fix: add citations to models (#3435)

mteb/models/model_implementations/arctic_models.py

@@ -4,6 +4,26 @@
 )
 from mteb.models.sentence_transformer_wrapper import sentence_transformers_loader
 
+ARCTIC_V1_CITATION = """@article{merrick2024embedding,
+      title={Embedding And Clustering Your Data Can Improve Contrastive Pretraining},
+      author={Merrick, Luke},
+      journal={arXiv preprint arXiv:2407.18887},
+      year={2024},
+      eprint={2407.18887},
+      archivePrefix={arXiv},
+      url={https://arxiv.org/abs/2407.18887}
+}"""
+
+ARCTIC_V2_CITATION = """@article{yu2024arctic,
+      title={Arctic-Embed 2.0: Multilingual Retrieval Without Compromise},
+      author={Yu, Puxuan and Merrick, Luke and Nuti, Gaurav and Campos, Daniel},
+      journal={arXiv preprint arXiv:2412.04506},
+      year={2024},
+      eprint={2412.04506},
+      archivePrefix={arXiv},
+      url={https://arxiv.org/abs/2412.04506}
+}"""
+
 LANGUAGES_V2_0 = [
     "afr-Latn",
     "ara-Arab",
@@ -138,6 +158,7 @@
     public_training_code=None,
     public_training_data=None,
     training_datasets=arctic_v1_training_datasets,
+    citation=ARCTIC_V1_CITATION,
 )
 
 
@@ -162,6 +183,7 @@
     public_training_code=None,
     public_training_data=None,  # couldn't find
     training_datasets=arctic_v1_training_datasets,
+    citation=ARCTIC_V1_CITATION,
 )
 
 
@@ -186,6 +208,7 @@
     public_training_code=None,
     public_training_data=None,  # couldn't find
     training_datasets=arctic_v1_training_datasets,
+    citation=ARCTIC_V1_CITATION,
 )
 
 arctic_embed_m_long = ModelMeta(
@@ -210,6 +233,7 @@
     public_training_code=None,
     public_training_data=None,  # couldn't find
     training_datasets=arctic_v1_training_datasets,
+    citation=ARCTIC_V1_CITATION,
 )
 
 arctic_embed_l = ModelMeta(
@@ -233,6 +257,7 @@
     public_training_code=None,
     public_training_data=None,  # couldn't find
     training_datasets=arctic_v1_training_datasets,
+    citation=ARCTIC_V1_CITATION,
 )
 
 arctic_embed_m_v1_5 = ModelMeta(
@@ -261,6 +286,7 @@
     public_training_code=None,
     public_training_data=None,
     training_datasets=arctic_v1_training_datasets,
+    citation=ARCTIC_V1_CITATION,
 )
 
 arctic_embed_m_v2_0 = ModelMeta(
@@ -285,6 +311,7 @@
     public_training_code=None,
     public_training_data=None,  # couldn't find
     training_datasets=arctic_v2_training_datasets,
+    citation=ARCTIC_V2_CITATION,
 )
 
 arctic_embed_l_v2_0 = ModelMeta(
@@ -308,4 +335,5 @@
     public_training_code=None,
     public_training_data=None,  # couldn't find
     training_datasets=arctic_v2_training_datasets,
+    citation=ARCTIC_V2_CITATION,
 )

mteb/models/model_implementations/b1ade_models.py

@@ -33,4 +33,13 @@
     # BAAI/bge-large-en-v1.5
     # mixedbread-ai/mxbai-embed-large-v1
     # avsolatorio/GIST-large-Embedding-v0
+    citation="""
+    @misc{bigscience_workshop_2022,
+    author       = { {Shreyas Subramanian} },
+    title        = { {b1ade series of models} },
+    year         = 2024,
+    url          = { https://huggingface.co/w601sxs/b1ade-embed },
+    publisher    = { Hugging Face }
+}
+""",
 )

mteb/models/model_implementations/bge_models.py

@@ -748,6 +748,17 @@
     public_training_data="https://huggingface.co/datasets/cfli/bge-full-data",
     training_datasets=E5_MISTRAL_TRAINING_DATA | bge_full_data,
     adapted_from="intfloat/e5-mistral-7b-instruct",
+    citation="""
+    @misc{li2024makingtextembeddersfewshot,
+      title={Making Text Embedders Few-Shot Learners},
+      author={Chaofan Li and MingHao Qin and Shitao Xiao and Jianlyu Chen and Kun Luo and Yingxia Shao and Defu Lian and Zheng Liu},
+      year={2024},
+      eprint={2409.15700},
+      archivePrefix={arXiv},
+      primaryClass={cs.IR},
+      url={https://arxiv.org/abs/2409.15700},
+}
+""",
 )
 
 bge_m3_unsupervised = ModelMeta(

mteb/models/model_implementations/e5_v.py

@@ -14,6 +14,16 @@
     "4.44.2"  # Issue 1647: Only works with transformers==4.44.2.
 )
 
+E5_V_CITATION = """@article{jiang2024e5v,
+      title={E5-V: Universal Embeddings with Multimodal Large Language Models},
+      author={Jiang, Ting and Song, Minghui and Zhang, Zihan and Huang, Haizhen and Deng, Weiwei and Sun, Feng and Zhang, Qi and Wang, Deqing and Zhuang, Fuzhen},
+      journal={arXiv preprint arXiv:2407.12580},
+      year={2024},
+      eprint={2407.12580},
+      archivePrefix={arXiv},
+      url={https://arxiv.org/abs/2407.12580}
+}"""
+
 
 class E5VModel(AbsEncoder):
     def __init__(
@@ -169,4 +179,5 @@ def encode(
     training_datasets=set(
         # princeton-nlp/datasets-for-simcse
     ),
+    citation=E5_V_CITATION,
 )

mteb/models/model_implementations/evaclip_models.py

@@ -11,6 +11,13 @@
 from mteb.models.model_meta import ModelMeta, ScoringFunction
 from mteb.types import Array, BatchedInput, PromptType
 
+EVA_CLIP_CITATION = """@article{EVA-CLIP,
+      title={EVA-CLIP: Improved Training Techniques for CLIP at Scale},
+      author={Sun, Quan and Fang, Yuxin and Wu, Ledell and Wang, Xinlong and Cao, Yue},
+      journal={arXiv preprint arXiv:2303.15389},
+      year={2023}
+}"""
+
 
 def evaclip_loader(model_name, **kwargs):
     try:
@@ -148,6 +155,7 @@ def encode(
     similarity_fn_name=ScoringFunction.COSINE,
     use_instructions=False,
     training_datasets=training_datasets,
+    citation=EVA_CLIP_CITATION,
 )
 
 EVA02_CLIP_L_14 = ModelMeta(
@@ -170,6 +178,7 @@ def encode(
     similarity_fn_name=ScoringFunction.COSINE,
     use_instructions=False,
     training_datasets=training_datasets,
+    citation=EVA_CLIP_CITATION,
 )
 
 EVA02_CLIP_bigE_14 = ModelMeta(
@@ -192,6 +201,7 @@ def encode(
     similarity_fn_name=ScoringFunction.COSINE,
     use_instructions=False,
     training_datasets=laion_2b,
+    citation=EVA_CLIP_CITATION,
 )
 
 
@@ -215,4 +225,5 @@ def encode(
     similarity_fn_name=ScoringFunction.COSINE,
     use_instructions=False,
     training_datasets=laion_2b,
+    citation=EVA_CLIP_CITATION,
 )

mteb/models/model_implementations/fa_models.py

@@ -27,6 +27,15 @@
         # Persian Wikipedia
         # Other data crawled from websites like bigbangpage.com, chetor.com, eligasht.com/blog, digikala.com/mag, and ted.com/talks.
     ),
+    citation="""
+    @article{ParsBERT,
+    title={ParsBERT: Transformer-based Model for Persian Language Understanding},
+    author={Mehrdad Farahani, Mohammad Gharachorloo, Marzieh Farahani, Mohammad Manthouri},
+    journal={ArXiv},
+    year={2020},
+    volume={abs/2005.12515}
+}
+""",
 )
 
 bert_zwnj = ModelMeta(

mteb/models/model_implementations/gme_v_models.py

@@ -14,6 +14,16 @@
 
 logger = logging.getLogger(__name__)
 
+GME_CITATION = """@misc{zhang2024gme,
+      title={GME: Improving Universal Multimodal Retrieval by Multimodal LLMs},
+      author={Zhang, Xin and Zhang, Yanzhao and Xie, Wen and Li, Mingxin and Dai, Ziqi and Long, Dingkun and Xie, Pengjun and Zhang, Meishan and Li, Wenjie and Zhang, Min},
+      year={2024},
+      eprint={2412.16855},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={http://arxiv.org/abs/2412.16855}
+}"""
+
 
 class Encoder(torch.nn.Module):
     def __init__(
@@ -349,6 +359,7 @@ def fetch_image(
     public_training_code=None,
     public_training_data=None,
     training_datasets=training_data,
+    citation=GME_CITATION,
 )
 
 gme_qwen2vl_7b = ModelMeta(
@@ -371,4 +382,5 @@ def fetch_image(
     public_training_code=None,
     public_training_data=None,
     training_datasets=training_data,
+    citation=GME_CITATION,
 )

mteb/models/model_implementations/mcinext_models.py

@@ -12,6 +12,13 @@
 
 logger = logging.getLogger(__name__)
 
+HAKIM_CITATION = """@article{sarmadi2025hakim,
+      title={Hakim: Farsi Text Embedding Model},
+      author={Sarmadi, Mehran and Alikhani, Morteza and Zinvandi, Erfan and Pourbahman, Zahra},
+      journal={arXiv preprint arXiv:2505.08435},
+      year={2025}
+}"""
+
 MODEL_API_NAMES = {
     "hakim": "Hakim",
     "hakim-small": "Hakim_small",
@@ -396,6 +403,7 @@ def encode(
         "SynPerSTS",
         "Query2Query",
     },
+    citation=HAKIM_CITATION,
 )
 
 
@@ -462,6 +470,7 @@ def encode(
         "SynPerSTS",
         "Query2Query",
     },
+    citation=HAKIM_CITATION,
 )
 
 hakim_unsup = ModelMeta(
@@ -491,4 +500,5 @@ def encode(
         "MSMARCO-Fa",
         "Query2Query",
     },
+    citation=HAKIM_CITATION,
 )

mteb/models/model_implementations/model2vec_models.py

@@ -14,6 +14,13 @@
 
 logger = logging.getLogger(__name__)
 
+MODEL2VEC_CITATION = """@software{minishlab2024model2vec,
+      authors = {Stephan Tulkens, Thomas van Dongen},
+      title = {Model2Vec: Turn any Sentence Transformer into a Small Fast Model},
+      year = {2024},
+      url = {https://github.com/MinishLab/model2vec}
+}"""
+
 _POTION_MULTILINGUAL_128M_LANGUAGES = [
     "afr-Latn",
     "amh-Ethi",
@@ -172,6 +179,7 @@ def encode(
     training_datasets=bge_training_data,  # distilled
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 
@@ -196,6 +204,7 @@ def encode(
     training_datasets=bge_training_data,  # distilled
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 m2v_base_output = ModelMeta(
@@ -219,6 +228,7 @@ def encode(
     training_datasets=bge_training_data,  # distilled
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 m2v_multilingual_output = ModelMeta(
@@ -242,6 +252,7 @@ def encode(
     training_datasets=None,
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 potion_base_2m = ModelMeta(
@@ -265,6 +276,7 @@ def encode(
     training_datasets=bge_training_data,  # distilled
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 potion_base_4m = ModelMeta(
@@ -288,6 +300,7 @@ def encode(
     training_datasets=bge_training_data,  # distilled
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 potion_base_8m = ModelMeta(
@@ -311,6 +324,7 @@ def encode(
     training_datasets=bge_training_data,  # distilled
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 potion_multilingual_128m = ModelMeta(
@@ -334,6 +348,7 @@ def encode(
     training_datasets=bge_training_data,  # distilled
     public_training_code="https://github.com/MinishLab/model2vec",
     public_training_data=None,
+    citation=MODEL2VEC_CITATION,
 )
 
 pubmed_bert_100k = ModelMeta(

mteb/models/model_implementations/nomic_models_vision.py

@@ -12,6 +12,16 @@
 from mteb.models.model_meta import ModelMeta, ScoringFunction
 from mteb.types import Array, BatchedInput, PromptType
 
+NOMIC_EMBED_VISION_CITATION = """@article{nussbaum2024nomicembedvision,
+      title={Nomic Embed Vision: Expanding the Latent Space},
+      author={Nussbaum, Zach and Duderstadt, Brandon and Mulyar, Andriy},
+      journal={arXiv preprint arXiv:2406.18587},
+      year={2024},
+      eprint={2406.18587},
+      archivePrefix={arXiv},
+      url={https://arxiv.org/abs/2406.18587}
+}"""
+
 
 class NomicVisionModel(AbsEncoder):
     def __init__(
@@ -174,4 +184,5 @@ def encode(
         # https://arxiv.org/pdf/2406.18587
         # DFN-2B
     ),
+    citation=NOMIC_EMBED_VISION_CITATION,
 )