TRIBE v2 is a multimodal AI model that predicts human brain activity more accurately than linear encoding models and recovers established neuroscientific findings through in-silico testing.
arXiv preprint arXiv:2402.12345 , year=
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Nitsum dynamically adapts tensor parallelism and GPU splits in LLM serving to raise SLO-compliant goodput by up to 5.3 times over prior systems.
AgenticRAG equips an LLM with iterative retrieval and navigation tools, delivering 49.6% recall@1 on BRIGHT, 0.96 factuality on WixQA, and 92% correctness on FinanceBench.
citing papers explorer
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A foundation model of vision, audition, and language for in-silico neuroscience
TRIBE v2 is a multimodal AI model that predicts human brain activity more accurately than linear encoding models and recovers established neuroscientific findings through in-silico testing.
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Nitsum: Serving Tiered LLM Requests with Adaptive Tensor Parallelism
Nitsum dynamically adapts tensor parallelism and GPU splits in LLM serving to raise SLO-compliant goodput by up to 5.3 times over prior systems.
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AgenticRAG: Agentic Retrieval for Enterprise Knowledge Bases
AgenticRAG equips an LLM with iterative retrieval and navigation tools, delivering 49.6% recall@1 on BRIGHT, 0.96 factuality on WixQA, and 92% correctness on FinanceBench.