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LLMs can now rank millions of candidates with significant accuracy gains thanks to a novel K-means clustering and graph-based ensemble approach that overcomes context length limitations.
LLMs can now tap into arbitrarily long-term memories by retrieving "thoughts" – their own past reasoning steps – rather than just raw data, leading to significant performance gains.
Continuous diffusion can finally rival discrete methods in language modeling, thanks to LangFlow's novel architecture and training techniques.
