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Paper Citation Record · LEDGER

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages

As of 12 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2412.08090.

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

pith.paper-citation-record.v1
2412.08090 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:18:29.510263Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

38 of 38 outbound references displayed

  • verified exact2
  • verified fuzzy3
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7b2ed780-d071-4eb5-bc07-d472cad763c6 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages , " * write output.state after.block = add.period write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:28.672266Z digest=sha256:f8a32c6b20a394028a7723714b6da50105809ad2f3d1e50906222384e113d8f9

Observation bc24eae3-b072-4037-b587-3e949580bd62 · outbound

This paper cites write newline.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages write newline

Reference 2

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source=arxiv_source observed=2026-08-11T18:18:28.770735Z digest=sha256:7c58f6811a5dce3a9e3e43d03267e284a890e9b2d35f1f98600602ff4c3999de

Observation 6f433e2e-f7b9-43da-8007-158d94b146ad · outbound

This paper cites LinguAlchemy: Fusing Typological and Geographical Elements for Unseen Language Generalization.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages LinguAlchemy: Fusing Typological and Geographical Elements for Unseen Language Generalization

Reference 3

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source=arxiv_source observed=2026-08-11T18:18:28.816609Z digest=sha256:b5ac652e31d52212271ddec801300d10f17ba6f0093c5674df1e46fa28b32204

Observation e241296d-86d8-4fde-9994-558d90a4117a · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-11T18:18:28.822239Z digest=sha256:c5a14ae8fdecd6d82b2278c830f4600dca5120838cbfe5453e49372b192e46de

Observation 35e406b6-22b9-478d-b314-1d2661b80169 · outbound

This paper cites BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer

Reference 5

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source=arxiv_source observed=2026-08-11T18:18:28.828728Z digest=sha256:44a261ef4e0da226e3c3f07b79b00f81fb419f8648d9b23edd0b46796feb5a8a

Observation d18b3534-5dc5-462b-b3db-7bb28c787bc2 · outbound

This paper cites NusaCrowd: Open Source Initiative for Indonesian NLP Resources.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages NusaCrowd: Open Source Initiative for Indonesian NLP Resources

Reference 6

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source=arxiv_source observed=2026-08-11T18:18:28.834812Z digest=sha256:b43c43f36900818d85f3cb863f85277bd976ac55bbf81f53733b9f7d7d029029

Observation ec276eed-7508-44f0-99f8-0fb784937807 · outbound

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

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages LLMs Are Few-Shot In-Context Low-Resource Language Learners

Reference 7

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source=arxiv_source observed=2026-08-11T18:18:28.840021Z digest=sha256:1620c71b1e21d3ecb8718f2647963c37fab0f85799dbc6e01336f974e5bdfc66

Observation 5929b099-7f6d-41ea-94c4-c160645c1062 · outbound

This paper cites A Dataset for Answering Time-Sensitive Questions.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages A Dataset for Answering Time-Sensitive Questions

Reference 8

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source=arxiv_source observed=2026-08-11T18:18:28.845612Z digest=sha256:1fae240f5e5471e650486e22aa2e48ee7ed9df8ed92a87ec476b0a99d5cebb43

Observation 8a96d62e-90ff-4093-85eb-2c8b963a1e38 · outbound

This paper cites R.; Eisenschlos, J.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages R.; Eisenschlos, J

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.022789Z digest=sha256:2c502d740b5d32535db68682c7d12adb8b6e17ca0fadcb567f279be32a4c77c6

Observation ab219242-a3db-4d0d-bb1d-020d1f4a130a · outbound

This paper cites From LLM to NMT: Advancing Low-Resource Machine Translation with Claude.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages From LLM to NMT: Advancing Low-Resource Machine Translation with Claude

Reference 10

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source=arxiv_source observed=2026-08-11T18:18:29.082018Z digest=sha256:fade31fc2533c265fd05b96eafa5588cd55b3940b0756c78662940ef4c6826f8

Observation 060875f3-66e1-4049-b69c-ae969a6e5587 · outbound

This paper cites Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting

Reference 11

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source=arxiv_source observed=2026-08-11T18:18:29.087300Z digest=sha256:f6a26d9780bc1cc831b71a88942ffd1cf44e0dde9286d918babf24f5c2bf7cb4

Observation 02ff9b7f-2437-4b31-ac96-128167bb35fa · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.093435Z digest=sha256:ba4b3a04d57a6914670f85845846277a76d3941f982439269158c7e1457f4842

Observation 80d06269-ee0f-4d30-9541-cb4c21f89712 · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.100015Z digest=sha256:2b07833f1d749ecd64c3e58adf85f0f12e98a221922a2a89a28f4f3496cf6858

Observation f57c9c14-9d92-48cb-9e84-2cb21bf87495 · outbound

This paper cites Mistral 7B.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Mistral 7B

Reference 14

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:29.104949Z digest=sha256:8bd18cf0f79b01d79163142bfb3833e8251b390aff9fb0d488c43b918f8a04f3

Observation 122e8b25-e760-4289-b86a-00406eeced0f · outbound

This paper cites XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples

Reference 15

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.112911Z digest=sha256:4ea89717ff3a8334ba1af778056067a93fcd223a2e9fe976376b79ca996c30ba

Observation 9ded8c27-0574-4db6-b4b6-5edadbc81872 · outbound

This paper cites V.; Mihaylov, T.; Artetxe, M.; Wang, T.; Chen, S.; Simig, D.; Ott, M.; Goyal, N.; Bhosale, S.; Du, J.; Pasunuru, R.; Shleifer, S.; Koura, P.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages V.; Mihaylov, T.; Artetxe, M.; Wang, T.; Chen, S.; Simig, D.; Ott, M.; Goyal, N.; Bhosale, S.; Du, J.; Pasunuru, R.; Shleifer, S.; Koura, P

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.120222Z digest=sha256:85fcc999eac463d73eff50c15ef280608ce7526cd52fc43da6f2ae861582a813

Observation d07e48a7-782d-4e5d-8ad4-7e0fcec4c047 · outbound

This paper cites Few-shot Learning with Multilingual Language Models.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Few-shot Learning with Multilingual Language Models

Reference 17

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source=arxiv_source observed=2026-08-11T18:18:29.126607Z digest=sha256:6b4b2b7de66a75ecb5447ae28d873080b62b165ebbc2b31e687d15ee4cf8fa86

Observation 7371ad37-a1b6-4b9a-9704-c41bf5fe7c16 · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 18

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.132922Z digest=sha256:201027d434150584b405581d5fda085e1e19ac4297760e6cb2becb9860cecc0d

Observation 437506e8-83cc-40ed-8ba5-49d2e97bf5c0 · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 19

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.139678Z digest=sha256:394fc7d6b455eec15056aad033331b78b5e2b1ee4581136600d7853aadb1bdb7

Observation 6a57101f-0b50-4287-b4d9-ab8891a2837b · outbound

This paper cites Crosslingual Generalization through Multitask Finetuning.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Crosslingual Generalization through Multitask Finetuning

Reference 20

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Observation 0b6b0910-9102-4413-98ff-f03b545c53ce · outbound

This paper cites Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts

Reference 21

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source=arxiv_source observed=2026-08-11T18:18:29.150391Z digest=sha256:90e0cf5e9f23928abd430659776e477127d5f72e7b62f3c3c457bd000d8b28e4

Observation e1a943fb-829b-4a05-b6ee-cb1dcaf9e486 · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.156013Z digest=sha256:1b7cfef6f3033d2a8f025091f1430ba56c9b16386af06fcd44762ede3744fe82

Observation 5c8b8831-3211-4278-8c66-2021f9bdd77d · outbound

This paper cites Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers

Reference 23

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Observation ed26186d-a6b7-45ff-84a3-de27ff96a0ed · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 24

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source=arxiv_source observed=2026-08-11T18:18:29.169364Z digest=sha256:da3b4a8bcf20d8c561c57a774590dfc12782f21e0de00aa7748252f0896d70c7

Observation 0944e5c6-8a59-47d4-9e6b-35965900c7b4 · outbound

This paper cites Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 25

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source=arxiv_source observed=2026-08-11T18:18:29.175273Z digest=sha256:5ddab9d3d683141d6cee972e3f4e42aa30e2e14372b6a94d06069b092d88032e

Observation b15acddb-259b-4cba-88ac-8e361b9ce9cf · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 26

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raw_fallback, observed 2026-08-11T18:18:30.234080Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation fa226ba3-3214-4161-af26-2624bdc12d96 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:29.336304Z digest=sha256:a991307140f31f050c499b13723c614667ade498e5d43713a5904a02c572d69b

Observation 89a2204a-b59c-48c9-9151-87d9179ac28d · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 28

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unresolved
raw_fallback, observed 2026-08-11T18:18:30.216445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation ac4a982c-3670-4923-8688-0fb835afff63 · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 29

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unresolved
raw_fallback, observed 2026-08-11T18:18:30.196664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.452800Z digest=sha256:961428b1ad07a463979f175c29a669bcdfee4e5a91b43281c7f3dde713327ddd

Observation f45bd402-7092-4a4d-abf7-646b3aa3bf06 · outbound

This paper cites Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:29.459293Z digest=sha256:fc15b640e2b53238dee916429fcaaecc3f9ccdee8acac2cbe75b47bedb0f8db1

Observation 09b86870-86eb-436f-984c-d3ad5c7e18c1 · outbound

This paper cites Multilingual LLMs are Better Cross-lingual In-context Learners with Alignment.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Multilingual LLMs are Better Cross-lingual In-context Learners with Alignment

Reference 31

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no resolver link, observed 2026-08-11T18:18:29.464807Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:29.464807Z digest=sha256:33fea812af583ff3a91c57a31b375bf92db3c1eb5aa008eab11fb122e1785080

Observation 41ca306d-37bc-4318-b083-f7198a6c18ac · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-11T18:18:30.178585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.469203Z digest=sha256:11f0f2e692e39cd232875dcaa0bb6dce2e40e738a9eba020921dffce5abbb31e

Observation 87b1e28b-0efd-4820-9ec5-ee663bfdbca2 · outbound

This paper cites an unresolved cited work.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Unresolved cited work

Reference 33

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unresolved
raw_fallback, observed 2026-08-11T18:18:30.161678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.474251Z digest=sha256:ee88bee1131087fb49f947107e5c242371b4866f608a012ebe90f4bd93e790a5

Observation ebe0cf59-4e44-4bf2-8dec-cc0bfa702365 · outbound

This paper cites I.; Madotto, A.; Lin, Z.; Liu, R.; Yosinski, J.; and Fung, P.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages I.; Madotto, A.; Lin, Z.; Liu, R.; Yosinski, J.; and Fung, P

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T18:18:30.117878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.479352Z digest=sha256:f9e7a554664daa699b7e896c5addcda4f5532ea4b1a1f3956c38c72ac73508f9

Observation 6173c4a5-d398-46ac-8276-6982552b155a · outbound

This paper cites LEIA: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages LEIA: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-11T18:18:29.643342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T18:18:29.484361Z digest=sha256:d5867171874a1d474cc37425c5ad7eac8ba9a93c3c050597aad1f03dc85852c0

Observation 8b91aba6-bc72-454f-bdcf-a0e35012da68 · outbound

This paper cites Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T18:18:29.491688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:29.491688Z digest=sha256:f7f32f2b5773e879fcb24f4bee86fe7abbeaeca862e2dd274ca00ae8c7bef21f

Observation 38e5b1f5-1d75-43d4-9c03-dde923d5508b · outbound

This paper cites Calibrate Before Use: Improving Few-Shot Performance of Language Models.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Calibrate Before Use: Improving Few-Shot Performance of Language Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-11T18:18:29.504225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:29.504225Z digest=sha256:ff502302c226035c0868b59f34077650826fba5d05d707ccd54656ef29b18ace

Observation 9a52f589-cd42-4ee4-b33b-4fabc4a25354 · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Multilingual LLMs Inherently Reward In-Language Time-Sensitive Semantic Alignment for Low-Resource Languages Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T18:18:29.510263Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:18:29.510263Z digest=sha256:bb127ea188bcbefa149a3467417d76bf16c5b9e526939736eeaa2cadc7d79e53

Pith citing papers

No inbound Pith citation observations are available.