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This paper introduces DiscoSign, a modular LLM-based framework for discourse-aware translation from written text to sign language glosses. The approach is grounded in linguistic research and explicitly addresses discourse phenomena such as (i) spatial coreference resolution and (ii) Question-Answer Clauses (QACs); the excerpt indicates a third phenomenon is also handled but does not specify it.
A NVIDIA Developer post describes applying full‑stack NIM optimizations to production serving for the Nemotron 3 Ultra large language model, reporting up to a 2.5× increase in concurrent users served. The piece emphasizes that deployment is only the first step and that system‑level changes across the stack are needed to maximize real‑world throughput and scalability.
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