Research papers improving performance of LLMs [1/3]

Research papers published from January 16th to February 15th, 2025 proposing context length and architectural changes in LLMs

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Highlights

• InfiniteHiP prunes tokens like scissors, extending context to 3M

• LongRoPE stretches context to 2M+ tokens with fine-tuning

• DarwinLM uses evolution to prune LLMs , keeping performance high with structured pruning and training

• New paper draws a line between context length and model size

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