The Ledger

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Insight
Angelopoulos: Static benchmarks are intrinsically unable to evaluate generative models
“Static benchmarks are intrinsically, to some extent, unable to measure generative model performance. And the reason is because you cannot Pre-annotate all the outputs of a generative model. You change the model. It's like the distribution of your data is chang…”
Anastasios Angelopoulos Nov 1, 2024 ▶ 6:40 In the Arena: How LMSys changed LLM Benchmarking Forever
Insight
Angelopoulos: Highly effective LLM routers only need simple heuristics like length
“Well, I think that you can build a very, very simple router that is very effective. So let me give you an example. You can build a great router with one parameter, and the parameter is just like, I'm gonna check if my question is hard, and if it's hard, then I…”
Anastasios Angelopoulos Nov 1, 2024 ▶ 36:33 In the Arena: How LMSys changed LLM Benchmarking Forever
Insight
Angelopoulos: Live voter data asymptotically eliminates pre-release ELO bias
“What happened is that over time, because we're getting new data, it'll get adjusted down. So if there's any bias that gets introduced at that stage in the long run, it actually doesn't matter because asymptotically, basically like in the long run, there's way …”
Anastasios Angelopoulos Nov 1, 2024 ▶ 32:16 In the Arena: How LMSys changed LLM Benchmarking Forever
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