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I am very curious how 3.7 and o1 pro perform in this regard: > We evaluate 12 popular LLMs that claim to support contexts of at least 128K tokens. While they p
by consumer451 2y ago
I am very curious how 3.7 and o1 pro perform in this regard:
> We evaluate 12 popular LLMs that claim to support contexts of at least 128K tokens. While they perform well in short contexts (<1K), performance degrades significantly as context length increases. At 32K, for instance, 10 models drop below 50% of their strong short-length baselines. Even GPT-4o, one of the top-performing exceptions, experiences a reduction from an almost-perfect baseline of 99.3% to 69.7%.
https://arxiv.org/abs/2502.05167 https://arxiv.org/abs/2502.05167
- futopy 2y agoAnyone ever tries to restructure a 10K text? For example, structure a 45min - 1hr interview transcript in an organized way without losing any detailed numbers / facts / supporting evidence. I find that none of OpenAI's model is capable of this task. Models are trying to summarize and omitting details. I think such task does not require much intelligence, but surprisingly OpenAI's "large" context model cannot make it.