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13 signals found for "Fine-tuning"
Retrieval-augmented generation (RAG) has become a standard mechanism for grounding language models in external knowle...
Advanced reasoning typically requires Chain-of-Thought prompting, which is accurate but incurs prohibitive latency an...
Foundation models are reshaping computational biology. Pretrained on massive corpora of protein or genomic sequences,...
Recently, large language models (LLMs) have achieved promising progress in the fields of classical Chinese translatio...
🚀 Intercept and log LLM calls to build fine-tuning datasets for compact models, enabling cost-effective and efficien...
Real-world spatial intelligence requires reasoning over a continuous and evolving 3D world, yet existing VLMs and too...
Modern Lean theorem provers achieve strong performance only with substantial training and inference compute, driven i...
This technical report introduces VibeThinker-3B, a compact dense model with 3B parameters developed to investigate ho...
Few AI use cases elicit more outrage than writing: Using AI makes writing duller ... dumber ... robotic. It kills thi...
Making large language models (LLMs) deeply forget specific knowledge and values without sacrificing general capabilit...
Large language models (LLMs) achieve strong relation extraction (RE), but their computational demands and reliance on...
Recent advances in large language models (LLMs) have produced many specialized multimodal LLMs (MLLMs) that share com...
OpenAI’s fourth large language model (LLM), GPT-4, took an estimated 50 gigawatt-hours to train, or the equivalent of...