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Paper Citation Record · LEDGER

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese

As of 10 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 1 inbound Pith citation observation for arXiv:2607.04581.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.04581 v2

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-11T16:55:28.735209Z

measured 69 of 69 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T08:45:15.934455Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

68 of 68 outbound references displayed

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  • unresolved67
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  • malformed identifier1
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 5087861e-ee3f-4143-9592-9a378cecd8ff · outbound

This paper cites MTEB: Massive text embedding benchmark,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese MTEB: Massive text embedding benchmark,

Reference 1

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:80e3cfd11382763701a9e95247534b95f17c3b15141b2bfd7d5df5567c7c3e9d

Observation 549fea7f-0848-4ea9-9e16-9368d9a63461 · outbound

This paper cites MMTEB: Massive multilingual text embedding benchmark,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese MMTEB: Massive multilingual text embedding benchmark,

Reference 2

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Observation 511266d5-b996-4e6e-a5ad-51b903d043ee · outbound

This paper cites mMARCO: A multilingual version of the MS MARCO passage ranking dataset,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese mMARCO: A multilingual version of the MS MARCO passage ranking dataset,

Reference 3

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Observation 4a91a814-7a7e-4f6b-b5f2-cb945f5d9d97 · outbound

This paper cites VN-MTEB: Vietnamese massive text embedding benchmark,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese VN-MTEB: Vietnamese massive text embedding benchmark,

Reference 4

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Observation 852bf0d4-2725-4372-86ad-a8fd427261e4 · outbound

This paper cites C-Pack: Packed Resources For General Chinese Embeddings.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese C-Pack: Packed Resources For General Chinese Embeddings

Reference 5

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Observation bb96ff81-99d1-4698-8ed2-456af1b61d4d · outbound

This paper cites The Scandinavian embedding benchmarks: Comprehensive assessment of multilingual and monolingual text embedding,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese The Scandinavian embedding benchmarks: Comprehensive assessment of multilingual and monolingual text embedding,

Reference 6

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Observation 28bf6485-a146-4565-b48f-09e5ce94bc7e · outbound

This paper cites MTEB-French: Resources for French sentence embedding evaluation and analysis,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese MTEB-French: Resources for French sentence embedding evaluation and analysis,

Reference 7

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Observation e6ffbe54-362c-4d23-a08b-b6c1e8d7ce35 · outbound

This paper cites PL-MTEB: Polish massive text embedding benchmark,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese PL-MTEB: Polish massive text embedding benchmark,

Reference 8

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Observation ab6b2e1e-9120-4f8e-ba89-66c7ddc446a4 · outbound

This paper cites The Russian-focused embedders’ exploration: ruMTEB benchmark and Russian embedding model design,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese The Russian-focused embedders’ exploration: ruMTEB benchmark and Russian embedding model design,

Reference 9

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Observation 56aba30d-a676-4d43-9e50-5e0a390cf45d · outbound

This paper cites FaMTEB: Massive text embedding benchmark in Persian language,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese FaMTEB: Massive text embedding benchmark in Persian language,

Reference 10

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Observation 3cc2bdf9-1fe7-48ac-bfaf-0b37817dcf45 · outbound

This paper cites MTEB-NL and E5-NL: Embedding benchmark and models for Dutch,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese MTEB-NL and E5-NL: Embedding benchmark and models for Dutch,

Reference 11

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Observation d69565a0-6fdf-4986-82cd-8fbb82de04d5 · outbound

This paper cites German text embedding clustering benchmark,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese German text embedding clustering benchmark,

Reference 12

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Observation 4963b912-af4f-4756-9e1f-cb2a0c33abd6 · outbound

This paper cites Ruri: Japanese general text embeddings,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Ruri: Japanese general text embeddings,

Reference 13

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Observation 960809f1-3d15-422a-9089-25f00eb52330 · outbound

This paper cites SentEval: An evaluation toolkit for universal sentence representations,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese SentEval: An evaluation toolkit for universal sentence representations,

Reference 14

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:ea78970aa2768d97791e5c2268f01188fe734cbc173984191a479c61aa89c071

Observation 7ef566a4-6342-4c03-b220-d15cac7bc318 · outbound

This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 15

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Observation 5b4067c1-a25d-4013-a44c-e7ac93294f1d · outbound

This paper cites MIRACL: A multilingual retrieval dataset covering 18 diverse languages,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese MIRACL: A multilingual retrieval dataset covering 18 diverse languages,

Reference 16

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Observation 49261ee1-1523-4624-863c-a08c15686990 · outbound

This paper cites Available: https://aclanthology.org/2023.tacl-1.63/.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Available: https://aclanthology.org/2023.tacl-1.63/

Reference 17

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:203974ce485cae8556aebf1f15e3d88c58a8dcbb23ce08b9acb055340a38ed98

Observation 3b1984ea-e788-4603-8969-893d61442633 · outbound

This paper cites BEIR-PL: Zero shot information retrieval benchmark for the Polish language,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese BEIR-PL: Zero shot information retrieval benchmark for the Polish language,

Reference 18

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Observation b8e728a2-8693-4b97-baeb-58153efac145 · outbound

This paper cites Napolab: The natural portuguese language bench- mark,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Napolab: The natural portuguese language bench- mark,

Reference 19

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Observation e4bfe681-7900-4f52-9bd9-9c741e62d4ac · outbound

This paper cites PORTULAN ExtraGLUE datasets and models: Kick-starting a benchmark for the neural processing of Portuguese,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese PORTULAN ExtraGLUE datasets and models: Kick-starting a benchmark for the neural processing of Portuguese,

Reference 20

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Observation 2076e809-4623-4e02-8ec4-002ff42f58fe · outbound

This paper cites Beyond multilingual averages: MTEB-PT, a benchmark for Portuguese sentence encoders,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Beyond multilingual averages: MTEB-PT, a benchmark for Portuguese sentence encoders,

Reference 21

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:e1bf26665c8b338964c79cceedc09cc36e7f786604f53c9a69c335bd3e64bbfa

Observation cb8b8d6a-f411-42ce-a4c1-ced1fa29d697 · outbound

This paper cites HateBR: A large expert annotated corpus of Brazilian Instagram comments for offensive language and hate speech detection,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese HateBR: A large expert annotated corpus of Brazilian Instagram comments for offensive language and hate speech detection,

Reference 22

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:fac0415c0a3927d53b64134698e2ea755ffe6ad5aa901d62579057157cc56c77

Observation 2b274027-c1e0-4b84-93f4-93523326d4ae · outbound

This paper cites FACTCK.BR: a new dataset to study fake news,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese FACTCK.BR: a new dataset to study fake news,

Reference 23

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:6f542f4f120e9cf417fc561be7836cea3b2cd359a6416acb4445406f25d44df3

Observation cd39f9c8-6edf-40b9-8c93-88bbebaec2f1 · outbound

This paper cites ToxSyn-PT: A synthetic fine-grained dataset of minority- targeted toxic language in Portuguese,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese ToxSyn-PT: A synthetic fine-grained dataset of minority- targeted toxic language in Portuguese,

Reference 24

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Observation 98b0e1dc-cc9f-4d6b-87ec-bdd22829ac16 · outbound

This paper cites Vis˜ao Geral da Avaliac ¸˜ao de Similaridade Sem ˆantica e Infer ˆencia Textual,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Vis˜ao Geral da Avaliac ¸˜ao de Similaridade Sem ˆantica e Infer ˆencia Textual,

Reference 25

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:64147b40cc61df0b96bc0b9de6abb349882b7c17ef4420c895c3d48c48d6e18a

Observation ba7d6e8a-efc7-4dda-8a27-2d350ffcf7af · outbound

This paper cites InferBR: A natural language inference dataset in Portuguese,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese InferBR: A natural language inference dataset in Portuguese,

Reference 26

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:bf52746db54629eceae9bc4cec50245f26586fe412180ab1801a96f2b5bbe19e

Observation 5f23f83e-ffeb-4035-9bdb-c292612f4d63 · outbound

This paper cites The ASSIN 2 shared task: A quick overview,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese The ASSIN 2 shared task: A quick overview,

Reference 27

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:39b38c7ad06b31fabc83a4f733b6f068b4055c3b7803e73806ef1d90b5f7f428

Observation 9c0ccc5f-de0a-46f6-b619-de753735574d · outbound

This paper cites MedPT: A massive medical question answering dataset for Brazilian-Portuguese speakers,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese MedPT: A massive medical question answering dataset for Brazilian-Portuguese speakers,

Reference 28

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:320beeb3e435daea122bdbd6b84c90fcdd3bf98535a02e4830e86709720b1347

Observation ebfaa18e-3034-4c1b-a1a3-a79e49e88cd1 · outbound

This paper cites Brazilian Portuguese Wikipedia categories clustering dataset,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Brazilian Portuguese Wikipedia categories clustering dataset,

Reference 29

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:c16af6711a1efce647cdbbd49a34870f00c9bb02ef9d34fa7a362355c0a4f019

Observation a1bc8c0d-fdb0-41c8-930a-db497cb76a46 · outbound

This paper cites JurisTCU: A Brazilian Portuguese Information Retrieval Dataset with Query Relevance Judgments.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese JurisTCU: A Brazilian Portuguese Information Retrieval Dataset with Query Relevance Judgments

Reference 30

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Observation 3e4018fc-85b0-4ef9-a8cd-69e90461d0d6 · outbound

This paper cites SciELO Brazil scientific abstracts clustering dataset,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese SciELO Brazil scientific abstracts clustering dataset,

Reference 31

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:b8ead0c61cafd36acfcfbf37f44c705bc371695b4119d18844450da82a08ebec

Observation 0f795c78-b94e-465c-bc6d-29e9b39c6cdd · outbound

This paper cites Portuguese Stack Overflow clustering dataset,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Portuguese Stack Overflow clustering dataset,

Reference 32

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Observation 6ba9489c-58dd-4139-8fa4-e31d37749cb8 · outbound

This paper cites FaQuAD: Reading comprehension dataset in the domain of Brazilian higher education,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese FaQuAD: Reading comprehension dataset in the domain of Brazilian higher education,

Reference 33

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:f62a1ef3f0d05bef379f9025f2091a2a7f37f0361abeeae0494fef1295ef5ad4

Observation 5021fe95-06e6-4820-9a5c-511ba4db4f2a · outbound

This paper cites Quati: A Brazilian Portuguese information retrieval dataset from native speakers,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Quati: A Brazilian Portuguese information retrieval dataset from native speakers,

Reference 34

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Observation e7f10294-be7a-4801-b91c-6777179e13a6 · outbound

This paper cites FaqBacen: Banco central do brasil public FAQ retrieval dataset,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese FaqBacen: Banco central do brasil public FAQ retrieval dataset,

Reference 35

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Observation 8865b975-43f8-44d3-866a-3991a1fc2427 · outbound

This paper cites BR-TaxQA-R: A dataset for question answering with references for Brazilian personal income tax law, including case law,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese BR-TaxQA-R: A dataset for question answering with references for Brazilian personal income tax law, including case law,

Reference 36

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Observation 08cecd67-3e21-4932-8930-b0d4549e3aea · outbound

This paper cites RoBERTaLexPT: A legal RoBERTa model pretrained with deduplication for Portuguese,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese RoBERTaLexPT: A legal RoBERTa model pretrained with deduplication for Portuguese,

Reference 37

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Observation c6c47d65-36df-49e9-b2d1-633fc94ed98d · outbound

This paper cites BRIGHTER: BRIdging the gap in human-annotated textual emotion recognition datasets for 28 languages,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese BRIGHTER: BRIdging the gap in human-annotated textual emotion recognition datasets for 28 languages,

Reference 38

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Observation 0c6af2dc-8806-4710-9713-a3c1914d57fb · outbound

This paper cites Qwen3 embedding: Advancing text embedding and reranking through foundation models,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Qwen3 embedding: Advancing text embedding and reranking through foundation models,

Reference 39

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Observation 61de10b0-cd62-40a1-9a29-72de4460f333 · outbound

This paper cites Octen-embedding model family,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Octen-embedding model family,

Reference 40

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Observation b0d83301-ff9b-4ce4-9b3c-0cf73daecd40 · outbound

This paper cites F2LLM-v2: Inclusive, performant, and efficient embeddings for a multilingual world,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese F2LLM-v2: Inclusive, performant, and efficient embeddings for a multilingual world,

Reference 41

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Observation 146cfd9f-4141-4d3e-9bac-2295fd859ca1 · outbound

This paper cites Harrier-OSS-v1 embedding family,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Harrier-OSS-v1 embedding family,

Reference 42

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:1a94b090987d5ea77d5b69c76184c8c2c0a65daf6e689114c93ab21aec87a326

Observation 9c7aa73c-e96a-43a2-9fc3-9b7ad1d2c12a · outbound

This paper cites SFR-embedding-mistral: Enhance text retrieval with transfer learning,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese SFR-embedding-mistral: Enhance text retrieval with transfer learning,

Reference 43

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Observation 4e67795c-3b6d-4f86-b900-51a607ff7a78 · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 44

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Observation 1629db09-a9d8-4e37-b426-a6a2d23f2422 · outbound

This paper cites Linq-Embed-Mistral technical report,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Linq-Embed-Mistral technical report,

Reference 45

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:2a9864b5d010e334597af5714a62fcec763fefbc5236ad916b8565172dfd57be

Observation d778ad52-eb46-4951-b3da-913b24ac4016 · outbound

This paper cites KaLM-Embedding-V2: Superior training techniques and data inspire a versatile embedding model,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese KaLM-Embedding-V2: Superior training techniques and data inspire a versatile embedding model,

Reference 46

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Observation ddbf0886-9ee5-4f59-b6ae-74300e561c0d · outbound

This paper cites Llama-Embed-Nemotron-8B: A universal text embedding model for multilingual and cross-lingual tasks,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Llama-Embed-Nemotron-8B: A universal text embedding model for multilingual and cross-lingual tasks,

Reference 47

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:8f183a2a2953cd1a8a0afc54686b8a84018a4fe871ad07fe0da751b493cc561b

Observation 98be4b82-70fa-4620-b6ee-968eb5acbb1b · outbound

This paper cites BidirLM: From text to omnimodal bidirectional encoders by adapting and composing causal LLMs,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese BidirLM: From text to omnimodal bidirectional encoders by adapting and composing causal LLMs,

Reference 48

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:a73bf562b4b5170e46e94aecd6d7ee65d86319f7703b90f920a2ac4032d6fee8

Observation 1c25690a-918b-4883-8b9f-dd57390dbdf5 · outbound

This paper cites jua: Domain-adaptive dense retrieval embeddings for Brazilian legal search,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese jua: Domain-adaptive dense retrieval embeddings for Brazilian legal search,

Reference 49

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:2f144094ad4fa880408a01c5b05fd0ce36059e7817fdefd0472a52b51dd80c63

Observation 7809d949-cb21-462b-af77-86a408f5a8f7 · outbound

This paper cites Multilingual E5 text embeddings: A technical report,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Multilingual E5 text embeddings: A technical report,

Reference 50

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:a7d5c1ae55f236975ce77fd3a66ec770151319bac93b241c016d66c3dc417b92

Observation bcf911d4-75ef-4c29-96fa-c6b3fbd88a9d · outbound

This paper cites Sentence-BERT: Sentence embeddings using Siamese BERT-networks,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Sentence-BERT: Sentence embeddings using Siamese BERT-networks,

Reference 51

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:20cbc2194137132db6b728dff9584ebc4233b7238d87b766cea645d970e7dce1

Observation ff6e06ee-10f1-476e-bd86-2f9a31d29295 · outbound

This paper cites Granite embedding multilingual R2 models,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Granite embedding multilingual R2 models,

Reference 52

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:29eb635b386920f7e25b6257c6091aec524f5c51b2a70466f8afa3be8670f946

Observation 9765ec5e-23d3-4042-8b50-d59d302dcba9 · outbound

This paper cites jina-embeddings-v5-text: Task-targeted embed- ding distillation,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese jina-embeddings-v5-text: Task-targeted embed- ding distillation,

Reference 53

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:4e87c58d890a206ddad4fef288173e915f3be3a498facf4bc4b0baca3578b911

Observation 6ae1b587-e4cd-44cd-96c7-3f9d78811163 · outbound

This paper cites M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge distillation,

Reference 54

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:626bbcbfacc5c9cf5d591ce56797f65265b77a94f105c9bd8421d0960c0a078b

Observation ffb0edc9-42ae-4045-94ef-e1700c492444 · outbound

This paper cites Arctic-embed 2.0: Multi- lingual retrieval without compromise,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Arctic-embed 2.0: Multi- lingual retrieval without compromise,

Reference 55

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:1feafb614b33e4ebdcfa7fa164e1f14c055bfacdf63cff35fd736727d3bc4e30

Observation abeb1e78-4458-4907-a278-2bc4f97c4b47 · outbound

This paper cites Open Sentence Embeddings for Portuguese with the Serafim PT* encoders family.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Open Sentence Embeddings for Portuguese with the Serafim PT* encoders family

Reference 56

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Observation 22c41d77-40c8-40ae-b8f3-8f2ba21a4a9f · outbound

This paper cites Fostering the ecosystem of open neural encoders for Portuguese with Albertina PT* family,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Fostering the ecosystem of open neural encoders for Portuguese with Albertina PT* family,

Reference 57

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Observation 62e460e6-b3ac-4258-84db-a55371d83033 · outbound

This paper cites BERTimbau: Pretrained BERT models for Brazilian Portuguese,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese BERTimbau: Pretrained BERT models for Brazilian Portuguese,

Reference 58

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:d21c2fe48c5846aae0e8d3e816d63dbbc2c1a5024ac31320c509a0edac4bfa10

Observation 8e231ee4-f138-4559-acb5-ff120ea4b613 · outbound

This paper cites A semantic search system for the Supremo Tribunal de Justic ¸a,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese A semantic search system for the Supremo Tribunal de Justic ¸a,

Reference 59

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Observation cce035fa-6466-43d1-8648-9d3031a98057 · outbound

This paper cites Language- agnostic BERT sentence embedding,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Language- agnostic BERT sentence embedding,

Reference 60

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:5585171282bcdd5723e85c371a784ca8e8eb46b0377a501f5ec6b155b5cc9cf2

Observation 4cc83b6c-82aa-43ff-89eb-5cef6af73f72 · outbound

This paper cites EmbeddingGemma: Powerful and lightweight text representations,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese EmbeddingGemma: Powerful and lightweight text representations,

Reference 61

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:241bc0bf5ab75bce4f727293eb1dcdd1d03e5f37097e302918c6961436f2339c

Observation 04ffcbb8-b8ed-46f4-bf3b-52615c9ff237 · outbound

This paper cites PIXIE-rune-v1.0,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese PIXIE-rune-v1.0,

Reference 62

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Observation ffe9e9e0-6d48-46be-9a79-8b1c613fabd2 · outbound

This paper cites PwC-embedding expr,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese PwC-embedding expr,

Reference 63

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Observation 5f4535cd-0037-4d6a-80f3-b29b51caf2ae · outbound

This paper cites What are the best systems? New perspectives on NLP Benchmarking.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese What are the best systems? New perspectives on NLP Benchmarking

Reference 64

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Observation aa7c11af-d329-4c9c-a1d7-4218f3a45320 · outbound

This paper cites an unresolved cited work.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Unresolved cited work

Reference 65

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Observation 634a025e-76df-4e32-980a-8c57d775da13 · outbound

This paper cites Building an evaluation scale using item response theory,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Building an evaluation scale using item response theory,

Reference 66

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:ebecfb45d906bf30a4e3746f47580a9b8ec9ec8a1c47dad3d32336420c641b23

Observation be3a9d01-efb5-4cbf-93f2-dc35f1c91451 · outbound

This paper cites tinyBenchmarks: evaluating LLMs with fewer examples,.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese tinyBenchmarks: evaluating LLMs with fewer examples,

Reference 67

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Observation 1f397c67-1702-437b-afb1-f8bd1c229425 · outbound

This paper cites Evaluation examples are not equally informative: How should that change NLP leaderboards?.

MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese Evaluation examples are not equally informative: How should that change NLP leaderboards?

Reference 68

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source=pdf_text observed=2026-07-11T16:55:28.735209Z digest=sha256:72228dc20ac502d2da8fe1cc620b0669661b83f39fcb72f1dd51e2f338b2f0d3

Pith citing papers

Observation 3937775a-dfcf-479b-8141-8ee1ed42ec0f · inbound

Beyond Multilingual Averages: MTEB-PT, a Benchmark for Portuguese Sentence Encoders cites this paper.

Beyond Multilingual Averages: MTEB-PT, a Benchmark for Portuguese Sentence Encoders MTEB-BR: A Text Embedding Benchmark for Brazilian Portuguese

Reference 18

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source=pdf_text observed=2026-08-02T08:45:15.934455Z digest=sha256:d606082304ffa88cfe02746f15d067f8a80defe542ee8ed7de4ff4e947eacab7