RankNovo

post-processor · Transformer (AR)

RankNovo: post-processor · Transformer (AR). Universal reranking

Universal reranking

Kind	post-processor
Deep learning	yes
Acquisition	both
Family	Transformer (AR)

Code

• https://github.com/BEAM-Labs/denovo/tree/main/RankNovo

Live stars, open issues and last-push figures are on the Code activity chart.

Checkpoints

Version	Trained on	Host	Licence	Size	Checked	Backup
shared with CrossNovo	—	Google Drive	MIT	607 MB	verified 2026-10-02	copy

A host marked archival has a DOI and keeps what it is given. The others can move or disappear, which is why they are checked rather than merely listed. verified means the bytes were fetched and hashed on the date shown; live means only that the host answered when last asked. Where a copy is linked, it is a backup of someone else’s weights kept in case the original link goes stale; the original is the link to cite and to prefer.

Data

What the papers describing this method trained it on and reported its results on, as each paper states it. A version is named only where the paper names one.

Trained on

• MassIVE-KB (v1 30M-PSM split (Casanovo)) · 2024 preprint, 2025 preprint, 2025 ML conference

Evaluated on

• Nine-species benchmark (original (DeepNovo, 2017)) · 2024 preprint, 2025 preprint, 2025 ML conference
• Nine-species benchmark (revised (build not stated)) · 2024 preprint, 2025 preprint, 2025 ML conference

Reported comparisons (3)

The comparison tables this method’s own papers print, standardised: every value on a 0-1 scale, methods down the side, the measure and then the species across. These are numbers papers report about themselves and their baselines. They are not a leaderboard, and they do not compare across tables: each was produced by a different group, on the dataset named in its corner, with each baseline either retrained, run from released weights or quoted from another paper. Where the paper says which, it follows the method’s name (hover it for the sentence); most papers do not say. Bold is the best value in a column and underline the runner-up, our ranking rather than the paper’s own marks.

Table1

Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing, page 7: Evaluation of RankNovo in comparison to baseline and base models on the 9-species-V1 and 9-species-V2 test sets. Bolded entries indicate the best-performing models. The symbol “†” indicates that the model serves as both a baseline and a base model. “⋆” signifies that the base models were developed and trained by us. Here, ByNovo is the best base model. So the performance of three self-trained base models (R-Casa, R-Contra, R-By) is only provided in Appendix D.1.

Nine-species benchmark	Amino acid precision
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
PEAKS	0.719	0.586	0.633	0.639	0.673	0.600	0.644	0.728	0.748	0.663
DeepNovo	0.742	0.602	0.630	0.610	0.694	0.623	0.679	0.731	0.750	0.673
PointNovo	0.768	0.589	0.644	0.606	0.712	0.626	0.730	0.733	0.779	0.687
Casanovo	0.749	0.603	0.629	0.586	0.679	0.689	0.668	0.721	0.684	0.667
Casanovo V2 · released	0.888	0.791	0.823	0.872	0.877	0.813	0.891	0.891	0.915	0.862
ContraNovo · released	0.901	0.807	0.848	0.920	0.896	0.839	0.913	0.898	0.919	0.882
ByNovo	0.920	0.823	0.876	0.917	0.914	0.841	0.932	0.912	0.934	0.897
RankNovo	0.926	0.838	0.885	0.929	0.920	0.860	0.938	0.918	0.938	0.906

Nine-species benchmark	Peptide recall
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
PEAKS	0.387	0.203	0.287	0.277	0.356	0.197	0.362	0.403	0.428	0.322
DeepNovo	0.449	0.253	0.330	0.293	0.422	0.286	0.436	0.454	0.462	0.376
PointNovo	0.518	0.298	0.396	0.351	0.478	0.355	0.511	0.513	0.534	0.439
Casanovo	0.537	0.330	0.406	0.341	0.478	0.426	0.506	0.521	0.490	0.448
Casanovo V2 · released	0.793	0.558	0.669	0.712	0.754	0.555	0.772	0.783	0.837	0.714
ContraNovo · released	0.815	0.575	0.711	0.820	0.780	0.616	0.799	0.794	0.854	0.752
ByNovo	0.833	0.582	0.731	0.789	0.799	0.596	0.814	0.807	0.871	0.758
RankNovo	0.851	0.620	0.752	0.820	0.813	0.629	0.836	0.822	0.885	0.781

RankNovo reranks the candidates of six base models. Casanovo V2 and ContraNovo are the released models; ByNovo is RankNovo's own in-house model, with an auxiliary b/y ion-annotation head (its Appendix B.4); R-Casanovo, R-ContraNovo and R-ByNovo are reverse-decoding versions of the three, trained by RankNovo's authors and recorded as the 'reverse decoding' variant. All six were trained on MassIVE-KB and evaluated zero-shot. '†' marks a model that is both baseline and base model, '⋆' one the authors trained. The plain Casanovo row repeats the values other papers print for Casanovo (0.749 and 0.537 on Bacillus) and the paper does not say where they come from. THE TEXT AND THE TABLE DISAGREE on V1: the prose gives RankNovo an amino-acid precision of 0.829 and a peptide recall '6.1%' above ByNovo; the table prints 0.824, and 0.660 against ByNovo's 0.623. The table's values are recorded.
In the paper: column amino acid precision, Average: the original table bolded RankNovo (0.824), RankNovo (0.906).
In the paper: column amino acid precision, Bacillus: the original table bolded RankNovo (0.874), RankNovo (0.926).
In the paper: column amino acid precision, C. bacteria: the original table bolded RankNovo (0.746), RankNovo (0.838).
In the paper: column amino acid precision, Honeybee: the original table bolded RankNovo (0.810), RankNovo (0.885).
In the paper: column amino acid precision, Human: the original table bolded RankNovo (0.802), RankNovo (0.929).
In the paper: column amino acid precision, M. mazei: the original table bolded RankNovo (0.840), RankNovo (0.920).
In the paper: column amino acid precision, Mouse: the original table bolded RankNovo (0.828), RankNovo (0.860).
In the paper: column amino acid precision, Ricebean: the original table bolded RankNovo (0.859), RankNovo (0.938).
In the paper: column amino acid precision, Tomato: the original table bolded RankNovo (0.844), RankNovo (0.918).
In the paper: column amino acid precision, Yeast: the original table bolded RankNovo (0.816), RankNovo (0.938).
In the paper: column peptide recall, Average: the original table bolded RankNovo (0.660), RankNovo (0.781).
In the paper: column peptide recall, Bacillus: the original table bolded RankNovo (0.738), RankNovo (0.851).
In the paper: column peptide recall, C. bacteria: the original table bolded RankNovo (0.539), RankNovo (0.620).
In the paper: column peptide recall, Honeybee: the original table bolded RankNovo (0.630), RankNovo (0.752).
In the paper: column peptide recall, Human: the original table bolded RankNovo (0.642), RankNovo (0.820).
In the paper: column peptide recall, M. mazei: the original table bolded RankNovo (0.672), RankNovo (0.813).
In the paper: column peptide recall, Mouse: the original table bolded RankNovo (0.583), RankNovo (0.629).
In the paper: column peptide recall, Ricebean: the original table bolded RankNovo (0.733), RankNovo (0.836).
In the paper: column peptide recall, Tomato: the original table bolded RankNovo (0.691), RankNovo (0.822).
In the paper: column peptide recall, Yeast: the original table bolded RankNovo (0.703), RankNovo (0.885).

Table6

Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing, page 17: Evaluation of RankNovo in comparison to baseline and base methods on the 9-species-V1 test set. Bolded entries indicate the best-performing models. The symbol “†” indicates that the model serves as both a baseline and a base model. “⋆” signifies that the base models were developed and trained by us.

The same table is also printed in RankNovo: A Universal Reranking Approach for Robust De Novo Peptide Sequencing (Table1, page 8).

Nine-species benchmark original (DeepNovo, 2017)	Amino acid precision
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
PEAKS	0.719	0.586	0.633	0.639	0.673	0.600	0.644	0.728	0.748	0.663
DeepNovo	0.742	0.602	0.630	0.610	0.694	0.623	0.679	0.731	0.750	0.673
PointNovo	0.768	0.589	0.644	0.606	0.712	0.626	0.730	0.733	0.779	0.687
Casanovo	0.749	0.603	0.629	0.586	0.679	0.689	0.668	0.721	0.684	0.667
Casanovo V2 · released	0.806	0.685	0.727	0.69	0.774	0.768	0.769	0.799	0.762	0.753
ContraNovo · released	0.828	0.706	0.761	0.771	0.798	0.799	0.804	0.808	0.782	0.784
ByNovo	0.858	0.723	0.791	0.767	0.823	0.803	0.836	0.828	0.804	0.804
Casanovo reverse decoding · retrained	0.804	0.699	0.728	0.719	0.769	0.776	0.782	0.795	0.762	0.759
ContraNovo reverse decoding · retrained	0.839	0.716	0.775	0.782	0.806	0.811	0.816	0.822	0.798	0.796
ByNovo reverse decoding	0.855	0.724	0.794	0.762	0.821	0.81	0.835	0.831	0.762	0.799
RankNovo	0.874	0.746	0.81	0.802	0.84	0.828	0.859	0.844	0.816	0.824

Nine-species benchmark original (DeepNovo, 2017)	Peptide recall
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
PEAKS	0.387	0.203	0.287	0.277	0.356	0.197	0.362	0.403	0.428	0.322
DeepNovo	0.449	0.253	0.330	0.293	0.422	0.286	0.436	0.454	0.462	0.376
PointNovo	0.518	0.298	0.396	0.351	0.478	0.355	0.511	0.513	0.534	0.439
Casanovo	0.537	0.330	0.406	0.341	0.478	0.426	0.506	0.521	0.490	0.448
Casanovo V2 · released	0.646	0.46	0.527	0.492	0.592	0.493	0.628	0.637	0.629	0.567
ContraNovo · released	0.684	0.487	0.576	0.624	0.628	0.563	0.676	0.655	0.669	0.618
ByNovo	0.708	0.499	0.597	0.584	0.639	0.545	0.696	0.667	0.676	0.623
Casanovo reverse decoding · retrained	0.628	0.467	0.515	0.511	0.57	0.505	0.611	0.611	0.601	0.558
ContraNovo reverse decoding · retrained	0.682	0.499	0.583	0.606	0.621	0.566	0.673	0.654	0.664	0.616
ByNovo reverse decoding	0.703	0.493	0.59	0.554	0.637	0.543	0.685	0.659	0.629	0.610
RankNovo	0.738	0.539	0.63	0.642	0.672	0.583	0.733	0.691	0.703	0.660

RankNovo reranks the candidates of six base models. Casanovo V2 and ContraNovo are the released models; ByNovo is RankNovo's own in-house model, with an auxiliary b/y ion-annotation head (its Appendix B.4); R-Casanovo, R-ContraNovo and R-ByNovo are reverse-decoding versions of the three, trained by RankNovo's authors and recorded as the 'reverse decoding' variant. All six were trained on MassIVE-KB and evaluated zero-shot. '†' marks a model that is both baseline and base model, '⋆' one the authors trained. The plain Casanovo row repeats the values other papers print for Casanovo (0.749 and 0.537 on Bacillus) and the paper does not say where they come from. THE TEXT AND THE TABLE DISAGREE on V1: the prose gives RankNovo an amino-acid precision of 0.829 and a peptide recall '6.1%' above ByNovo; the table prints 0.824, and 0.660 against ByNovo's 0.623. The table's values are recorded.

Table7

Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing, page 17: Evaluation of RankNovo in comparison to baseline and base methods on the 9-species-V2 test set. Bolded entries indicate the best-performing models. The symbol “†” indicates that the model serves as both a baseline and a base model. “⋆” signifies that the base models were developed and trained by us.

The same table is also printed in RankNovo: A Universal Reranking Approach for Robust De Novo Peptide Sequencing (Table2, page 8).

Nine-species benchmark revised (build not stated)	Amino acid precision
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
Casanovo V2 · released	0.888	0.791	0.823	0.872	0.877	0.813	0.891	0.891	0.915	0.862
ContraNovo · released	0.901	0.807	0.848	0.920	0.896	0.839	0.913	0.898	0.919	0.882
ByNovo	0.92	0.823	0.876	0.917	0.914	0.841	0.932	0.912	0.934	0.897
Casanovo reverse decoding · retrained	0.876	0.804	0.814	0.891	0.867	0.821	0.881	0.891	0.898	0.860
ContraNovo reverse decoding · retrained	0.909	0.815	0.865	0.923	0.901	0.849	0.919	0.907	0.925	0.890
ByNovo reverse decoding	0.919	0.822	0.879	0.912	0.912	0.843	0.932	0.913	0.936	0.897
RankNovo	0.926	0.838	0.885	0.929	0.920	0.860	0.938	0.918	0.938	0.906

Nine-species benchmark revised (build not stated)	Peptide recall
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
Casanovo V2 · released	0.793	0.558	0.669	0.712	0.754	0.555	0.772	0.783	0.837	0.714
ContraNovo · released	0.815	0.575	0.711	0.820	0.780	0.616	0.799	0.794	0.854	0.752
ByNovo	0.833	0.582	0.731	0.789	0.799	0.596	0.814	0.807	0.871	0.758
Casanovo reverse decoding · retrained	0.759	0.558	0.643	0.732	0.723	0.558	0.721	0.768	0.799	0.696
ContraNovo reverse decoding · retrained	0.821	0.581	0.719	0.815	0.779	0.620	0.804	0.798	0.861	0.755
ByNovo reverse decoding	0.831	0.585	0.729	0.781	0.794	0.589	0.815	0.803	0.873	0.756
RankNovo	0.851	0.620	0.752	0.820	0.813	0.629	0.836	0.822	0.885	0.781

RankNovo reranks the candidates of six base models. Casanovo V2 and ContraNovo are the released models; ByNovo is RankNovo's own in-house model, with an auxiliary b/y ion-annotation head (its Appendix B.4); R-Casanovo, R-ContraNovo and R-ByNovo are reverse-decoding versions of the three, trained by RankNovo's authors and recorded as the 'reverse decoding' variant. All six were trained on MassIVE-KB and evaluated zero-shot. '†' marks a model that is both baseline and base model, '⋆' one the authors trained. The plain Casanovo row repeats the values other papers print for Casanovo (0.749 and 0.537 on Bacillus) and the paper does not say where they come from.
In the paper: column peptide recall, Human: the original table only bolded RankNovo (0.820); ContraNovo (ContraNovo†) (0.820) ties with it and is bolded here too.

Compared against in other papers (1)

2 tables from 1 paper that report this method as a baseline, newest first. The caveats of the comparisons above hold twice over: each paper ran, retrained or quoted this method its own way, so its number here is that paper’s claim, not a measurement of the method. Where a paper says which it did, the word follows the method’s name.

ScopeNovo: a De Novo Peptide Sequencing Method Using Spectrum-Spectrum Similarity to Refine the Prediction Accuracy (2026) · 2 tables

Table 1 (Nine-species · revised (build not stated))

ScopeNovo: a De Novo Peptide Sequencing Method Using Spectrum-Spectrum Similarity to Refine the Prediction Accuracy, page 5: Comparison of de novo peptide sequencing methods on 9-species-V1 and 9-species-V2 benchmarks. For ScopeNovo we report two operating regimes: Setting 1 (External Library, spectrum-consistency reranking against a curated external spectral library), which characterizes the upper-bound performance attainable when high-quality external spectral resources are available; and Setting 2 (Self-Constructed Library), in which the reference library is bootstrapped entirely from high-confidence in-batch de novo predictions on the test data itself, placing ScopeNovo under the same resource assumptions as the baselines and yielding a direct comparison. In each column, the best value among the baselines and ScopeNovo (Setting 2) is in bold; ScopeNovo (Setting 1) is reported separately for reference and excluded from the bold comparison.

Nine-species benchmark revised (build not stated)	Amino acid precision
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
Casanovo	0.923	0.787	0.776	0.856	0.828	0.806	0.854	0.874	0.865	0.881
Casanovo V2	0.843	0.799	0.788	0.865	0.836	0.813	0.867	0.882	0.875	0.865
InstaNovo	0.852	0.751	0.799	0.847	0.848	0.634	0.894	0.864	0.877	0.850
ContraNovo	0.863	0.802	0.817	0.909	0.864	0.830	0.903	0.881	0.883	0.865
AdaNovo	0.792	0.816	0.756	0.800	0.804	0.757	0.759	0.831	0.801	0.794
RankNovo	0.836	0.836	0.891	0.836	0.879	0.920	0.896	0.893	0.879	0.880
π-PrimeNovo	0.874	0.806	0.824	0.870	0.869	0.808	0.921	0.885	0.891	0.866
ScopeNovo Setting 1	0.885	0.822	0.839	0.884	0.882	0.841	0.931	0.897	0.900	0.885
ScopeNovo Setting 2	0.877	0.814	0.829	0.879	0.874	0.821	0.926	0.889	0.892	0.868

Nine-species benchmark revised (build not stated)	Peptide accuracy
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
Casanovo	0.687	0.522	0.579	0.662	0.656	0.522	0.645	0.730	0.738	0.682
Casanovo V2	0.693	0.532	0.587	0.670	0.661	0.531	0.654	0.737	0.743	0.683
InstaNovo	0.704	0.512	0.625	0.670	0.666	0.504	0.679	0.721	0.758	0.698
ContraNovo	0.709	0.533	0.615	0.759	0.698	0.567	0.722	0.729	0.725	0.701
AdaNovo	0.636	0.624	0.597	0.590	0.641	0.472	0.538	0.693	0.653	0.635
RankNovo	0.713	0.603	0.617	0.717	0.712	0.559	0.744	0.724	0.680	0.682
π-PrimeNovo	0.712	0.572	0.612	0.710	0.714	0.548	0.766	0.719	0.684	0.697
ScopeNovo Setting 1	0.748	0.664	0.669	0.762	0.772	0.664	0.816	0.771	0.702	0.737
ScopeNovo Setting 2	0.728	0.619	0.641	0.750	0.743	0.611	0.788	0.745	0.691	0.716

The paper bolds the best of the baselines and ScopeNovo (Setting 2) only: 'ScopeNovo (Setting 1) is reported separately for reference and excluded from the bold comparison.' Bold and underline here rank every row, Setting 1 included; the paper's own marks were checked against its rule, and match it.

Table 1 (Nine-species · original (DeepNovo, 2017))

ScopeNovo: a De Novo Peptide Sequencing Method Using Spectrum-Spectrum Similarity to Refine the Prediction Accuracy, page 5: Comparison of de novo peptide sequencing methods on 9-species-V1 and 9-species-V2 benchmarks. For ScopeNovo we report two operating regimes: Setting 1 (External Library, spectrum-consistency reranking against a curated external spectral library), which characterizes the upper-bound performance attainable when high-quality external spectral resources are available; and Setting 2 (Self-Constructed Library), in which the reference library is bootstrapped entirely from high-confidence in-batch de novo predictions on the test data itself, placing ScopeNovo under the same resource assumptions as the baselines and yielding a direct comparison. In each column, the best value among the baselines and ScopeNovo (Setting 2) is in bold; ScopeNovo (Setting 1) is reported separately for reference and excluded from the bold comparison.

Nine-species benchmark original (DeepNovo, 2017)	Amino acid precision
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
Casanovo	0.788	0.676	0.708	0.676	0.754	0.765	0.761	0.792	0.756	0.743
Casanovo V2	0.801	0.687	0.721	0.687	0.767	0.774	0.768	0.802	0.768	0.754
InstaNovo	0.802	0.656	0.718	0.691	0.756	0.742	0.794	0.774	0.767	0.745
ContraNovo	0.828	0.700	0.764	0.778	0.798	0.803	0.804	0.812	0.787	0.785
AdaNovo	0.858	0.798	0.767	0.690	0.804	0.778	0.878	0.818	0.791	0.798
RankNovo	0.807	0.771	0.880	0.784	0.838	0.823	0.876	0.846	0.828	0.827
π-PrimeNovo	0.840	0.715	0.767	0.725	0.799	0.797	0.823	0.822	0.795	0.789
ScopeNovo Setting 1	0.849	0.715	0.778	0.729	0.811	0.809	0.816	0.825	0.796	0.797
ScopeNovo Setting 2	0.844	0.722	0.774	0.732	0.806	0.809	0.829	0.828	0.798	0.795

Nine-species benchmark original (DeepNovo, 2017)	Peptide accuracy
	Bacillus subtilis	Candidatus Thiodiazotropha endoloripes	Apis mellifera	Homo sapiens	Methanosarcina mazei	Mus musculus	Vigna mungo	Solanum lycopersicum	Saccharomyces cerevisiae	Average
Casanovo	0.621	0.437	0.494	0.446	0.568	0.485	0.593	0.622	0.601	0.551
Casanovo V2	0.630	0.445	0.504	0.455	0.579	0.493	0.600	0.629	0.607	0.559
InstaNovo	0.652	0.459	0.535	0.515	0.595	0.525	0.635	0.635	0.618	0.582
ContraNovo	0.688	0.486	0.580	0.625	0.633	0.574	0.678	0.674	0.673	0.628
AdaNovo	0.753	0.638	0.620	0.494	0.671	0.546	0.797	0.684	0.660	0.660
RankNovo	0.765	0.592	0.642	0.621	0.688	0.595	0.765	0.720	0.726	0.687
π-PrimeNovo	0.725	0.532	0.602	0.575	0.654	0.572	0.701	0.701	0.703	0.650
ScopeNovo Setting 1	0.789	0.610	0.665	0.628	0.731	0.660	0.755	0.752	0.744	0.711
ScopeNovo Setting 2	0.749	0.572	0.643	0.624	0.690	0.637	0.733	0.732	0.721	0.684

The paper bolds the best of the baselines and ScopeNovo (Setting 2) only: 'ScopeNovo (Setting 1) is reported separately for reference and excluded from the bold comparison.' Bold and underline here rank every row, Setting 1 included; the paper's own marks were checked against its rule, and match it.

Papers describing it (3)

• RankNovo: A Universal Reranking Approach for Robust De Novo Peptide Sequencing (2024, OpenReview, preprint)
• Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing (2025, arXiv, preprint)
• Universal Biological Sequence Reranking for Improved De Novo Peptide Sequencing (2025, ICML 2025, ML conference)

Authors (9)

Zijie Qiu, Jiaqi Wei, Xiang Zhang (Shanghai AI Lab), Sheng Xu, Kai Zou, Zhi Jin, Zhiqiang Gao, Nanqing Dong, Siqi Sun

Seen in the charts

• The architectures
• Code activity
• Models and the authors behind them

Back to the full map