We use the answer_similarity and answer_correctness metrics to measure the overall performance of the RAG chain. The evaluation shows that the RAG chain produces an answer similarity of 0.8873 and an answer correctness of 0.5922 on our dataset. The correctness seems a bit low so let’s ...
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1), and since the value of the cosine of a linear combination of vectors equals the the value of the cosine of any linear combination on the same vectors, the measure is independent from the scale
Open AI's new model claims to achieve 1800+ rating. I would assume in the near future, AI could achieve 4000+ rating and beattourist. Although I'll mark this day as the day when AGI comes, it will pose an existential threat to Codeforces!
Manual testing is a prudent measure until there are robust LLM testing platforms. Nikolaos Vasiloglou, VP of Research ML at RelationalAI, says, “There are no state-of-the-art platforms for systematic testing. When it comes to reliability and hallucination, a knowledge graph question-generating...
and it compares the prediction to the actual word in the data and adjusts the internal map based on its accuracy." This prediction and adjustment happens billions of times, so the LLM is constantly refining its understanding of language and getting better at identifying patte...
With this strategy we can improve the accuracy of a LLaMA-2 13B model (already fine-tuned with RL) on GSM8K from 53% to 65% when greedily sampled.\correspondence Alex Havrilla at 1 Introduction State-of-the-art large language models (LLMs) exhibit a wide range of downstream capabilities ...
This creates semantic representation one passage at a time, and then uses a heuristic metric to measure relevance. A reranking model evaluates the relevance of a passage to a given query. By analyzing the patterns, context, and shared information between the query and passage...
Hampering the interpretation of benchmark scores, evaluation data contamination has become a growing concern in the evaluation of LLMs, and an active area of research studies its effects. While evaluation data contamination is easily understood intuitively, it is surprisingly difficult to define ...