Paper Citation Record · LEDGER

How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 33 inbound Pith citation observations for arXiv:2302.09210.

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

pith.paper-citation-record.v1
2302.09210 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:32:27.810628Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

187
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 94b9e3e2-2b4e-4279-ad24-3ede76a9f8a3 · inbound

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate cites this paper.

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-14T00:00:15.884284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0e89f9f4-fe39-4c91-8a25-cee6e716fd93 · inbound

Low-Resource Languages Jailbreak GPT-4 cites this paper.

Low-Resource Languages Jailbreak GPT-4 How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T09:24:14.011839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c81f9268-37b8-4a8b-b2cf-503fea5af899 · inbound

Benchmark Data Contamination of Large Language Models: A Survey cites this paper.

Benchmark Data Contamination of Large Language Models: A Survey How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:10:40.965343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b395d7d1-40bd-42f6-a663-405cbea4383f · inbound

The Prompt Report: A Systematic Survey of Prompt Engineering Techniques cites this paper.

The Prompt Report: A Systematic Survey of Prompt Engineering Techniques How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:16:17.946339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 812e7b30-4b8c-4b63-a429-d2be37e609b6 · inbound

Towards AI-driven Sign Language Generation with Non-manual Markers cites this paper.

Towards AI-driven Sign Language Generation with Non-manual Markers How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-08T18:32:27.810628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 494cdbe5-55a6-465b-baa5-380b4909a6eb · inbound

Universal Model Routing for Efficient LLM Inference cites this paper.

Universal Model Routing for Efficient LLM Inference How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T23:48:00.942127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feb0859f-6396-46da-ad35-4f61479df4bf · inbound

Small Language Models in the Real World: Insights from Industrial Text Classification cites this paper.

Small Language Models in the Real World: Insights from Industrial Text Classification How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:09:53.633654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcfcf841-0755-4c5a-b9ae-a16ca4b2a634 · inbound

Compensating for Data with Reasoning: Low-Resource Machine Translation with LLMs cites this paper.

Compensating for Data with Reasoning: Low-Resource Machine Translation with LLMs How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:15:32.499378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d361a085-7952-44c9-9f1f-c9d12e927a1f · inbound

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity cites this paper.

Beyond Semantic Entropy: Boosting LLM Uncertainty Quantification with Pairwise Semantic Similarity How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T12:14:01.593619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0a85456-5aa3-479c-bc77-fb2760ebe846 · inbound

Exploring In-context Example Generation for Machine Translation cites this paper.

Exploring In-context Example Generation for Machine Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:08:51.966709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f15c9f74-ebdd-4959-aa1f-36ddff6893a4 · inbound

Prompting LLMs: Length Control for Isometric Machine Translation cites this paper.

Prompting LLMs: Length Control for Isometric Machine Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T10:37:57.549257Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43b41472-3c25-4441-a101-1f1dcfe7eb14 · inbound

Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models cites this paper.

Beyond the Sentence: A Survey on Context-Aware Machine Translation with Large Language Models How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:33:49.990491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60a38528-020e-4e66-aa65-1c05b487cd3e · inbound

TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration cites this paper.

TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:18:25.074851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6e3f251-1ffb-4d9f-adb1-5fd8e2ad0803 · inbound

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons cites this paper.

Are Large Language Models Capable of Deep Relational Reasoning? Insights from DeepSeek-R1 and Benchmark Comparisons How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T21:52:51.306115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 116a8329-64a5-4a66-a869-594924b913b2 · inbound

Invariant-based Robust Weights Watermark for Large Language Models cites this paper.

Invariant-based Robust Weights Watermark for Large Language Models How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T18:33:04.299795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 057de0a2-a0d8-48b4-9f1c-a0f925420254 · inbound

LLMCup: Ranking-Enhanced Comment Updating with LLMs cites this paper.

LLMCup: Ranking-Enhanced Comment Updating with LLMs How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:58.268546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d7dc0f7-0807-4310-8ab8-8405aa7d5649 · inbound

Psychology-Driven Enhancement of Humour Translation cites this paper.

Psychology-Driven Enhancement of Humour Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:04:30.715145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6d17730-4fcb-4a9f-a41c-dfe03d0a2f74 · inbound

How Important is `Perfect' English for Machine Translation Prompts? cites this paper.

How Important is `Perfect' English for Machine Translation Prompts? How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T17:56:59.487900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e568ebdf-ced8-40b1-b9fd-8e1c27a07fb9 · inbound

Toxicity-Aware Few-Shot Prompting for Low-Resource Singlish Translation cites this paper.

Toxicity-Aware Few-Shot Prompting for Low-Resource Singlish Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 2022

Resolution: malformed identifier; no resolver link, observed 2026-08-06T17:03:23.953099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cdd74d53-5673-4387-b47e-707c26cb6546 · inbound

ML2B: Benchmarking LLMs on Cross-Lingual ML Pipeline Generation cites this paper.

ML2B: Benchmarking LLMs on Cross-Lingual ML Pipeline Generation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T14:52:46.813328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

$M^2PO$: Multi-Perspective Multi-Pair Preference Optimization for Machine Translation cites this paper.

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

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T09:50:04.149883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24592cb2-1a7b-4476-a411-7f716b6cd467 · inbound

Translation Heads: Disentangling meaning from language in LLM-based machine translation cites this paper.

Translation Heads: Disentangling meaning from language in LLM-based machine translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 624

Resolution: unresolved; no resolver link, observed 2026-08-03T04:36:22.886085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 191b6ffb-a0e1-4e0a-aa44-5505c0e6de52 · inbound

Mining Large Language Models for Low-Resource Language Data: Comparing Elicitation Strategies for Hausa and Fongbe cites this paper.

Mining Large Language Models for Low-Resource Language Data: Comparing Elicitation Strategies for Hausa and Fongbe How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T11:11:06.292069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation dc02485f-4953-43b5-bbce-83aca5698a2d · inbound

When Does Data Augmentation Help? Evaluating LLM and Back-Translation Methods for Hausa and Fongbe NLP cites this paper.

When Does Data Augmentation Help? Evaluating LLM and Back-Translation Methods for Hausa and Fongbe NLP How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:41:01.372352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 684a4765-ed36-46d7-9de6-858fa62850f7 · inbound

RouteLMT: Learned Sample Routing for Hybrid LLM Translation Deployment cites this paper.

RouteLMT: Learned Sample Routing for Hybrid LLM Translation Deployment How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 11

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T19:31:07.284253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4191e5a3-e3cc-478a-9bf3-2d237d969891 · inbound

Nsanku: Evaluating Zero-Shot Translation Performance of LLMs for Ghanaian Languages cites this paper.

Nsanku: Evaluating Zero-Shot Translation Performance of LLMs for Ghanaian Languages How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T17:36:04.711279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a127a3fe-4c61-4403-b283-82a47d0b867c · inbound

Evaluating Chinese Ambiguity Understanding in Large Language Models cites this paper.

Evaluating Chinese Ambiguity Understanding in Large Language Models How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:48:57.153851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f219b475-4eec-43d4-a9c7-85307df31d76 · inbound

From Outliers to Errors: Auditing Pali-to-English LLM Translations with Multi-Reference Adjudication cites this paper.

From Outliers to Errors: Auditing Pali-to-English LLM Translations with Multi-Reference Adjudication How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 24

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T17:12:24.313231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a368c759-4522-4c51-8529-51d29a603c4d · inbound

MC-PDD: Masked Corpus-Level Pretraining Data Detection for Black-Box Large Language Models cites this paper.

MC-PDD: Masked Corpus-Level Pretraining Data Detection for Black-Box Large Language Models How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T20:57:23.331813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7c4de206-b253-4fd2-b163-f53012c504ef · inbound

Evaluating Large Language Models for Hausa and Fongbe Machine Translation: Benchmarks, Failures, and Metric Reliability cites this paper.

Evaluating Large Language Models for Hausa and Fongbe Machine Translation: Benchmarks, Failures, and Metric Reliability How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T08:29:41.924681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cf2c5ba0-c58b-4232-8935-9b2efd4d0676 · inbound

The Role of Prompt Language and Translation-Theory-Driven Prompts in Large Language Models: A Case Study on Spanish-Chinese Journalistic Translation cites this paper.

The Role of Prompt Language and Translation-Theory-Driven Prompts in Large Language Models: A Case Study on Spanish-Chinese Journalistic Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-12T04:26:45.127419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9c55aaa-795a-41f8-96da-262661bc3e85 · inbound

Reasoning Before Translation: Enhancing Legal Machine Translation with Structured Reasoning cites this paper.

Reasoning Before Translation: Enhancing Legal Machine Translation with Structured Reasoning How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T13:15:35.709692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 399b1f58-c927-48c5-abf8-9bab9d29b081 · inbound

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation cites this paper.

Evaluating Prompt Scope and Demonstration Similarity in Local LLM Machine Translation How Good Are GPT Models at Machine Translation? A Comprehensive Evaluation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T00:17:54.133008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.