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Feature/tvd mi metric #1080

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4db51f7
add tvd-mi prompt + parser
zrobertson466920 Nov 20, 2025
3cb0dfc
implement judgellmtvdmi and aggregator
zrobertson466920 Nov 20, 2025
bfa6e65
corpus aggregator + register metric + sanity test
zrobertson466920 Nov 20, 2025
81ec63c
add unit-testing + response normalization
zrobertson466920 Nov 20, 2025
0febc81
Document tvd_mi metric
zrobertson466920 Nov 21, 2025
5a0c3df
Add inspect implementation for tvd-mi metric
zrobertson466920 Nov 24, 2025
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1 change: 1 addition & 0 deletions docs/source/metric-list.mdx
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Expand Up @@ -61,3 +61,4 @@ These metrics need the model to generate an output. They are therefore slower.
- `llm_judge_llama_3_405b`: Can be used for any generative task, the model will be scored by a Llama 3.405B model using the HuggingFace API.
- `llm_judge_multi_turn_gpt3p5`: Can be used for any generative task, the model will be scored by a GPT3.5 model using the OpenAI API. It is used for multiturn tasks like mt-bench.
- `llm_judge_multi_turn_llama_3_405b`: Can be used for any generative task, the model will be scored by a Llama 3.405B model using the HuggingFace API. It is used for multiturn tasks like mt-bench.
- `tvd_mi`: Corpus-level LLM-as-a-judge metric that estimates a lower bound on total variation mutual information using paired responses. It assumes each example has two responses and a binary label indicating whether they are from the same underlying item (`1`) or from different items (`0`), and computes `TPR + TNR - 1` from the judge’s binary decisions.
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