diff --git a/README.md b/README.md
index ebdc4ee..c8221c7 100644
--- a/README.md
+++ b/README.md
@@ -265,24 +265,42 @@
| [local-politics-BERT](http://local-politics.jp/%e5%85%ac%e9%96%8b%e7%89%a9/local-politics-bert/) | 政治 | BERT (base) | Wikipedia, 国会会議録, 地方議会会議録 | 地方議会会議録コーパスプロジェクト | CC BY-SA 4.0 | ◯ ([SC-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-scratch), [SC-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-scratch), [SC-2M-wiki](https://huggingface.co/local-politics-jp/bert-base-japanese-wikipedia-scratch-2m), [SC-2M-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-scratch-2m), [SC-2M-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-scratch-2m), [FP-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-further), [FP-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-further)) [^18] |
-## 埋め込み (Embeddings) 作成に特化したモデル
+## 埋め込み (Embeddings) 作成に特化したモデル [^21]
-| | アーキテクチャ | 開発元 | ライセンス |
+### Bi-Encoders
+
+#### Single-representation bi-encoders
+
+| | 入力で扱えるトークン数 | 開発元 | ライセンス |
|:---|:---:|:---:|:---:|
-| [JaColBERTv2.5](https://www.answer.ai/posts/2024-08-02-jacolbert-v25.html)
([JaColBERTv2.4](https://huggingface.co/answerdotai/JaColBERTv2.4), [JaColBERTv2.5](https://huggingface.co/answerdotai/JaColBERTv2.5)) | ColBERTv2 | Answer.AI | MIT |
-| [JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)
([JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)) | ColBERTv2 | 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
-| [JaColBERT](https://arxiv.org/pdf/2312.16144.pdf)
([JaColBERT](https://huggingface.co/bclavie/JaColBERT)) | ColBERTv2 | 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
-| [Japanese SimCSE](https://github.com/hppRC/simple-simcse-ja)
([cl-nagoya/unsup-simcse-ja-base](https://huggingface.co/cl-nagoya/unsup-simcse-ja-base), [cl-nagoya/unsup-simcse-ja-large](https://huggingface.co/cl-nagoya/unsup-simcse-ja-large), [cl-nagoya/sup-simcse-ja-base](https://huggingface.co/cl-nagoya/sup-simcse-ja-base), [cl-nagoya/sup-simcse-ja-large](https://huggingface.co/cl-nagoya/sup-simcse-ja-large)) | SimCSE | 名大 武田・笹野研 | CC BY-SA 4.0 |
-| [GLuCoSE](https://prtimes.jp/main/html/rd/p/000000123.000022705.html)
([pkshatech/GLuCoSE-base-ja](https://huggingface.co/pkshatech/GLuCoSE-base-ja)) | LUKEベースの文埋め込みモデル
(GLuCoSE) | PKSHA Technology | Apache 2.0 |
-||||
-| [colorfulscoop/sbert-base-ja](https://huggingface.co/colorfulscoop/sbert-base-ja) | Sentence-BERT | Colorful Scoop | CC BY-SA 4.0 |
-| [MU-Kindai/SBERT-JSNLI-base](https://huggingface.co/MU-Kindai/SBERT-JSNLI-base)
[MU-Kindai/SBERT-JSNLI-large](https://huggingface.co/MU-Kindai/SBERT-JSNLI-large) | Sentence-BERT | 近畿大学 (研究室不明) | ？ |
-| [MU-Kindai/Japanese-SimCSE-BERT-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-large-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-unsup)
[MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-base-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-sup)
[MU-Kindai/Japanese-SimCSE-BERT-large-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-sup) | SimCSE | 近畿大学 (研究室不明) | MIT |
-| [pkshatech/simcse-ja-bert-base-clcmlp](https://huggingface.co/pkshatech/simcse-ja-bert-base-clcmlp) | SimCSE | PKSHA Technology | CC BY-SA 4.0 |
-| [MU-Kindai/Japanese-MixCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-base)
[MU-Kindai/Japanese-MixCSE-BERT-large](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-large) | MixCSE | 近畿大学 (研究室不明) | MIT |
-| [MU-Kindai/Japanese-DiffCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-DiffCSE-BERT-base) | DiffCSE | 近畿大学 (研究室不明) | MIT |
-| [bclavie/fio-base-japanese-v0.1](https://huggingface.co/bclavie/fio-base-japanese-v0.1) | | 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | |
-| [cl-nagoya/shioriha-large-pt](https://huggingface.co/cl-nagoya/shioriha-large-pt) | | 名大 武田・笹野研 | |
+| [RoSEtta](https://prtimes.jp/main/html/rd/p/000000169.000022705.html)
([pkshatech/RoSEtta-base-ja](https://huggingface.co/pkshatech/RoSEtta-base-ja)) | 1,024 | PKSHA Technology | Apache 2.0 |
+| [GLuCoSE v2](https://prtimes.jp/main/html/rd/p/000000169.000022705.html)
([pkshatech/GLuCoSE-base-ja-v2](https://huggingface.co/pkshatech/GLuCoSE-base-ja-v2)) | 512 | PKSHA Technology | Apache 2.0 |
+| [Ruri](https://arxiv.org/abs/2409.07737)
([cl-nagoya/ruri-pt-small](https://huggingface.co/cl-nagoya/ruri-pt-small), [cl-nagoya/ruri-pt-base](https://huggingface.co/cl-nagoya/ruri-pt-base), [cl-nagoya/ruri-pt-large](https://huggingface.co/cl-nagoya/ruri-pt-large), [cl-nagoya/ruri-small](https://huggingface.co/cl-nagoya/ruri-small), [cl-nagoya/ruri-base](https://huggingface.co/cl-nagoya/ruri-base), [cl-nagoya/ruri-large](https://huggingface.co/cl-nagoya/ruri-large)) | 512 | 名大 笹野研 | Apache 2.0 |
+| [Japanese SimCSE](https://github.com/hppRC/simple-simcse-ja)
([cl-nagoya/unsup-simcse-ja-base](https://huggingface.co/cl-nagoya/unsup-simcse-ja-base), [cl-nagoya/unsup-simcse-ja-large](https://huggingface.co/cl-nagoya/unsup-simcse-ja-large), [cl-nagoya/sup-simcse-ja-base](https://huggingface.co/cl-nagoya/sup-simcse-ja-base), [cl-nagoya/sup-simcse-ja-large](https://huggingface.co/cl-nagoya/sup-simcse-ja-large)) | 512 | 名大 笹野研 | CC BY-SA 4.0 |
+| [GLuCoSE](https://prtimes.jp/main/html/rd/p/000000123.000022705.html)
([pkshatech/GLuCoSE-base-ja](https://huggingface.co/pkshatech/GLuCoSE-base-ja)) | 512 | PKSHA Technology | Apache 2.0 |
+| [colorfulscoop/sbert-base-ja](https://huggingface.co/colorfulscoop/sbert-base-ja) || Colorful Scoop | CC BY-SA 4.0 |
+| [MU-Kindai/SBERT-JSNLI-base](https://huggingface.co/MU-Kindai/SBERT-JSNLI-base)
[MU-Kindai/SBERT-JSNLI-large](https://huggingface.co/MU-Kindai/SBERT-JSNLI-large) || 近畿大学 (研究室不明) | ？ |
+| [MU-Kindai/Japanese-SimCSE-BERT-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-large-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-unsup)
[MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-base-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-sup)
[MU-Kindai/Japanese-SimCSE-BERT-large-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-sup) || 近畿大学 (研究室不明) | MIT |
+| [pkshatech/simcse-ja-bert-base-clcmlp](https://huggingface.co/pkshatech/simcse-ja-bert-base-clcmlp) || PKSHA Technology | CC BY-SA 4.0 |
+| [MU-Kindai/Japanese-MixCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-base)
[MU-Kindai/Japanese-MixCSE-BERT-large](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-large) || 近畿大学 (研究室不明) | MIT |
+| [MU-Kindai/Japanese-DiffCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-DiffCSE-BERT-base) || 近畿大学 (研究室不明) | MIT |
+| [bclavie/fio-base-japanese-v0.1](https://huggingface.co/bclavie/fio-base-japanese-v0.1) || 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | |
+| [cl-nagoya/shioriha-large-pt](https://huggingface.co/cl-nagoya/shioriha-large-pt) || 名大 笹野研 | |
+
+#### Multi-representation bi-encoders
+
+| | 開発元 | ライセンス |
+|:---|:---:|:---:|
+| [JaColBERTv2.5](https://www.answer.ai/posts/2024-08-02-jacolbert-v25.html)
([JaColBERTv2.4](https://huggingface.co/answerdotai/JaColBERTv2.4), [JaColBERTv2.5](https://huggingface.co/answerdotai/JaColBERTv2.5)) | Answer.AI | MIT |
+| [JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)
([JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)) | 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
+| [JaColBERT](https://arxiv.org/pdf/2312.16144.pdf)
([JaColBERT](https://huggingface.co/bclavie/JaColBERT)) | 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
+
+### Cross-Encoders
+
+| | 開発元 | ライセンス |
+|:---|:---:|:---:|
+| [Ruri-Reranker](https://arxiv.org/abs/2409.07737)
([cl-nagoya/ruri-reranker-stage1-small](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-small), [cl-nagoya/ruri-reranker-stage1-base](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-base), [cl-nagoya/ruri-reranker-stage1-large](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-large), [cl-nagoya/ruri-reranker-small](https://huggingface.co/cl-nagoya/ruri-reranker-small), [cl-nagoya/ruri-reranker-base](https://huggingface.co/cl-nagoya/ruri-reranker-base), [cl-nagoya/ruri-reranker-large](https://huggingface.co/cl-nagoya/ruri-reranker-large)) | 名大 笹野研 | Apache 2.0 |
+| [hotchpotch/japanese-reranker-cross-encoder-xsmall-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-xsmall-v1)
[hotchpotch/japanese-reranker-cross-encoder-small-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-small-v1)
[hotchpotch/japanese-reranker-cross-encoder-base-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-base-v1)
[hotchpotch/japanese-reranker-cross-encoder-large-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-large-v1)
[hotchpotch/japanese-bge-reranker-v2-m3-v1](https://huggingface.co/hotchpotch/japanese-bge-reranker-v2-m3-v1) | 個人 (舘野祐一) | MIT |
## 視覚言語モデル (Vision-Language Models)
@@ -532,4 +550,6 @@
[^19]: 詳細は以下の記事を参照: [大規模言語モデルTanuki-8B, 8x8Bの位置づけや開発指針など](https://zenn.dev/matsuolab/articles/377f7ae8b1169e), [大規模言語モデルを開発するにあたっての事前・事後学習の戦略メモー特に合成データについてー](https://zenn.dev/matsuolab/articles/34036f017fae9e)
-[^20]: ORPO を行う前に、Gemma 2 Instruct と Gemma 2 Base の差分の Chat Vector を加えている。
\ No newline at end of file
+[^20]: ORPO を行う前に、Gemma 2 Instruct と Gemma 2 Base の差分の Chat Vector を加えている。
+
+[^21]: 埋め込みモデルの分類は [Dense Text Retrieval based on Pretrained Language Models: A Survey (Zhao+, 2022)](https://arxiv.org/abs/2211.14876) を参考に行った。Bi-Encoder は 2つの入力を個別にモデルに入力し、それぞれベクトル化した上で、それらの内積やコサイン類似度を入力の近さとして定式化するアーキテクチャである。それに対し、Cross-Encoder は 2 つの入力を組み合わせたものをモデルに入力し、モデル内部で近さを直接計算するアーキテクチャである。情報抽出の分野では、Cross-Encoder の方が計算コストがかかるが、入力の近さをよりきめ細かくモデルが計算することが期待されるため、抽出結果の順序を再検討するリランカーとして用いられることも多い。なお、Bi-Encoder の中でも、入力を単一のベクトルではなく（トークンごとなどの）複数のベクトルとして表現するタイプのもの（例: ColBERT）があるため、Single-representation bi-encoders と Multi-representation bi-encoders にさらに細分化している。
\ No newline at end of file
diff --git a/en/README.md b/en/README.md
index a94c3ee..34d39bb 100644
--- a/en/README.md
+++ b/en/README.md
@@ -263,24 +263,42 @@ Please point out any errors on the [issues page](https://github.com/llm-jp/aweso
| [local-politics-BERT](http://local-politics.jp/%e5%85%ac%e9%96%8b%e7%89%a9/local-politics-bert/) | Politics | BERT (base) | Wikipedia, Minutes of the National Diet, Minutes of the Local Assembly | Japanese Local Assembly Minutes Corpus Project | CC BY-SA 4.0 | ◯ ([SC-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-scratch), [SC-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-scratch), [SC-2M-wiki](https://huggingface.co/local-politics-jp/bert-base-japanese-wikipedia-scratch-2m), [SC-2M-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-scratch-2m), [SC-2M-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-scratch-2m), [FP-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-further), [FP-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-further)) [^18] |
-## Sentence and Document Embeddings
+## Sentence and Document Embeddings [^21]
-| | Architecture | Developer | License |
+### Bi-Encoders
+
+#### Single-representation bi-encoders
+
+| | Max Context Length | Developer | License |
|:---|:---:|:---:|:---:|
-| [JaColBERTv2.5](https://www.answer.ai/posts/2024-08-02-jacolbert-v25.html)
([JaColBERTv2.4](https://huggingface.co/answerdotai/JaColBERTv2.4), [JaColBERTv2.5](https://huggingface.co/answerdotai/JaColBERTv2.5)) | ColBERTv2 | Answer.AI | MIT |
-| [JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)
([JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)) | ColBERTv2 | Individual ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
-| [JaColBERT](https://arxiv.org/pdf/2312.16144.pdf)
([JaColBERT](https://huggingface.co/bclavie/JaColBERT)) | ColBERTv2 | Individual ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
-| [Japanese SimCSE](https://arxiv.org/pdf/2310.19349.pdf)
([cl-nagoya/unsup-simcse-ja-base](https://huggingface.co/cl-nagoya/unsup-simcse-ja-base), [cl-nagoya/unsup-simcse-ja-large](https://huggingface.co/cl-nagoya/unsup-simcse-ja-large), [cl-nagoya/sup-simcse-ja-base](https://huggingface.co/cl-nagoya/sup-simcse-ja-base), [cl-nagoya/sup-simcse-ja-large](https://huggingface.co/cl-nagoya/sup-simcse-ja-large)) | SimCSE | Nagoya University Takeda-Sasano Group | CC BY-SA 4.0 |
-| [GLuCoSE](https://prtimes.jp/main/html/rd/p/000000123.000022705.html)
([pkshatech/GLuCoSE-base-ja](https://huggingface.co/pkshatech/GLuCoSE-base-ja)) | Sentence embedding model based on LUKE
(GLuCoSE) | PKSHA Technology | Apache 2.0 |
-||||
-| [colorfulscoop/sbert-base-ja](https://huggingface.co/colorfulscoop/sbert-base-ja) | Sentence-BERT | Colorful Scoop | CC BY‑SA 4.0 |
-| [MU-Kindai/SBERT-JSNLI-base](https://huggingface.co/MU-Kindai/SBERT-JSNLI-base)
[MU-Kindai/SBERT-JSNLI-large](https://huggingface.co/MU-Kindai/SBERT-JSNLI-large) | Sentence-BERT | Kindai University | ？ |
-| [MU-Kindai/Japanese-SimCSE-BERT-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-large-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-unsup)
[MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-base-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-sup)
[MU-Kindai/Japanese-SimCSE-BERT-large-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-sup) | SimCSE | Kindai University | MIT |
-| [pkshatech/simcse-ja-bert-base-clcmlp](https://huggingface.co/pkshatech/simcse-ja-bert-base-clcmlp) | SimCSE | PKSHA Technology | CC BY‑SA 4.0 |
-| [MU-Kindai/Japanese-MixCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-base)
[MU-Kindai/Japanese-MixCSE-BERT-large](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-large) | MixCSE | Kindai University | MIT |
-| [MU-Kindai/Japanese-DiffCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-DiffCSE-BERT-base) | DiffCSE | Kindai University | MIT |
-| [bclavie/fio-base-japanese-v0.1](https://huggingface.co/bclavie/fio-base-japanese-v0.1) | | 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | |
-| [cl-nagoya/shioriha-large-pt](https://huggingface.co/cl-nagoya/shioriha-large-pt) | | Nagoya University Takeda-Sasano Group | |
+| [RoSEtta](https://prtimes.jp/main/html/rd/p/000000169.000022705.html)
([pkshatech/RoSEtta-base-ja](https://huggingface.co/pkshatech/RoSEtta-base-ja)) | 1,024 | PKSHA Technology | Apache 2.0 |
+| [GLuCoSE v2](https://prtimes.jp/main/html/rd/p/000000169.000022705.html)
([pkshatech/GLuCoSE-base-ja-v2](https://huggingface.co/pkshatech/GLuCoSE-base-ja-v2)) | 512 | PKSHA Technology | Apache 2.0 |
+| [Ruri](https://arxiv.org/abs/2409.07737)
([cl-nagoya/ruri-pt-small](https://huggingface.co/cl-nagoya/ruri-pt-small), [cl-nagoya/ruri-pt-base](https://huggingface.co/cl-nagoya/ruri-pt-base), [cl-nagoya/ruri-pt-large](https://huggingface.co/cl-nagoya/ruri-pt-large), [cl-nagoya/ruri-small](https://huggingface.co/cl-nagoya/ruri-small), [cl-nagoya/ruri-base](https://huggingface.co/cl-nagoya/ruri-base), [cl-nagoya/ruri-large](https://huggingface.co/cl-nagoya/ruri-large)) | 512 | Nagoya University Sasano Group | Apache 2.0 |
+| [Japanese SimCSE](https://arxiv.org/pdf/2310.19349.pdf)
([cl-nagoya/unsup-simcse-ja-base](https://huggingface.co/cl-nagoya/unsup-simcse-ja-base), [cl-nagoya/unsup-simcse-ja-large](https://huggingface.co/cl-nagoya/unsup-simcse-ja-large), [cl-nagoya/sup-simcse-ja-base](https://huggingface.co/cl-nagoya/sup-simcse-ja-base), [cl-nagoya/sup-simcse-ja-large](https://huggingface.co/cl-nagoya/sup-simcse-ja-large)) | 512 | Nagoya University Sasano Group | CC BY-SA 4.0 |
+| [GLuCoSE](https://prtimes.jp/main/html/rd/p/000000123.000022705.html)
([pkshatech/GLuCoSE-base-ja](https://huggingface.co/pkshatech/GLuCoSE-base-ja)) | 512 | PKSHA Technology | Apache 2.0 |
+| [colorfulscoop/sbert-base-ja](https://huggingface.co/colorfulscoop/sbert-base-ja) || Colorful Scoop | CC BY‑SA 4.0 |
+| [MU-Kindai/SBERT-JSNLI-base](https://huggingface.co/MU-Kindai/SBERT-JSNLI-base)
[MU-Kindai/SBERT-JSNLI-large](https://huggingface.co/MU-Kindai/SBERT-JSNLI-large) || Kindai University | ？ |
+| [MU-Kindai/Japanese-SimCSE-BERT-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-large-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-unsup)
[MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-base-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-sup)
[MU-Kindai/Japanese-SimCSE-BERT-large-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-sup) || Kindai University | MIT |
+| [pkshatech/simcse-ja-bert-base-clcmlp](https://huggingface.co/pkshatech/simcse-ja-bert-base-clcmlp) || PKSHA Technology | CC BY‑SA 4.0 |
+| [MU-Kindai/Japanese-MixCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-base)
[MU-Kindai/Japanese-MixCSE-BERT-large](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-large) || Kindai University | MIT |
+| [MU-Kindai/Japanese-DiffCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-DiffCSE-BERT-base) || Kindai University | MIT |
+| [bclavie/fio-base-japanese-v0.1](https://huggingface.co/bclavie/fio-base-japanese-v0.1) || Individual ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | |
+| [cl-nagoya/shioriha-large-pt](https://huggingface.co/cl-nagoya/shioriha-large-pt) || Nagoya University Sasano Group | |
+
+#### Multi-representation bi-encoders
+
+| | Developer | License |
+|:---|:---:|:---:|
+| [JaColBERTv2.5](https://www.answer.ai/posts/2024-08-02-jacolbert-v25.html)
([JaColBERTv2.4](https://huggingface.co/answerdotai/JaColBERTv2.4), [JaColBERTv2.5](https://huggingface.co/answerdotai/JaColBERTv2.5)) | Answer.AI | MIT |
+| [JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)
([JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)) | Individual ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
+| [JaColBERT](https://arxiv.org/pdf/2312.16144.pdf)
([JaColBERT](https://huggingface.co/bclavie/JaColBERT)) | Individual ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
+
+### Cross-Encoders
+
+| | Developer | License |
+|:---|:---:|:---:|
+| [Ruri-Reranker](https://arxiv.org/abs/2409.07737)
([cl-nagoya/ruri-reranker-stage1-small](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-small), [cl-nagoya/ruri-reranker-stage1-base](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-base), [cl-nagoya/ruri-reranker-stage1-large](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-large), [cl-nagoya/ruri-reranker-small](https://huggingface.co/cl-nagoya/ruri-reranker-small), [cl-nagoya/ruri-reranker-base](https://huggingface.co/cl-nagoya/ruri-reranker-base), [cl-nagoya/ruri-reranker-large](https://huggingface.co/cl-nagoya/ruri-reranker-large)) | Nagoya University Sasano Group | Apache 2.0 |
+| [hotchpotch/japanese-reranker-cross-encoder-xsmall-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-xsmall-v1)
[hotchpotch/japanese-reranker-cross-encoder-small-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-small-v1)
[hotchpotch/japanese-reranker-cross-encoder-base-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-base-v1)
[hotchpotch/japanese-reranker-cross-encoder-large-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-large-v1)
[hotchpotch/japanese-bge-reranker-v2-m3-v1](https://huggingface.co/hotchpotch/japanese-bge-reranker-v2-m3-v1) | Individual (Yuichi Tateno) | MIT |
## Vision-Language Models
@@ -530,4 +548,6 @@ When referencing this repository, please cite as follows:
[^19]: Refer to the following articles: [大規模言語モデルTanuki-8B, 8x8Bの位置づけや開発指針など](https://zenn.dev/matsuolab/articles/377f7ae8b1169e), [大規模言語モデルを開発するにあたっての事前・事後学習の戦略メモー特に合成データについてー](https://zenn.dev/matsuolab/articles/34036f017fae9e)
-[^20]: Before conducting Instruction Tuning, a Chat Vector between Gemma 2 Instruct and Gemma 2 Base is added.
\ No newline at end of file
+[^20]: Before conducting Instruction Tuning, a Chat Vector between Gemma 2 Instruct and Gemma 2 Base is added.
+
+[^21]: The classification of embedding models was referenced from [Dense Text Retrieval based on Pretrained Language Models: A Survey (Zhao+, 2022)](https://arxiv.org/abs/2211.14876). The Bi-Encoder architecture inputs two separate inputs into the model and vectorizes each, using their dot product or cosine similarity as a measure of their proximity. In contrast, the Cross-Encoder architecture inputs the combined inputs into the model to directly compute their proximity internally. Although Cross-Encoders incur higher computational costs, they are often used as rerankers in information extraction due to their ability to compute input proximity more precisely. Among Bi-Encoders, there are types (e.g., ColBERT) that represent the input as multiple vectors (such as one per token) rather than a single vector, hence further classification into Single-representation bi-encoders and Multi-representation bi-encoders.
\ No newline at end of file
diff --git a/fr/README.md b/fr/README.md
index 590e76b..cb55a2f 100644
--- a/fr/README.md
+++ b/fr/README.md
@@ -263,24 +263,42 @@ N'hésitez pas à signaler les erreurs sur la page [issues](https://github.com/l
| [local-politics-BERT](http://local-politics.jp/%e5%85%ac%e9%96%8b%e7%89%a9/local-politics-bert/) | Politique | BERT (base) | Procès-verbaux de la Diète nationale, Procès-verbaux de l'Assemblée locale | Projet de Corpus des Procès-Verbaux des Assemblées Locales Japonaises | CC BY-SA 4.0 | ◯ ([SC-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-scratch), [SC-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-scratch), [SC-2M-wiki](https://huggingface.co/local-politics-jp/bert-base-japanese-wikipedia-scratch-2m), [SC-2M-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-scratch-2m), [SC-2M-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-scratch-2m), [FP-min](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-further), [FP-minwiki](https://huggingface.co/local-politics-jp/bert-base-japanese-minutes-wikipedia-further)) [^18] |
-## Plongement lexical par mots et par documents
+## Plongement lexical par mots et par documents [^21]
-| | Architecture | Développeur | Licence |
+### Bi-Encoders
+
+#### Single-representation bi-encoders
+
+| | Longueur Maximale du Contexte | Développeur | Licence |
|:---|:---:|:---:|:---:|
-| [JaColBERTv2.5](https://www.answer.ai/posts/2024-08-02-jacolbert-v25.html)
([JaColBERTv2.4](https://huggingface.co/answerdotai/JaColBERTv2.4), [JaColBERTv2.5](https://huggingface.co/answerdotai/JaColBERTv2.5)) | ColBERTv2 | Answer.AI | MIT |
-| [JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)
([JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)) | ColBERTv2 | Individuel ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
-| [JaColBERT](https://arxiv.org/pdf/2312.16144.pdf)
([JaColBERT](https://huggingface.co/bclavie/JaColBERT)) | ColBERTv2 | Individuel ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
-| [Japanese SimCSE](https://arxiv.org/pdf/2310.19349.pdf)
([cl-nagoya/unsup-simcse-ja-base](https://huggingface.co/cl-nagoya/unsup-simcse-ja-base), [cl-nagoya/unsup-simcse-ja-large](https://huggingface.co/cl-nagoya/unsup-simcse-ja-large), [cl-nagoya/sup-simcse-ja-base](https://huggingface.co/cl-nagoya/sup-simcse-ja-base), [cl-nagoya/sup-simcse-ja-large](https://huggingface.co/cl-nagoya/sup-simcse-ja-large)) | SimCSE | Université de Nagoya - Takeda-Sasano Group | CC BY-SA 4.0 |
-| [GLuCoSE](https://prtimes.jp/main/html/rd/p/000000123.000022705.html)
([pkshatech/GLuCoSE-base-ja](https://huggingface.co/pkshatech/GLuCoSE-base-ja)) | Modèle de plongement lexical basé sur LUKE
(GLuCoSE) | PKSHA Technology | Apache 2.0 |
-||||
-| [colorfulscoop/sbert-base-ja](https://huggingface.co/colorfulscoop/sbert-base-ja) | Sentence-BERT | Colorful Scoop | CC BY‑SA 4.0 |
-| [MU-Kindai/SBERT-JSNLI-base](https://huggingface.co/MU-Kindai/SBERT-JSNLI-base)
[MU-Kindai/SBERT-JSNLI-large](https://huggingface.co/MU-Kindai/SBERT-JSNLI-large) | Sentence-BERT | Université de Kindai | ？ |
-| [MU-Kindai/Japanese-SimCSE-BERT-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-large-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-unsup)
[MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-base-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-sup)
[MU-Kindai/Japanese-SimCSE-BERT-large-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-sup) | SimCSE | Université de Kindai | MIT |
-| [pkshatech/simcse-ja-bert-base-clcmlp](https://huggingface.co/pkshatech/simcse-ja-bert-base-clcmlp) | SimCSE | PKSHA Technology | CC BY‑SA 4.0 |
-| [MU-Kindai/Japanese-MixCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-base)
[MU-Kindai/Japanese-MixCSE-BERT-large](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-large) | MixCSE | Université de Kindai | MIT |
-| [MU-Kindai/Japanese-DiffCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-DiffCSE-BERT-base) | DiffCSE | Université de Kindai | MIT |
-| [bclavie/fio-base-japanese-v0.1](https://huggingface.co/bclavie/fio-base-japanese-v0.1) | | 個人 ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | |
-| [cl-nagoya/shioriha-large-pt](https://huggingface.co/cl-nagoya/shioriha-large-pt) | | Université de Nagoya - Takeda-Sasano Group | |
+| [RoSEtta](https://prtimes.jp/main/html/rd/p/000000169.000022705.html)
([pkshatech/RoSEtta-base-ja](https://huggingface.co/pkshatech/RoSEtta-base-ja)) | 1,024 | PKSHA Technology | Apache 2.0 |
+| [GLuCoSE v2](https://prtimes.jp/main/html/rd/p/000000169.000022705.html)
([pkshatech/GLuCoSE-base-ja-v2](https://huggingface.co/pkshatech/GLuCoSE-base-ja-v2)) | 512 | PKSHA Technology | Apache 2.0 |
+| [Ruri](https://arxiv.org/abs/2409.07737)
([cl-nagoya/ruri-pt-small](https://huggingface.co/cl-nagoya/ruri-pt-small), [cl-nagoya/ruri-pt-base](https://huggingface.co/cl-nagoya/ruri-pt-base), [cl-nagoya/ruri-pt-large](https://huggingface.co/cl-nagoya/ruri-pt-large), [cl-nagoya/ruri-small](https://huggingface.co/cl-nagoya/ruri-small), [cl-nagoya/ruri-base](https://huggingface.co/cl-nagoya/ruri-base), [cl-nagoya/ruri-large](https://huggingface.co/cl-nagoya/ruri-large)) | 512 | Université de Nagoya - Sasano Group | Apache 2.0 |
+| [Japanese SimCSE](https://arxiv.org/pdf/2310.19349.pdf)
([cl-nagoya/unsup-simcse-ja-base](https://huggingface.co/cl-nagoya/unsup-simcse-ja-base), [cl-nagoya/unsup-simcse-ja-large](https://huggingface.co/cl-nagoya/unsup-simcse-ja-large), [cl-nagoya/sup-simcse-ja-base](https://huggingface.co/cl-nagoya/sup-simcse-ja-base), [cl-nagoya/sup-simcse-ja-large](https://huggingface.co/cl-nagoya/sup-simcse-ja-large)) | 512 | Université de Nagoya - Sasano Group | CC BY-SA 4.0 |
+| [GLuCoSE](https://prtimes.jp/main/html/rd/p/000000123.000022705.html)
([pkshatech/GLuCoSE-base-ja](https://huggingface.co/pkshatech/GLuCoSE-base-ja)) | 512 | PKSHA Technology | Apache 2.0 |
+| [colorfulscoop/sbert-base-ja](https://huggingface.co/colorfulscoop/sbert-base-ja) || Colorful Scoop | CC BY‑SA 4.0 |
+| [MU-Kindai/SBERT-JSNLI-base](https://huggingface.co/MU-Kindai/SBERT-JSNLI-base)
[MU-Kindai/SBERT-JSNLI-large](https://huggingface.co/MU-Kindai/SBERT-JSNLI-large) || Université de Kindai | ？ |
+| [MU-Kindai/Japanese-SimCSE-BERT-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-large-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-unsup)
[MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-RoBERTa-base-unsup)
[MU-Kindai/Japanese-SimCSE-BERT-base-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-base-sup)
[MU-Kindai/Japanese-SimCSE-BERT-large-sup](https://huggingface.co/MU-Kindai/Japanese-SimCSE-BERT-large-sup) || Université de Kindai | MIT |
+| [pkshatech/simcse-ja-bert-base-clcmlp](https://huggingface.co/pkshatech/simcse-ja-bert-base-clcmlp) || PKSHA Technology | CC BY‑SA 4.0 |
+| [MU-Kindai/Japanese-MixCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-base)
[MU-Kindai/Japanese-MixCSE-BERT-large](https://huggingface.co/MU-Kindai/Japanese-MixCSE-BERT-large) || Université de Kindai | MIT |
+| [MU-Kindai/Japanese-DiffCSE-BERT-base](https://huggingface.co/MU-Kindai/Japanese-DiffCSE-BERT-base) || Université de Kindai | MIT |
+| [bclavie/fio-base-japanese-v0.1](https://huggingface.co/bclavie/fio-base-japanese-v0.1) || Individuel ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | |
+| [cl-nagoya/shioriha-large-pt](https://huggingface.co/cl-nagoya/shioriha-large-pt) || Université de Nagoya - Sasano Group | |
+
+#### Multi-representation bi-encoders
+
+| | Développeur | Licence |
+|:---|:---:|:---:|
+| [JaColBERTv2.5](https://www.answer.ai/posts/2024-08-02-jacolbert-v25.html)
([JaColBERTv2.4](https://huggingface.co/answerdotai/JaColBERTv2.4), [JaColBERTv2.5](https://huggingface.co/answerdotai/JaColBERTv2.5)) | Answer.AI | MIT |
+| [JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)
([JaColBERTv2](https://huggingface.co/bclavie/JaColBERTv2)) | Individuel ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
+| [JaColBERT](https://arxiv.org/pdf/2312.16144.pdf)
([JaColBERT](https://huggingface.co/bclavie/JaColBERT)) | Individuel ([Benjamin Clavié](https://scholar.google.com/citations?user=vuMln98AAAAJ)) | MIT |
+
+### Cross-Encoders
+
+| | Développeur | Licence |
+|:---|:---:|:---:|
+| [Ruri-Reranker](https://arxiv.org/abs/2409.07737)
([cl-nagoya/ruri-reranker-stage1-small](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-small), [cl-nagoya/ruri-reranker-stage1-base](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-base), [cl-nagoya/ruri-reranker-stage1-large](https://huggingface.co/cl-nagoya/ruri-reranker-stage1-large), [cl-nagoya/ruri-reranker-small](https://huggingface.co/cl-nagoya/ruri-reranker-small), [cl-nagoya/ruri-reranker-base](https://huggingface.co/cl-nagoya/ruri-reranker-base), [cl-nagoya/ruri-reranker-large](https://huggingface.co/cl-nagoya/ruri-reranker-large)) | Université de Nagoya - Sasano Group | Apache 2.0 |
+| [hotchpotch/japanese-reranker-cross-encoder-xsmall-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-xsmall-v1)
[hotchpotch/japanese-reranker-cross-encoder-small-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-small-v1)
[hotchpotch/japanese-reranker-cross-encoder-base-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-base-v1)
[hotchpotch/japanese-reranker-cross-encoder-large-v1](https://huggingface.co/hotchpotch/japanese-reranker-cross-encoder-large-v1)
[hotchpotch/japanese-bge-reranker-v2-m3-v1](https://huggingface.co/hotchpotch/japanese-bge-reranker-v2-m3-v1) | Individuel (Yuichi Tateno) | MIT |
## Modèles Vision-Language
@@ -531,4 +549,6 @@ Lorsque vous référencez ce répertoire, veuillez le citer comme suit:
[^19]: Référez-vous aux articles suivants: [大規模言語モデルTanuki-8B, 8x8Bの位置づけや開発指針など](https://zenn.dev/matsuolab/articles/377f7ae8b1169e), [大規模言語モデルを開発するにあたっての事前・事後学習の戦略メモー特に合成データについてー](https://zenn.dev/matsuolab/articles/34036f017fae9e)
-[^20]: Avant de procéder à l'ajustement des instructions, un vecteur de chat entre Gemma 2 Instruct et Gemma 2 Base est ajouté.
\ No newline at end of file
+[^20]: Avant de procéder à l'ajustement des instructions, un vecteur de chat entre Gemma 2 Instruct et Gemma 2 Base est ajouté.
+
+[^21]: La classification des modèles d'intégration a été référencée à partir de [Dense Text Retrieval based on Pretrained Language Models: A Survey (Zhao+, 2022)](https://arxiv.org/abs/2211.14876). L'architecture Bi-Encoder insère deux entrées distinctes dans le modèle et vectorise chacune d'elles, en utilisant leur produit scalaire ou la similarité cosinus comme mesure de leur proximité. En revanche, l'architecture Cross-Encoder insère les entrées combinées dans le modèle pour calculer directement leur proximité en interne. Bien que les Cross-Encoders entraînent des coûts de calcul plus élevés, ils sont souvent utilisés comme rerankers dans l'extraction d'informations en raison de leur capacité à calculer plus précisément la proximité des entrées. Parmi les Bi-Encoders, il existe des types (par exemple, ColBERT) qui représentent l'entrée en tant que multiples vecteurs (comme un par token) plutôt qu'un seul vecteur, d'où une classification supplémentaire en bi-encodeurs à représentation unique et bi-encodeurs à représentation multiple.
\ No newline at end of file