KRONE derives semantic execution hierarchies from flat logs to enable modular multi-level anomaly detection with hybrid local and nested-aware detectors plus limited LLM use, delivering 10% F1 gains and over 100x data efficiency on benchmarks and industrial data.
PromptNER: Prompting for named entity recognition
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IRC-Bench is a new dataset and evaluation framework for implicit entity recognition in reminiscence narratives, where entities must be inferred from non-local contextual cues across 1,994 transcripts linked to 12,337 WikiData entities.
YoNER supplies a multi-domain Yoruba NER corpus of 5k sentences plus OyoBERT, showing African-centric models beat multilingual baselines in-domain while cross-domain performance drops sharply for blogs and movies.
LLMs exhibit 20-40% lower recall on ambiguous human names for PII detection, worsening under prompt injections, as shown via the new AmBench benchmark.
DynamicNER is a dynamic-categorization multilingual NER dataset with 155 entity types paired with CascadeNER, a two-stage lightweight LLM method claiming higher fine-grained accuracy.
Small language models extract structured information from paediatric renal biopsy reports at up to 84.3% accuracy on CPU hardware with minimal clinician review.
A multi-step LLM-based pipeline constructs the first knowledge graph for nuclear fusion energy and enables RAG for multi-hop queries.
citing papers explorer
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KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction
KRONE derives semantic execution hierarchies from flat logs to enable modular multi-level anomaly detection with hybrid local and nested-aware detectors plus limited LLM use, delivering 10% F1 gains and over 100x data efficiency on benchmarks and industrial data.
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IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences
IRC-Bench is a new dataset and evaluation framework for implicit entity recognition in reminiscence narratives, where entities must be inferred from non-local contextual cues across 1,994 transcripts linked to 12,337 WikiData entities.
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YoNER: A New Yor\`ub\'a Multi-domain Named Entity Recognition Dataset
YoNER supplies a multi-domain Yoruba NER corpus of 5k sentences plus OyoBERT, showing African-centric models beat multilingual baselines in-domain while cross-domain performance drops sharply for blogs and movies.
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Can Large Language Models Really Recognize Your Name?
LLMs exhibit 20-40% lower recall on ambiguous human names for PII detection, worsening under prompt injections, as shown via the new AmBench benchmark.
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DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition
DynamicNER is a dynamic-categorization multilingual NER dataset with 155 entity types paired with CascadeNER, a two-stage lightweight LLM method claiming higher fine-grained accuracy.
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A Semi-Automated Annotation Workflow for Paediatric Histopathology Reports Using Small Language Models
Small language models extract structured information from paediatric renal biopsy reports at up to 84.3% accuracy on CPU hardware with minimal clinician review.
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Automated Construction of a Knowledge Graph of Nuclear Fusion Energy for Effective Elicitation and Retrieval of Information
A multi-step LLM-based pipeline constructs the first knowledge graph for nuclear fusion energy and enables RAG for multi-hop queries.