method called error-type-aware loss reweighting to improve the robustness of named entity recognition (NER) models trained on noisy data generated by large language models (LLMs). The ap…
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Hugging Face unveils efficient multimodal encoder NeoMME, study favors encoders for Indic NER
Hugging Face has introduced NeoMME, a new family of multilingual multimodal encoders designed for efficiency. Unlike many generative models, NeoMME uses a single bidirectional Transformer to process both text and image …
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NLP unlocks ancient Indian medical texts with knowledge graphs
Researchers have developed a novel approach using Natural Language Processing (NLP) techniques to extract and classify knowledge from translated ancient Indian medical texts, such as the Sushruta Samhita. The method emp…
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New LLM method boosts zero-shot NER efficiency and accuracy
Researchers have developed a new method called "Just Pass Twice" (JPT) to improve the efficiency of large language models (LLMs) for zero-shot named-entity recognition (NER). JPT addresses the limitations of causal atte…
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New ContractScrub Benchmark Reveals LLM Weaknesses in Legal Contract Review
Researchers have introduced ContractScrub, the first benchmark specifically designed to evaluate the capabilities of large language models (LLMs) in performing contract scrubbing. This task involves reviewing legal agre…
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New AWED-PIPER framework offers FgNER and PII anonymization across 36 languages
Researchers have developed AWED-PIPER, an open-source framework designed for fine-grained Named Entity Recognition (FgNER) and Personally Identifiable Information (PII) anonymization. This system integrates agentic tool…
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New geometric filtering method enhances LLM-generated data for text classification
Researchers have developed a novel geometric filtering framework to improve the quality of synthetic data generated by large language models (LLMs) for text classification tasks. This method evaluates LLM-generated samp…
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CoffeeBSD seeks help with open-slopware issues on Codeberg
The CoffeeBSD project is seeking assistance with issues related to "open-slopware" on the Codeberg platform. Specifically, help is needed to address problems documented in an issue tracker on Codeberg. The call for help…
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AssemblyAI introduces comprehensive voice AI agent evaluation methods
AssemblyAI has introduced a method for evaluating voice AI agents, focusing on comprehensive testing beyond simple speech-to-text benchmarks. Their approach incorporates simulation-based tests to measure key performance…