BitNet Text Embeddings | Paper Citation Record

Observation 68cccac2-828a-41d9-9cbb-5e679b00d5f4 · outbound

This paper cites Semeval-2012 task 6: A pilot on semantic textual similarity.

BitNet Text Embeddings Semeval-2012 task 6: A pilot on semantic textual similarity

Reference 1

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Observation 548d6f02-c42f-4d39-ba9d-944f80fee9b7 · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

BitNet Text Embeddings Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 2

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Observation 1c77f84c-4863-4e3e-9083-ea3c82a85279 · outbound

This paper cites Revela: Dense retriever learning via language modeling.

BitNet Text Embeddings Revela: Dense retriever learning via language modeling

Reference 3

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Observation 99ec687a-81ff-4a9b-821d-66d28c73272b · outbound

This paper cites Efficient Intent Detection with Dual Sentence Encoders.

BitNet Text Embeddings Efficient Intent Detection with Dual Sentence Encoders

Reference 4

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Observation 427a91f3-6204-4c65-8ea3-6aa342978bf0 · outbound

This paper cites Quartet: Native fp4 training can be optimal for large language models.Advances in Neural Information Processing Systems, 38:43552–43572, 2026.

BitNet Text Embeddings Quartet: Native fp4 training can be optimal for large language models.Advances in Neural Information Processing Systems, 38:43552–43572, 2026

Reference 5

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Observation 4876d1da-16e1-4f1b-bfa3-231c4658adb9 · outbound

This paper cites SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation.

BitNet Text Embeddings SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

Reference 6

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Observation 16d2eaba-d87f-455c-bd89-630682d09c58 · outbound

This paper cites Open-domain question answering.

BitNet Text Embeddings Open-domain question answering

Reference 7

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Observation 0fbec2ce-2d69-49f9-b37a-a2930f253af0 · outbound

This paper cites mme5: Improving multimodal multilingual embeddings via high-quality synthetic data.

BitNet Text Embeddings mme5: Improving multimodal multilingual embeddings via high-quality synthetic data

Reference 8

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Observation 0b4e4b86-6573-450b-9ecf-96f2bc4bb8ab · outbound

This paper cites Efficientqat: Efficient quantization-aware training for large language models.

BitNet Text Embeddings Efficientqat: Efficient quantization-aware training for large language models

Reference 9

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Observation 7989b89e-db36-4c26-b389-13b08b2ff65d · outbound

This paper cites Semeval-2022 task 8: Multilingual news article similarity.

BitNet Text Embeddings Semeval-2022 task 8: Multilingual news article similarity

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.702386Z

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Observation 80ff849d-c4f5-4a32-a997-9495e93f8712 · outbound

This paper cites Linq-Embed-Mistral Technical Report.

BitNet Text Embeddings Linq-Embed-Mistral Technical Report

Reference 11

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Observation 9df2b6dd-078a-4ce5-9284-887c757c0a57 · outbound

This paper cites SPECTER: Document-level Representation Learning using Citation-informed Transformers.

BitNet Text Embeddings SPECTER: Document-level Representation Learning using Citation-informed Transformers

Reference 12

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Observation 583e13f7-b308-4b9a-af4f-ea677e37fec0 · outbound

This paper cites Quora question pairs.https://kaggle.com/competitions/quora-question-pairs, 2017.

BitNet Text Embeddings Quora question pairs.https://kaggle.com/competitions/quora-question-pairs, 2017

Reference 13

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Observation a9fb71f6-1f66-4864-8924-904ab7e7e504 · outbound

This paper cites an unresolved cited work.

BitNet Text Embeddings Unresolved cited work

Reference 14

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Observation 31d7998c-8849-4fce-b6b2-45a0d25751f9 · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.

BitNet Text Embeddings BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 15

Resolution: malformed identifier; doi_truncated, observed 2026-08-02T10:19:32.259436Z

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Observation 34fa1e2d-743c-48eb-9058-7e73845bb444 · outbound

This paper cites Bitdistiller: Unleashing the potential of sub-4-bit llms via self-distillation.

BitNet Text Embeddings Bitdistiller: Unleashing the potential of sub-4-bit llms via self-distillation

Reference 16

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Observation 29bbf45e-2e69-479a-803e-038fea64543f · outbound

This paper cites Mmteb: Massive multilingual text embedding benchmark.arXiv preprint arXiv:2502.13595, 2025.

BitNet Text Embeddings Mmteb: Massive multilingual text embedding benchmark.arXiv preprint arXiv:2502.13595, 2025

Reference 17

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Observation b8b70091-10ae-4c00-ae30-5dadac2aeefe · outbound

This paper cites ELI5: Long Form Question Answering.

BitNet Text Embeddings ELI5: Long Form Question Answering

Reference 18

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Observation 84dc436c-dd22-4589-92fa-c0e75a618456 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

BitNet Text Embeddings GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 19

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Observation 33a03117-e2da-4546-a560-49361b73254d · outbound

This paper cites SimCSE: Simple Contrastive Learning of Sentence Embeddings.

BitNet Text Embeddings SimCSE: Simple Contrastive Learning of Sentence Embeddings

Reference 20

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Observation 55c70530-ea35-415e-a680-5c0fd84dc513 · outbound

This paper cites A survey of low-bit large language models: Basics, systems, and algorithms.Neural networks, page 107856, 2025.

BitNet Text Embeddings A survey of low-bit large language models: Basics, systems, and algorithms.Neural networks, page 107856, 2025

Reference 21

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Observation 4c367864-57a7-4933-872f-b8323812637d · outbound

This paper cites an unresolved cited work.

BitNet Text Embeddings Unresolved cited work

Reference 22

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Observation 4e021082-1f01-4864-b0ab-9c4721f37522 · outbound

This paper cites Quaff: Quantized parameter-efficient fine-tuning under outlier spatial stability hypothesis.

BitNet Text Embeddings Quaff: Quantized parameter-efficient fine-tuning under outlier spatial stability hypothesis

Reference 23

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Observation 6e82e67c-0213-4d96-ac2c-d39b7945c067 · outbound

This paper cites Dense passage retrieval for open-domain question answering.

BitNet Text Embeddings Dense passage retrieval for open-domain question answering

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.745552Z

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Observation bb65246a-72ee-4d93-8054-20f057fe658e · outbound

This paper cites Colbert: Efficient and effective passage search via contextual- ized late interaction over bert.

BitNet Text Embeddings Colbert: Efficient and effective passage search via contextual- ized late interaction over bert

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.748170Z

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Observation bcbdf0c5-f709-4359-b44b-1ad652600395 · outbound

This paper cites Ma- tryoshka representation learning.Advances in Neural Information Processing Systems, 35: 30233–30249, 2022.

BitNet Text Embeddings Ma- tryoshka representation learning.Advances in Neural Information Processing Systems, 35: 30233–30249, 2022

Reference 26

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Observation c78f134e-705f-4d6b-895c-0c007eab928e · outbound

This paper cites Newsweeder: Learning to filter netnews.

BitNet Text Embeddings Newsweeder: Learning to filter netnews

Reference 27

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Observation 13ef06f1-972e-4c08-b7e1-debac3ad4714 · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

BitNet Text Embeddings NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 28

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Observation 9546d93a-71f4-47b5-8cba-d6a02507aa56 · outbound

This paper cites Gecko: Versatile Text Embeddings Distilled from Large Language Models.

BitNet Text Embeddings Gecko: Versatile Text Embeddings Distilled from Large Language Models

Reference 29

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Observation ecd02d8d-b6c6-4c66-b74b-eea92adbee2a · outbound

This paper cites Llama2vec: Unsupervised adaptation of large language models for dense retrieval.

BitNet Text Embeddings Llama2vec: Unsupervised adaptation of large language models for dense retrieval

Reference 30

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Observation c55050a8-2572-4fd9-8736-8cceb5fa2231 · outbound

This paper cites Making Text Embedders Few-Shot Learners.

BitNet Text Embeddings Making Text Embedders Few-Shot Learners

Reference 31

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Observation 6180ac0e-a17e-4bb2-96d1-39ca7518cf1d · outbound

This paper cites MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark.

BitNet Text Embeddings MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark

Reference 32

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Observation ed187fa9-f8c9-4113-8833-c726af7dd2bf · outbound

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

BitNet Text Embeddings Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 33

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Observation 683df9b5-c998-4695-9b30-185101d4e448 · outbound

This paper cites Quantization Meets Reasoning: Exploring LLM Low-Bit Quantization Degradation for Mathematical Reasoning.

BitNet Text Embeddings Quantization Meets Reasoning: Exploring LLM Low-Bit Quantization Degradation for Mathematical Reasoning

Reference 35

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Observation d5bf3bed-3b2c-43c9-bf4a-9c5b0a64adf3 · outbound

This paper cites Awq: Activation-aware weight quantization for on-device llm compression and acceleration.Proceedings of machine learning and systems, 6:87–100, 2024.

BitNet Text Embeddings Awq: Activation-aware weight quantization for on-device llm compression and acceleration.Proceedings of machine learning and systems, 6:87–100, 2024

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.779910Z

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Observation 0032569b-1d12-4b5b-892c-7ad2d63d7f37 · outbound

This paper cites Linkso: a dataset for learning to retrieve similar question answer pairs on software development forums.

BitNet Text Embeddings Linkso: a dataset for learning to retrieve similar question answer pairs on software development forums

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.782599Z

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Observation 6e54f463-5e09-4b9e-bf38-b9b7d4443591 · outbound

This paper cites Llm-qat: Data-free quantiza- tion aware training for large language models.

BitNet Text Embeddings Llm-qat: Data-free quantiza- tion aware training for large language models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.786698Z

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Observation 7db72f83-fca9-478a-a924-a376b05b1056 · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

BitNet Text Embeddings The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.789980Z

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Observation 72af1efb-8c32-4097-92fc-e065449905a5 · outbound

This paper cites BitNet b1.58 2B4T Technical Report.

BitNet Text Embeddings BitNet b1.58 2B4T Technical Report

Reference 40

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Observation 892fc396-f748-4c3d-94cc-8b682288c644 · outbound

This paper cites Fine-tuning llama for multi-stage text retrieval.

BitNet Text Embeddings Fine-tuning llama for multi-stage text retrieval

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.797987Z

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Observation d4611761-d902-4f96-8342-79f0d85a94e8 · outbound

This paper cites Learning word vectors for sentiment analysis.

BitNet Text Embeddings Learning word vectors for sentiment analysis

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.801339Z

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Observation 9bbb558e-c3f6-47ad-af87-93d4fddf5473 · outbound

This paper cites Tweet sentiment extraction.

BitNet Text Embeddings Tweet sentiment extraction

Reference 43

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Observation 0594be60-c1a2-4c7b-8d2b-197b8c1a4ecd · outbound

This paper cites Www’18 open challenge: financial opinion mining and question answering.

BitNet Text Embeddings Www’18 open challenge: financial opinion mining and question answering

Reference 44

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Observation 295a87bc-40de-4d52-8c67-3f5c4e6ed89b · outbound

This paper cites Hidden factors and hidden topics: understanding rating dimensions with review text.

BitNet Text Embeddings Hidden factors and hidden topics: understanding rating dimensions with review text

Reference 45

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Observation c7bb3b0f-df8c-4859-91d5-11c963ee2318 · outbound

This paper cites Sfrembedding-mistral: enhance text retrieval with transfer learning.Salesforce AI Research Blog, 3:6, 2024.

BitNet Text Embeddings Sfrembedding-mistral: enhance text retrieval with transfer learning.Salesforce AI Research Blog, 3:6, 2024

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.813022Z

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Observation 6a1a9e08-cdc5-497c-a720-c28ca48dea16 · outbound

This paper cites SGPT: GPT Sentence Embeddings for Semantic Search.

BitNet Text Embeddings SGPT: GPT Sentence Embeddings for Semantic Search

Reference 47

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Observation 3af3a148-bc12-4ff5-acc6-75a667f05196 · outbound

This paper cites MTEB: Massive text embedding benchmark.

BitNet Text Embeddings MTEB: Massive text embedding benchmark

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.818635Z

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Observation 60baa285-ebe7-4d17-9107-0297108a69c7 · outbound

This paper cites Generative representational instruction tuning.

BitNet Text Embeddings Generative representational instruction tuning

Reference 49

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Observation 3c6b9b42-9c05-4204-a611-bf7c1b169da2 · outbound

This paper cites Matryoshka Quantization.

BitNet Text Embeddings Matryoshka Quantization

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.824522Z

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Observation 6990a46a-5092-4990-84e9-e4948206c28f · outbound

This paper cites Ms marco: A human-generated machine reading comprehension dataset.

BitNet Text Embeddings Ms marco: A human-generated machine reading comprehension dataset

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.827484Z

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Observation ca065d1d-757c-44fb-a976-8d728ed90847 · outbound

This paper cites I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Reviews.

BitNet Text Embeddings I Wish I Would Have Loved This One, But I Didn't -- A Multilingual Dataset for Counterfactual Detection in Product Reviews

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.830259Z

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Observation 8f4f450c-e484-4d47-83dc-d6476bfb4263 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

BitNet Text Embeddings Representation Learning with Contrastive Predictive Coding

Reference 53

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Observation ea11a738-4664-4030-8b72-45aba594b306 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert- networks.

BitNet Text Embeddings Sentence-bert: Sentence embeddings using siamese bert- networks

Reference 54

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Observation 843eec74-723d-4b14-a989-098986469783 · outbound

This paper cites Carer: Contextualized affect representations for emotion recognition.

BitNet Text Embeddings Carer: Contextualized affect representations for emotion recognition

Reference 55

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Observation 8e7cb965-7f61-4bce-bcbd-56a2bd992864 · outbound

This paper cites Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training.

BitNet Text Embeddings Q-RAG: Long Context Multi-step Retrieval via Value-based Embedder Training

Reference 56

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Observation b327fc5d-0fa0-4f47-9d5f-efab8ec76753 · outbound

This paper cites Smith, Luke Zettlemoyer, and Tao Yu.

BitNet Text Embeddings Smith, Luke Zettlemoyer, and Tao Yu

Reference 57

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Observation 2c2322bf-3fb9-4b04-ae53-aa4ad3b82e43 · outbound

This paper cites LLMs are Also Effective Embedding Models: An In-depth Overview.

BitNet Text Embeddings LLMs are Also Effective Embedding Models: An In-depth Overview

Reference 58

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Observation d42a69f1-6825-4bac-90e8-4b4d64f5a8c6 · outbound

This paper cites Gemma 3 Technical Report.

BitNet Text Embeddings Gemma 3 Technical Report

Reference 59

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Observation 601f90e0-4d65-4eae-8206-05b79ff2defc · outbound

This paper cites FEVER: a large-scale dataset for Fact Extraction and VERification.

BitNet Text Embeddings FEVER: a large-scale dataset for Fact Extraction and VERification

Reference 60

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Observation af066b5d-5789-47c8-8471-9d6148034f07 · outbound

This paper cites Retrieval of the best counterargument without prior topic knowledge.

BitNet Text Embeddings Retrieval of the best counterargument without prior topic knowledge

Reference 61

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Observation 9a8a2b89-6783-4bfc-8152-2bd3622b6702 · outbound

This paper cites BitNet: Scaling 1-bit Transformers for Large Language Models.

BitNet Text Embeddings BitNet: Scaling 1-bit Transformers for Large Language Models

Reference 62

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Observation ba61b102-f779-4f22-bc75-b557681fdd37 · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

BitNet Text Embeddings Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 63

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Observation f91543c4-78dc-4830-9f1b-4fd6489a8545 · outbound

This paper cites Improving text embeddings with large language models.

BitNet Text Embeddings Improving text embeddings with large language models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.868119Z

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Observation c5aac65f-35f1-4c2a-ae74-fdf132409529 · outbound

This paper cites Multilingual E5 Text Embeddings: A Technical Report.

BitNet Text Embeddings Multilingual E5 Text Embeddings: A Technical Report

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.871165Z

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Observation fdefdc46-a3bb-4825-bdc8-626c120148d9 · outbound

This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020.

BitNet Text Embeddings Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.874303Z

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Observation b792bd47-0902-42b0-9450-3847a8ea6dc1 · outbound

This paper cites Minilmv2: Multi-head self-attention relation distillation for compressing pretrained transformers.

BitNet Text Embeddings Minilmv2: Multi-head self-attention relation distillation for compressing pretrained transformers

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.877636Z

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Observation 95cb002b-9301-4097-a4ab-39612a54dd44 · outbound

This paper cites an unresolved cited work.

BitNet Text Embeddings Unresolved cited work

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.880360Z

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Observation 06c57d76-d617-441f-8cce-316809d13db9 · outbound

This paper cites Bitnet distillation.arXiv preprint arXiv:2510.13998, 2025.

BitNet Text Embeddings Bitnet distillation.arXiv preprint arXiv:2510.13998, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.883369Z

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Observation dceafbff-b725-47ce-aa25-cfa5b3424d6f · outbound

This paper cites Smoothquant: Accurate and efficient post-training quantization for large language models.

BitNet Text Embeddings Smoothquant: Accurate and efficient post-training quantization for large language models

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.886235Z

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Observation ef02838f-0a8a-4f05-8d67-27dc2092e242 · outbound

This paper cites Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval.

BitNet Text Embeddings Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.889437Z

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Observation 51f1c0d3-b396-4fc2-9098-54774267ba38 · outbound

This paper cites Onebit: Towards extremely low-bit large language models.Advances in Neural Information Processing Systems, 37:66357–66382, 2024.

BitNet Text Embeddings Onebit: Towards extremely low-bit large language models.Advances in Neural Information Processing Systems, 37:66357–66382, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.892460Z

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Observation 50ce3a38-d5e2-4a6d-badb-4d27cf96a74b · outbound

This paper cites Qwen3 Technical Report.

BitNet Text Embeddings Qwen3 Technical Report

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.895400Z

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Observation cff555c3-15e6-4e0e-9948-f5bbff97a1a1 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

BitNet Text Embeddings HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.898561Z

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Observation be4909c9-1ac6-4e44-8e94-20dbf0afa05f · outbound

This paper cites RPTQ: Reorder-based Post-training Quantization for Large Language Models.

BitNet Text Embeddings RPTQ: Reorder-based Post-training Quantization for Large Language Models

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.901412Z

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Observation 5d95d693-86a2-48d8-be80-9acec3e4512e · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

BitNet Text Embeddings Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.904759Z

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Observation 13d2c91c-3c8c-46f7-a9d6-378e733f40df · outbound

This paper cites Retrieval-Augmented Generation for AI-Generated Content: A Survey.

BitNet Text Embeddings Retrieval-Augmented Generation for AI-Generated Content: A Survey

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.907527Z

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Observation 4260c38a-ab3e-4c50-a4cd-7fa32bef607e · outbound

This paper cites Dense text retrieval based on pretrained language models: A survey.ACM Transactions on Information Systems, 42(4):1–60, 2024.

BitNet Text Embeddings Dense text retrieval based on pretrained language models: A survey.ACM Transactions on Information Systems, 42(4):1–60, 2024

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.910373Z

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Observation c48f276d-b36f-4fab-bc7b-a9f95940d7c4 · outbound

This paper cites Embedding in recommender systems: A survey.arXiv preprint arXiv:2310.18608, 2023.

BitNet Text Embeddings Embedding in recommender systems: A survey.arXiv preprint arXiv:2310.18608, 2023

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.912971Z

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Observation 65ffb201-b354-445b-92cb-27f5b8fa5673 · outbound

This paper cites Kalm-embedding-v2: Superior training techniques and data inspire a versatile embedding model.arXiv preprint arXiv:2506.20923, 2025.

BitNet Text Embeddings Kalm-embedding-v2: Superior training techniques and data inspire a versatile embedding model.arXiv preprint arXiv:2506.20923, 2025

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Resolution: unresolved; no resolver link, observed 2026-08-02T10:15:53.915610Z

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