Meta-Learning Preferences for Multilingual LLM Alignment | Paper Citation Record

Observation 3b11c6ea-5363-4d49-8ca2-652dbba94092 · outbound

This paper cites GPT-4 Technical Report.

Meta-Learning Preferences for Multilingual LLM Alignment GPT-4 Technical Report

Reference 1

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Observation 7ef4aba8-3a77-4195-988c-971851eefba3 · outbound

This paper cites Apertus: Democratizing open and compliant llms for global language environments, 2025.

Meta-Learning Preferences for Multilingual LLM Alignment Apertus: Democratizing open and compliant llms for global language environments, 2025

Reference 2

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Observation b862e81c-3465-4979-b439-26aac3f8b66e · outbound

This paper cites Qwen Technical Report.

Meta-Learning Preferences for Multilingual LLM Alignment Qwen Technical Report

Reference 3

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Observation 5ee7f332-c4b0-479f-a78b-aa5893c4681c · outbound

This paper cites Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM.

Meta-Learning Preferences for Multilingual LLM Alignment Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM

Reference 4

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Observation bd78940f-8849-44fc-b349-50df09e3cddc · outbound

This paper cites BLOOM (revision 4ab0472), 2022.

Meta-Learning Preferences for Multilingual LLM Alignment BLOOM (revision 4ab0472), 2022

Reference 5

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Observation b0898f9b-d7f8-4cd1-9760-022d9ee9aa8a · outbound

This paper cites LLMs Are Few-Shot In-Context Low-Resource Language Learners.

Meta-Learning Preferences for Multilingual LLM Alignment LLMs Are Few-Shot In-Context Low-Resource Language Learners

Reference 6

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Observation b26122b2-55de-4fe1-a2be-f27e8b042cf2 · outbound

This paper cites Meta-learning via lan- guage model in-context tuning.

Meta-Learning Preferences for Multilingual LLM Alignment Meta-learning via lan- guage model in-context tuning

Reference 7

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Observation 4e2bc3b5-cf0c-4357-aaab-bbc7062d216d · outbound

This paper cites TigerBot: An Open Multilingual Multitask LLM.

Meta-Learning Preferences for Multilingual LLM Alignment TigerBot: An Open Multilingual Multitask LLM

Reference 8

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Observation 03de064c-8d93-4a80-b715-038590cd68cb · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Meta-Learning Preferences for Multilingual LLM Alignment Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 9

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Observation b09b8675-8c74-4349-af80-5e706d9d14ae · outbound

This paper cites Meta-in-context learning in large language models.

Meta-Learning Preferences for Multilingual LLM Alignment Meta-in-context learning in large language models

Reference 10

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Observation 8f372cca-0619-4d06-b64b-7472d8dc7dbe · outbound

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

Meta-Learning Preferences for Multilingual LLM Alignment Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 11

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Observation 7f125744-e2a6-4b51-b6a8-640a9b30b4c5 · outbound

This paper cites Okapi: Instruction-tuned large language models in multiple languages with reinforcement learning from human feedback.arXiv e-prints, pages arXiv–2307, 2023.

Meta-Learning Preferences for Multilingual LLM Alignment Okapi: Instruction-tuned large language models in multiple languages with reinforcement learning from human feedback.arXiv e-prints, pages arXiv–2307, 2023

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:13.056728Z

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Observation 791f37b8-4910-46a7-87b1-ca620e11334f · outbound

This paper cites Evaluating and mitigating linguistic discrimination in large language models: Perspectives on safety equity and knowledge equity.

Meta-Learning Preferences for Multilingual LLM Alignment Evaluating and mitigating linguistic discrimination in large language models: Perspectives on safety equity and knowledge equity

Reference 13

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Observation fe344923-69f3-4e72-9945-ed44a6d066f4 · outbound

This paper cites Rlhf workflow: From reward modeling to online rlhf,.

Meta-Learning Preferences for Multilingual LLM Alignment Rlhf workflow: From reward modeling to online rlhf,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:13.243452Z

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Observation 8e545401-af02-4696-91e8-24cd4ca7da99 · outbound

This paper cites Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators.

Meta-Learning Preferences for Multilingual LLM Alignment Length-Controlled AlpacaEval: A Simple Way to Debias Automatic Evaluators

Reference 15

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Observation 01f70ae9-1127-4a5f-a0cd-59b72d21835e · outbound

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

Meta-Learning Preferences for Multilingual LLM Alignment KTO: Model Alignment as Prospect Theoretic Optimization

Reference 16

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Observation 668aa081-a40f-440a-96a7-313f2f862fcf · outbound

This paper cites On the convergence theory of gradient- based model-agnostic meta-learning algorithms.

Meta-Learning Preferences for Multilingual LLM Alignment On the convergence theory of gradient- based model-agnostic meta-learning algorithms

Reference 17

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Observation 8c9e2753-2239-49c6-adcb-4f2bf0e3433c · outbound

This paper cites Model-agnostic meta-learning for fast adap- tation of deep networks.

Meta-Learning Preferences for Multilingual LLM Alignment Model-agnostic meta-learning for fast adap- tation of deep networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:13.661052Z

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Observation 02e4f11c-e8b8-419a-8c58-fc8201182734 · outbound

This paper cites A general theoretical paradigm to understand learning from human preferences.

Meta-Learning Preferences for Multilingual LLM Alignment A general theoretical paradigm to understand learning from human preferences

Reference 19

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Observation 73f270be-dc13-4393-8342-9a27eb0bb313 · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Meta-Learning Preferences for Multilingual LLM Alignment Measuring Massive Multitask Language Understanding

Reference 20

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Observation b3c3f426-240c-48eb-8b8a-99a6995c99b8 · outbound

This paper cites Measuring massive multitask language understanding.Proceedings of the International Conference on Learning Representations (ICLR), 2021.

Meta-Learning Preferences for Multilingual LLM Alignment Measuring massive multitask language understanding.Proceedings of the International Conference on Learning Representations (ICLR), 2021

Reference 21

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Observation 47c8e219-4039-439a-992d-f199e86ac3e5 · outbound

This paper cites Llms as in-context meta-learners for model and hyperparameter selection, 2025.

Meta-Learning Preferences for Multilingual LLM Alignment Llms as in-context meta-learners for model and hyperparameter selection, 2025

Reference 22

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Observation dbfbb7a2-e660-4d35-b145-72e6c138010c · outbound

This paper cites Meta-learning in neural networks: A survey.IEEE transactions on pattern analysis and machine intelligence, 44 (9):5149–5169, 2021.

Meta-Learning Preferences for Multilingual LLM Alignment Meta-learning in neural networks: A survey.IEEE transactions on pattern analysis and machine intelligence, 44 (9):5149–5169, 2021

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:13.955285Z

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Observation fff61118-b1c4-45d7-af18-0b0e5857ba3b · outbound

This paper cites Meta-Learning Online Adaptation of Language Models.

Meta-Learning Preferences for Multilingual LLM Alignment Meta-Learning Online Adaptation of Language Models

Reference 24

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Observation a78282be-9c25-4e96-849c-dd5c4ee31059 · outbound

This paper cites Krutrim LLM: Multilingual Foundational Model for over a Billion People.

Meta-Learning Preferences for Multilingual LLM Alignment Krutrim LLM: Multilingual Foundational Model for over a Billion People

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.074298Z

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Observation 54d02ecb-abea-446a-9d2d-7b20c16653a7 · outbound

This paper cites Mistral–a journey towards reproducible language model training, 2021.

Meta-Learning Preferences for Multilingual LLM Alignment Mistral–a journey towards reproducible language model training, 2021

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.171078Z

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Observation 1a16c7e4-f4fd-4c27-b473-80f1851748b3 · outbound

This paper cites LLMs Beyond English: Scaling the Multilingual Capability of LLMs with Cross-Lingual Feedback.

Meta-Learning Preferences for Multilingual LLM Alignment LLMs Beyond English: Scaling the Multilingual Capability of LLMs with Cross-Lingual Feedback

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.237858Z

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Observation e4f11dc6-c188-4784-973f-3377241a6687 · outbound

This paper cites Improving in-context learning of multilingual generative language models with cross-lingual alignment.

Meta-Learning Preferences for Multilingual LLM Alignment Improving in-context learning of multilingual generative language models with cross-lingual alignment

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.331522Z

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Observation 0171f048-b64a-4755-bc3f-90c030d0cdea · outbound

This paper cites Meta in-context learning makes large language models better zero and few-shot relation extractors,.

Meta-Learning Preferences for Multilingual LLM Alignment Meta in-context learning makes large language models better zero and few-shot relation extractors,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.401895Z

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Observation 0bc005ac-2cdc-4506-adbd-650d3e3d796d · outbound

This paper cites Congrad: Conflicting gradient filtering for multilingual preference align- ment.

Meta-Learning Preferences for Multilingual LLM Alignment Congrad: Conflicting gradient filtering for multilingual preference align- ment

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.547872Z

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Observation 84a4f034-7b6d-41f7-aa98-db68561fbf1b · outbound

This paper cites Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors.

Meta-Learning Preferences for Multilingual LLM Alignment Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.454651Z

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Observation eaef0e02-cb26-4cc7-ada6-c149aa068731 · outbound

This paper cites MEND: Meta dEmonstratioN Distillation for Efficient and Effective In-Context Learning.

Meta-Learning Preferences for Multilingual LLM Alignment MEND: Meta dEmonstratioN Distillation for Efficient and Effective In-Context Learning

Reference 32

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Observation 76694aae-860f-42e7-be5f-642ed2147cfa · outbound

This paper cites Language-emphasized cross-lingual in-context learning for multilingual llm.

Meta-Learning Preferences for Multilingual LLM Alignment Language-emphasized cross-lingual in-context learning for multilingual llm

Reference 33

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Observation b254970c-5506-4496-9f17-1c2abf0b110f · outbound

This paper cites Simpo: Simple preference optimization with a reference-free reward.Advances in Neural Information Processing Systems, 37:124198–124235, 2024.

Meta-Learning Preferences for Multilingual LLM Alignment Simpo: Simple preference optimization with a reference-free reward.Advances in Neural Information Processing Systems, 37:124198–124235, 2024

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.898909Z

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Observation 85326a5a-047e-468c-9dc8-1f0d1bed32e0 · outbound

This paper cites DeepSeek-V3 Technical Report.

Meta-Learning Preferences for Multilingual LLM Alignment DeepSeek-V3 Technical Report

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.832439Z

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Observation db68de96-c3ce-40e6-ad59-890f6cd89f8c · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

Meta-Learning Preferences for Multilingual LLM Alignment Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.065872Z

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Observation 85053ee8-46ce-4576-a0ce-3a84d8fc576c · outbound

This paper cites Reward model learning vs.

Meta-Learning Preferences for Multilingual LLM Alignment Reward model learning vs

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:14.990916Z

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Observation fee721f8-c723-4745-9e3e-ed26574b3300 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Meta-Learning Preferences for Multilingual LLM Alignment Direct preference optimization: Your language model is secretly a reward model

Reference 38

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Observation 9447292d-4435-4b0e-b53c-93b3d597264b · outbound

This paper cites From $r$ to $Q^*$: Your Language Model is Secretly a Q-Function.

Meta-Learning Preferences for Multilingual LLM Alignment From $r$ to $Q^*$: Your Language Model is Secretly a Q-Function

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.114550Z

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Observation 8fdeeca5-15ed-4667-8713-5cde168f5f0f · outbound

This paper cites Right now, wrong then: Non-stationary direct preference optimization under preference drift.

Meta-Learning Preferences for Multilingual LLM Alignment Right now, wrong then: Non-stationary direct preference optimization under preference drift

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.311747Z

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Observation ade80df4-469e-43cb-9b3f-1d019dda5e2c · outbound

This paper cites Maml-en-llm: Model agnostic meta-training of llms for improved in-context learning.

Meta-Learning Preferences for Multilingual LLM Alignment Maml-en-llm: Model agnostic meta-training of llms for improved in-context learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.239541Z

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Observation c6df849d-a624-4467-ab32-2e4767dd5460 · outbound

This paper cites RSPO: Regularized Self-Play Alignment of Large Language Models.

Meta-Learning Preferences for Multilingual LLM Alignment RSPO: Regularized Self-Play Alignment of Large Language Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.423449Z

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Observation 50742d01-a050-4cb1-896c-44018ef59ed5 · outbound

This paper cites Spo: Self preference optimization with self regularization.

Meta-Learning Preferences for Multilingual LLM Alignment Spo: Self preference optimization with self regularization

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.370686Z

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Observation 9bf61e01-390f-44f2-9695-48ccde926366 · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Meta-Learning Preferences for Multilingual LLM Alignment Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.680171Z

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Observation 3ea7d0a3-5654-46c4-87c5-8ea13b546c1e · outbound

This paper cites Hashimoto.

Meta-Learning Preferences for Multilingual LLM Alignment Hashimoto

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.507286Z

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Observation b2b73175-2180-49dc-80c2-bde577431d60 · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Meta-Learning Preferences for Multilingual LLM Alignment Gemma: Open Models Based on Gemini Research and Technology

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:15.952924Z

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Observation 30b0e66a-0b28-468c-aa2a-64046902667b · outbound

This paper cites Dai, Anja Hauth, Katie Millican, David Silver, et al.

Meta-Learning Preferences for Multilingual LLM Alignment Dai, Anja Hauth, Katie Millican, David Silver, et al

Reference 47

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Observation be385503-c9e8-400e-a301-a16f09f45290 · outbound

This paper cites Gemma 3 Technical Report.

Meta-Learning Preferences for Multilingual LLM Alignment Gemma 3 Technical Report

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.059522Z

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Observation 46fce1d2-d56d-4d1e-a029-1263bf01a586 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Meta-Learning Preferences for Multilingual LLM Alignment Gemma 2: Improving Open Language Models at a Practical Size

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.008896Z

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Observation 3e965813-8f3b-4596-a684-13ebae63d99e · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Meta-Learning Preferences for Multilingual LLM Alignment Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.195603Z

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Observation f569277c-d9ca-4bcb-9e9d-9225b711a8c0 · outbound

This paper cites Towards Multilingual LLM Evaluation for European Languages.

Meta-Learning Preferences for Multilingual LLM Alignment Towards Multilingual LLM Evaluation for European Languages

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.111549Z

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Observation 51333ff6-c5d5-4990-a3aa-21fc841a6dd3 · outbound

This paper cites Performance unfairness of large language models in cross-language fact-checking.Information Processing & Management, 63 (4):104616, 2026.

Meta-Learning Preferences for Multilingual LLM Alignment Performance unfairness of large language models in cross-language fact-checking.Information Processing & Management, 63 (4):104616, 2026

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.347062Z

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Observation 1df22fd9-8897-4e5a-961d-870a776e0235 · outbound

This paper cites Matching networks for one shot learning.Advances in neural information processing systems, 29, 2016.

Meta-Learning Preferences for Multilingual LLM Alignment Matching networks for one shot learning.Advances in neural information processing systems, 29, 2016

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.260193Z

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Observation 684223ad-b5e2-423b-8895-23f299205330 · outbound

This paper cites Pangea: A fully open multilingual multimodal llm for 39 languages.

Meta-Learning Preferences for Multilingual LLM Alignment Pangea: A fully open multilingual multimodal llm for 39 languages

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.483653Z

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Observation 8da3d815-7164-449f-9afb-35f55a83bc06 · outbound

This paper cites Reinforcement Learning for LLM Post-Training: A Survey.

Meta-Learning Preferences for Multilingual LLM Alignment Reinforcement Learning for LLM Post-Training: A Survey

Reference 55

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Observation f7751a00-c185-43d9-b02d-8aa291d2a240 · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

Meta-Learning Preferences for Multilingual LLM Alignment HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.597690Z

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Observation f39a01b4-4e6e-45ee-80e2-bcef15ad409b · outbound

This paper cites an unresolved cited work.

Meta-Learning Preferences for Multilingual LLM Alignment Unresolved cited work

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.543048Z

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Observation 896c10fe-1119-449a-a3de-99e6bfe48471 · outbound

This paper cites anycross-lingual preprocessing dominates target-only adaptation by a log(RSFTµτ /σ2) factor in adaptation step count.

Meta-Learning Preferences for Multilingual LLM Alignment anycross-lingual preprocessing dominates target-only adaptation by a log(RSFTµτ /σ2) factor in adaptation step count

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.873054Z

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Observation b1d58992-f54d-4c64-be46-62eb162275c0 · outbound

This paper cites Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B.

Meta-Learning Preferences for Multilingual LLM Alignment Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.686669Z

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Observation 11f66626-ed33-4858-8b14-f6b3857ae188 · outbound

This paper cites H Impact Statement and Limitations This work proposes a meta-learning approach for LLM preference learning, designed to mitigate the unequal performance across different languages.

Meta-Learning Preferences for Multilingual LLM Alignment H Impact Statement and Limitations This work proposes a meta-learning approach for LLM preference learning, designed to mitigate the unequal performance across different languages

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:17.029024Z

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Observation a538b06c-c7a3-4e7e-b90d-e18ec285db67 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Meta-Learning Preferences for Multilingual LLM Alignment Fine-Tuning Language Models from Human Preferences

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:16.761846Z

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Observation 7a0a1743-c795-41af-bc21-7d20c71987f4 · outbound

This paper cites RLHF Workflow: From Reward Modeling to Online RLHF.

Meta-Learning Preferences for Multilingual LLM Alignment RLHF Workflow: From Reward Modeling to Online RLHF

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T05:36:13.318358Z

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