[L/R] next to the model name refers to the number of left and right context sentences the model was trained on. Rank is ordered according to recall@5.

Zero-Shot Setting

These models were deployed in a zero-shot manner (i.e. not trained on the RELiC dataset).

Rank	Model [L/R]	Contributors	recall@k
			1	3	5	10	50	100
1	RankGen [4/0]	Anonymous Razorbill
	PG-XL-inbk	^	6.0	12.2	15.4	20.7	37.3	46.1
	all-XL-both	^	4.9	9.2	11.9	16.5	31.5	39.9
	PG-XL-both	^	4.5	8.4	11.0	15.1	27.9	35.0
	PG-base-both	^	3.7	7.3	9.8	13.8	29.1	38.3
	PG-XL-gen	^	0.7	1.9	2.7	4.1	9.1	12.8
2	ColBERT [1/1]	Khattab and Zaharia, 2020*	2.9	6.0	7.8	11.0	21.4	27.9
3	c-REALM [1/1]	Krishna et al., 2021*	1.6	3.5	4.8	7.1	15.9	21.7
4	DPR [1/1]	Karpukhin et al., 2020*	1.3	3.0	4.3	76.6	15.4	22.2
5	BM25 [1/1]	Robertson et al., 1995*	1.2	3.2	4.2	5.9	12.5	17.0
6	SIM [1/1]	Wieting et al., 2019*	1.3	2.8	3.8	5.6	13.4	18.8

Trained Setting

These models were trained on the RELiC dataset.

Rank	Model [L/R]	Contributors	recall@k
			1	3	5	10	50	100
1	dense-RELiC [4/4]	RELiC team, 2022	9.4	18.3	24.0	32.4	51.3	60.8

* Baseline reported in RELiC paper