Live mathematical reference

Mathematical compendium

A live index of the equations in published articles. Each entry leads to its article, equation guide, and the terms explained there. New or edited published articles appear automatically.

1680 equations across 1484 symbols.

LPM(θ)=− E(x, yw, yl) ∼ DH∪DAI[log⁡σ(rθ(x,yw)−rθ(x,yl))]\mathcal{L}_{PM}(\theta) = -\,\mathbb{E}_{(x,\,y_w,\,y_l)\,\sim\, D_H \cup D_{AI}}\Big[\log \sigma\big(r_\theta(x,y_w) - r_\theta(x,y_l)\big)\Big]

1 published occurrence

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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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LPMAI(θ)=− E(x, yA, yB, p) ∼ DAI[p log⁡σ(rθ(x,yA)−rθ(x,yB))+(1−p) log⁡σ(rθ(x,yB)−rθ(x,yA))]\mathcal{L}^{AI}_{PM}(\theta) = -\,\mathbb{E}_{(x,\,y_A,\,y_B,\,p)\,\sim\, D_{AI}}\Big[p\,\log \sigma\big(r_\theta(x,y_A)-r_\theta(x,y_B)\big) + (1-p)\,\log \sigma\big(r_\theta(x,y_B)-r_\theta(x,y_A)\big)\Big]

1 published occurrence

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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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DCG@k=∑i=1k2 reli−1log⁡2(i+1),nDCG@k=DCG@kIDCG@k\mathrm{DCG@}k = \sum_{i=1}^{k} \frac{2^{\,\mathrm{rel}_i}-1}{\log_2(i+1)}, \qquad \mathrm{nDCG@}k = \frac{\mathrm{DCG@}k}{\mathrm{IDCG@}k}

1 published occurrence

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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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Faithfulness=claims supported by the retrieved contexttotal claims in the response\mathrm{Faithfulness} = \frac{\text{claims supported by the retrieved context}}{\text{total claims in the response}}

1 published occurrence

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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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MRR=1∣Q∣∑q=1∣Q∣1rankq\mathrm{MRR} = \frac{1}{|Q|}\sum_{q=1}^{|Q|} \frac{1}{\mathrm{rank}_q}

1 published occurrence

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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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score(D,Q)=∑qi∈QIDF(qi)⋅f(qi,D)⋅(k1+1)f(qi,D)+k1⋅(1−b+b⋅∣D∣avgdl)\mathrm{score}(D, Q) = \sum_{q_i \in Q} \mathrm{IDF}(q_i) \cdot \frac{f(q_i, D) \cdot (k_1 + 1)}{f(q_i, D) + k_1 \cdot \left(1 - b + b \cdot \dfrac{|D|}{\mathrm{avgdl}}\right)}

1 published occurrence

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This equation states an equality: the expressions on both sides have the same value under the article’s assumptions.

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