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Paper Citation Record · LEDGER

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation

As of 13 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2510.13434.

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

pith.paper-citation-record.v1
2510.13434 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:50:07.507773Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

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  • unresolved44
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  • malformed identifier0
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External citation measurements

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Outbound references

Observation d0b2ce2a-2566-43c4-84b3-38d45da0fc1f · outbound

This paper cites GPT-4 Technical Report.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation GPT-4 Technical Report

Reference 1

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source=arxiv_source observed=2026-08-04T09:50:02.522117Z digest=sha256:8a90c9823dc133e99eb40e85693f2272707fb0c9883ddbcaf79dd6d33adf30a4

Observation ba61d1fd-32a7-452e-9529-f199e4bb7258 · outbound

This paper cites Modeling User Preferences with Automatic Metrics: Creating a High-Quality Preference Dataset for Machine Translation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Modeling User Preferences with Automatic Metrics: Creating a High-Quality Preference Dataset for Machine Translation

Reference 2

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source=arxiv_source observed=2026-08-04T09:50:02.592842Z digest=sha256:37968a3113e8757437ef4127f8ca2c3f85a1efa40980eacca11eeb8d99b6dfa0

Observation 79757d5f-7c5f-410a-88b6-61320cfa373f · outbound

This paper cites Tower: An Open Multilingual Large Language Model for Translation-Related Tasks.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Tower: An Open Multilingual Large Language Model for Translation-Related Tasks

Reference 3

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source=arxiv_source observed=2026-08-04T09:50:02.653585Z digest=sha256:cf8f2d0ebad7c016b6b82ce745e24b533ba09a0ddebd9af258c0c458c35879c3

Observation f24a5ba4-b0d2-4fe6-8475-e1c8080ddb17 · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-04T09:50:02.724556Z digest=sha256:fdf39d30a7f2de14fe241f245cafb5ece821101ca55c1f159f6f449425d41c16

Observation a9c76934-81f2-4fd8-8497-e32f9f43fab8 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 5

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source=arxiv_source observed=2026-08-04T09:50:02.802498Z digest=sha256:fa434af40a76f3909c3a583de61db084c275306130b1d1e9ffbbdbe3b4bb64f2

Observation 4e44bbe1-9eb7-4ff1-a653-869c697fb589 · outbound

This paper cites No Language Left Behind: Scaling Human-Centered Machine Translation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation No Language Left Behind: Scaling Human-Centered Machine Translation

Reference 6

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source=arxiv_source observed=2026-08-04T09:50:02.905069Z digest=sha256:631c74d50d4b4d05f1005ed8bf911ba8b09c2b5efb09e2e2e66af2f6bc92076f

Observation 976a655d-ee16-4605-9b09-749733efc3ba · outbound

This paper cites CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation CRPO: Confidence-Reward Driven Preference Optimization for Machine Translation

Reference 7

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source=arxiv_source observed=2026-08-04T09:50:02.986120Z digest=sha256:8fcdeb9944278ae3e0512921e406a73b9517f6b553baa43d47e754e3518ba49b

Observation cf1d0701-7515-42ca-b9f0-49c483a3e0d7 · outbound

This paper cites Detecting and Mitigating Hallucinations in Machine Translation: Model Internal Workings Alone Do Well, Sentence Similarity Even Better.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Detecting and Mitigating Hallucinations in Machine Translation: Model Internal Workings Alone Do Well, Sentence Similarity Even Better

Reference 8

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source=arxiv_source observed=2026-08-04T09:50:03.089672Z digest=sha256:eb6deb7840a0ab9b9eeb277de75a36ca20f36e91915c31be3c182052185eef6f

Observation 6bd915dc-f38a-4a00-9760-6635ca90c592 · outbound

This paper cites HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation HalOmi: A Manually Annotated Benchmark for Multilingual Hallucination and Omission Detection in Machine Translation

Reference 9

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source=arxiv_source observed=2026-08-04T09:50:03.261501Z digest=sha256:3efd383a2aeb01fdfd9da4466c220db05de7df24d205a2fb84856cc47fe19ee6

Observation ac1de6ad-7ff7-4f55-8a41-018cf485df48 · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation KTO: Model Alignment as Prospect Theoretic Optimization

Reference 10

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source=arxiv_source observed=2026-08-04T09:50:03.376401Z digest=sha256:fb751ad1ebcfe028e26b60b379c6420ac9b4ddc7a26118ab69e985b60f12c45e

Observation e03e3530-dc5c-4898-b38b-9a02114b9626 · outbound

This paper cites Can LLMs Detect Intrinsic Hallucinations in Paraphrasing and Machine Translation?.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Can LLMs Detect Intrinsic Hallucinations in Paraphrasing and Machine Translation?

Reference 11

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Observation 73e17357-97f6-4436-a6c3-60e243300d80 · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-04T09:50:03.541620Z digest=sha256:38c9096cf82239ec2f52f20698bae32e474663ab075351fddc4518bcea4e665a

Observation 175ff436-4aa9-45a1-a1e5-9c79c92d5c31 · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 13

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source=arxiv_source observed=2026-08-04T09:50:03.599366Z digest=sha256:9d4e3a385a90f1848d21f1c3eaab7ed87eee32f6771d14d9af5d13e56952653b

Observation 002a8e3c-571b-4083-8a5d-d97d2360c8b5 · outbound

This paper cites Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation

Reference 14

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source=arxiv_source observed=2026-08-04T09:50:03.668869Z digest=sha256:0c80f2489d9bdadf2836e1c9fba02ccd051dd4129fcaf86043c2ec8421833ebb

Observation acaf48c6-814a-4f58-a64c-09881400811e · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 15

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source=arxiv_source observed=2026-08-04T09:50:03.793596Z digest=sha256:9cb430f3ce6933e610dee63cc81191be794407a27799a596651607069e00528f

Observation 0944a4b3-c4c1-4b57-99f2-434fcf8205b6 · outbound

This paper cites Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Improving Machine Translation with Human Feedback: An Exploration of Quality Estimation as a Reward Model

Reference 16

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source=arxiv_source observed=2026-08-04T09:50:03.898506Z digest=sha256:48426cc866c7bdc6d5e05a206a9e69547cffea301acbe0eaa5bb1e4dc5c8dcb6

Observation cea6677b-c46f-4e5a-bab4-70b51806097d · outbound

This paper cites Contrastive Preference Learning: Learning from Human Feedback without RL.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Contrastive Preference Learning: Learning from Human Feedback without RL

Reference 17

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source=arxiv_source observed=2026-08-04T09:50:04.047978Z digest=sha256:2c1be6ab58d47a2a16df374ca4d78a5931a2e907a8215ddf8e95faedce029a5e

Observation 2094f886-37ee-45fb-acda-1e1ea2889166 · outbound

This paper cites How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 18

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source=arxiv_source observed=2026-08-04T09:50:04.149883Z digest=sha256:322f1277c30ec250fc6bc3583503073ff3af333b9823e883af51c691b225124a

Observation 24c12511-d0bc-4ee4-8041-b610e0d283de · outbound

This paper cites ORPO: Monolithic Preference Optimization without Reference Model.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation ORPO: Monolithic Preference Optimization without Reference Model

Reference 19

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Observation 1068cad0-90c5-4006-a27b-4d002608ef6a · outbound

This paper cites GPT-4o System Card.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation GPT-4o System Card

Reference 20

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Observation 7436fb04-70f6-48f3-9d7e-99c7e05693ef · outbound

This paper cites Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine

Reference 21

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Observation 6a11adde-ad1c-4c6c-b76f-cf4fc1caa69f · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 22

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Observation 77c37f51-0885-41b6-b3b9-abe8b1828281 · outbound

This paper cites Memory-efficient NLLB-200: Language-specific Expert Pruning of a Massively Multilingual Machine Translation Model.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Memory-efficient NLLB-200: Language-specific Expert Pruning of a Massively Multilingual Machine Translation Model

Reference 23

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source=arxiv_source observed=2026-08-04T09:50:04.628687Z digest=sha256:85d295f40dfbbd779424801d77ca8a7b6afb42572b32586f9aeb3ba35ba94041

Observation dd7c05a7-8a48-4440-a20d-1c43a7b4be05 · outbound

This paper cites DeepSeek-V3 Technical Report.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation DeepSeek-V3 Technical Report

Reference 24

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source=arxiv_source observed=2026-08-04T09:50:04.727264Z digest=sha256:e7c2ba463574af66fa9930d90e93192ccabd80f6282e710016c8816f836de4a7

Observation 94036643-f98c-4511-8f50-09710931f967 · outbound

This paper cites Decoupled Weight Decay Regularization.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Decoupled Weight Decay Regularization

Reference 25

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source=arxiv_source observed=2026-08-04T09:50:04.865393Z digest=sha256:dd978bda5867b76a2b14ddae31b0ed9d653ddb21bc82568dc9863be71846823e

Observation 9f5d4f3e-986e-4b30-856b-be9eacfc1ed6 · outbound

This paper cites LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages

Reference 26

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Observation 1c84cec1-4113-441f-bba7-63915c8ee19b · outbound

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$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 27

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Observation 58888cfb-78cb-4565-869a-fb0ee621c168 · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

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source=arxiv_source observed=2026-08-04T09:50:05.452940Z digest=sha256:ade2d8d41adbca2f9b7acaca1109d7b52b37b1de7582f528b0ad78c2a8492881

Observation c744e360-72ef-4285-a536-d6fb697291d6 · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 29

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source=arxiv_source observed=2026-08-04T09:50:05.629235Z digest=sha256:14f8467436328e992c5a45447c22a8baeb5d679d8b410141a9d790d50973cf14

Observation 9bfc88cd-18f3-4727-9369-0ec777d20691 · outbound

This paper cites Tower+: Bridging Generality and Translation Specialization in Multilingual LLMs.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Tower+: Bridging Generality and Translation Specialization in Multilingual LLMs

Reference 30

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source=arxiv_source observed=2026-08-04T09:50:05.807754Z digest=sha256:a43a962074c121604e05e59f2fe46c61dbd607721bef57430d7374d97e4d9441

Observation 68209624-acf6-46a4-808e-c2ce651b45fd · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 31

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source=arxiv_source observed=2026-08-04T09:50:05.998908Z digest=sha256:434b6f0565c66e3a57e107e9ff018984d90f3bc1a3a4535c396a482747b4a32c

Observation 085e88d5-4484-414c-ad14-c9e3dd12d00a · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation LLaMA: Open and Efficient Foundation Language Models

Reference 32

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Observation 227fb14d-6978-44ba-b4cc-3bda7881dc65 · outbound

This paper cites As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation As Little as Possible, as Much as Necessary: Detecting Over- and Undertranslations with Contrastive Conditioning

Reference 33

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Observation a48460c2-dc43-407b-955c-bbd1480ca13a · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 34

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source=arxiv_source observed=2026-08-04T09:50:06.449352Z digest=sha256:9f53f17fb85617de00791ec43ad3fb88ae217761acca0c0e97c874c23105469d

Observation 39f9e1b7-32d0-447e-ab86-ee2afe9d4162 · outbound

This paper cites Word Alignment as Preference for Machine Translation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Word Alignment as Preference for Machine Translation

Reference 35

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source=arxiv_source observed=2026-08-04T09:50:06.617470Z digest=sha256:faa5b92609a7736b9ed15ca50461252073cd4a32388ccb64332d4b5738366ea8

Observation a8eba93f-e899-4e42-ae64-ebb3ce1363e4 · outbound

This paper cites WSPAlign: Word Alignment Pre-training via Large-Scale Weakly Supervised Span Prediction.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation WSPAlign: Word Alignment Pre-training via Large-Scale Weakly Supervised Span Prediction

Reference 36

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source=arxiv_source observed=2026-08-04T09:50:06.740435Z digest=sha256:2b68fdfc3a738e0a1364856590e18a324cceac57b626f2f6264c61aca1832590

Observation 8f768d4f-7346-4581-97e0-854535ccfe64 · outbound

This paper cites A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation A Paradigm Shift in Machine Translation: Boosting Translation Performance of Large Language Models

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:06.870329Z digest=sha256:a0f86da6758e26191766f5c042d5fe5526a22525c5b01288542b59f506ca094c

Observation 7dc8f5b0-233c-48f0-9338-4d058e4aa7c3 · outbound

This paper cites X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-04T09:50:07.000933Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:07.000933Z digest=sha256:babc9edbeb053b4a1c1b9889e2481878d4dabc30600402fd058856df66542404

Observation bec05bba-af50-483a-8d70-9c325ea225c9 · outbound

This paper cites Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-04T09:50:07.127724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:07.127724Z digest=sha256:b3e92abe64956d7d6108f3c9c31170fdab116f695fc9e8092d19347c696b9252

Observation 1a7d487f-b550-4290-8cc0-b15c9f7d393c · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-04T09:50:07.188460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:07.188460Z digest=sha256:f34071cb840b3f86c0b226e7c1dec89c7779a2c2b288f9f0df6c665380e64f68

Observation c55f7cc3-6b9e-437e-b1f1-75e49ad8408d · outbound

This paper cites an unresolved cited work.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-04T09:50:07.275069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:07.275069Z digest=sha256:66e79e7e054427e11604ec845c3a94c2e1e9d96f1b0310a6a0c5ffede0521340

Observation c1e8727d-529e-4339-8bd7-30539d0afbf9 · outbound

This paper cites BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T09:50:07.340658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:07.340658Z digest=sha256:3a902a3287d016516662c796c29bb06e8f2bc280449b6d688cdebb5923795dc5

Observation a00962b9-4fa7-4d1c-b05b-ad815d419e51 · outbound

This paper cites online" 'onlinestring :=.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation online" 'onlinestring :=

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T09:50:07.414828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:07.414828Z digest=sha256:d0e763523a3da6a81278c08cfbe370eaf5254d6501e3c72b173292703ba24873

Observation edf7a611-6f91-4b80-b17e-331ee69ac66d · outbound

This paper cites write newline.

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation write newline

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-04T09:50:07.507773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T09:50:07.507773Z digest=sha256:d7f718073bc715b14cc8b189d68b4e9b7203cfbe4e31f4f3a93b29355cd899ae

Pith citing papers

No inbound Pith citation observations are available.