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Knowledgator Releases GLiFormer: A 575M-Parameter Encoder That Hits 91.10 F1 on Nested JSON Extraction Without Generating Tokens

Knowledgator released GLiFormer, an Apache-2.0 encoder (264M/575M) handling NER, classification, relations, and nested JSON extraction, scoring 91.10 F1.

Knowledgator Engineering released GLiFormer, a schema-conditioned encoder that performs NER, classification, relation extraction, nested JSON structuring, and embeddings without generating output tokens. GLiFormer Large v1 has 575.6M parameters and scores 91.10 F1 on nested JSON extraction, close to GPT-5.6-luna's 91.96; both checkpoints are Apache 2.0 on Hugging Face. Reported median latency is 69 ms on GPU for the base model, though relation extraction (21.33 micro-F1) still trails GLiNER-Relex and larger LLMs.

MarkTechPost · 12h agoModel release1

Enterprise Threat Intelligence Buying Guide: How to Choose the Right Solution

ANY.RUN published a buyer's guide for enterprise threat intelligence platforms, outlining evaluation criteria and promoting its own TI products.

ANY.RUN, whose sandbox, TI Lookup, and TI Feeds products are featured throughout, published guidance for selecting an enterprise threat intelligence provider. The guide recommends defining SOC or MSSP requirements first, then weighing intelligence quality and freshness, integrations including STIX/TAXII support, privacy, scalability, and proof-of-concept testing with real alerts. It emphasizes context and enrichment over raw data volume, citing figures such as TI Lookup results in about 2 seconds and 99% validated IOCs in its feeds.

ANY.RUNupdated · 1h agofirst · 2h agoIndustry 3 sources