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Paper Citation Record · LEDGER

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation

As of 13 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.29287.

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

pith.paper-citation-record.v1
2607.29287 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T10:03:46.886252Z

measured 24 of 24 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

24 of 24 outbound references displayed

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  • verified fuzzy0
  • unresolved22
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fd44e3c4-c73c-44f6-a920-0b47b3126af2 · outbound

This paper cites an unresolved cited work.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Unresolved cited work

Reference 1

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source=pdf_text observed=2026-08-03T10:03:44.862986Z digest=sha256:4c5ae95ff0c5e1046a8940928b522b5770e7e165e3c8300244fa3cca732e1b19

Observation d6de92e1-ec76-4ba7-be77-da2fc07ddbe1 · outbound

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

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

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source=pdf_text observed=2026-08-03T10:03:44.541057Z digest=sha256:8fabd976af9450f96456ca77173070ad3e95f4c873fef16446743bf4c4b74da2

Observation 9466be78-4f07-4f82-af5d-21f654500c52 · outbound

This paper cites New Trends for Modern Machine Translation with Large Reasoning Models.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation New Trends for Modern Machine Translation with Large Reasoning Models

Reference 3

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source=pdf_text observed=2026-08-03T10:03:44.664106Z digest=sha256:638ddda9b78f6a8db54e3fdcada51893bbb5490008e1df9542e7fcd9ba2b8ba6

Observation 7ab47e0b-b658-4ca7-a942-8cd89a36259e · outbound

This paper cites easy", "medium.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation easy", "medium

Reference 4

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source=pdf_text observed=2026-08-03T10:03:45.099524Z digest=sha256:b9d4d813545a5806434489977c2ae03443f2ea5f68b7b0ad4abcd7cba9238291

Observation 893fe5d5-6dfa-4332-b1a9-1bcab147e99a · outbound

This paper cites cited Vietnamese data.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation cited Vietnamese data

Reference 5

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source=pdf_text observed=2026-08-03T10:03:46.184388Z digest=sha256:8ede8aa2209fc7235b9eeaf9a9969e81ade13521de4c51235dfb2277ba727b21

Observation dd2f3fed-6ef4-4f10-8bdc-d424e6b5401d · outbound

This paper cites an unresolved cited work.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Unresolved cited work

Reference 6

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source=pdf_text observed=2026-08-03T10:03:44.963352Z digest=sha256:f0c7e8eac59f4c44e90dcf02d22356d3594e198fc06b0d91f9b510099c77dee7

Observation 89c2b668-921e-431b-94e9-5328fa07d08c · outbound

This paper cites an unresolved cited work.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Unresolved cited work

Reference 7

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source=pdf_text observed=2026-08-03T10:03:45.054615Z digest=sha256:6a0414c8bdcbfc19c4e65063a732929713ad198e7e22404c6b046244563e78be

Observation 1782e714-9aa9-4aae-89d9-4477d4fc0b18 · outbound

This paper cites 根据越南方面的资料,西沙群岛和南沙群岛自古以 来就是中国的领土。.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation 根据越南方面的资料,西沙群岛和南沙群岛自古以 来就是中国的领土。

Reference 8

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source=pdf_text observed=2026-08-03T10:03:46.886252Z digest=sha256:2edc4ac235cdd5573aa4a44f683e033e0c7041ba967f458bbf45e9b1fe0c052e

Observation 614938e8-971a-454f-a022-c5080b90fe3e · outbound

This paper cites 外门弟子”为宗门中层级较低的弟子,常见翻译为“outer sect disciples.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation 外门弟子”为宗门中层级较低的弟子,常见翻译为“outer sect disciples

Reference 9

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source=pdf_text observed=2026-08-03T10:03:45.292445Z digest=sha256:96ca4d839c9b16f5e75e3cdf5d44150d86e0bbc9395e01907bdbc983c54ef726

Observation 2672c3a2-0e41-4f5d-b87c-0a04ffae8b1b · outbound

This paper cites 现在”表明当前动作,但考虑到小说常用过去时,主句采用了“needed to find.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation 现在”表明当前动作,但考虑到小说常用过去时,主句采用了“needed to find

Reference 10

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source=pdf_text observed=2026-08-03T10:03:45.446254Z digest=sha256:892dcc14f1cf0831567121cd115bff9a379942c5631e1bdd272f52ad58d866e5

Observation a1daa1eb-8345-4feb-a6b9-c290ed3d700b · outbound

This paper cites 现在他要找的就是…….

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation 现在他要找的就是……

Reference 11

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source=pdf_text observed=2026-08-03T10:03:45.521859Z digest=sha256:b43b711bc6b0594c86f7d7e58f7279cfbe83101728943e35b60b5af37112b112

Observation 3047dbcf-e5ff-4aee-a240-3b795bf47099 · outbound

This paper cites thought" and.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation thought" and

Reference 12

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source=pdf_text observed=2026-08-03T10:03:44.778468Z digest=sha256:7fffa7083783b071249ada10ec058c3e848b2f9be48336cfa425ed878eb74887

Observation bfe2508f-468b-406c-a931-bb59ada5fed5 · outbound

This paper cites Now, he needed to find the place where the outer sect disciples cultivated.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Now, he needed to find the place where the outer sect disciples cultivated

Reference 13

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source=pdf_text observed=2026-08-03T10:03:45.610845Z digest=sha256:4c22a875d66bd5822415c76e9050a779abdcd47d5d5603b90298f9d47285ee63

Observation 16996e39-1590-4228-9072-9f0b86ced8b5 · outbound

This paper cites chargé d'affaires ad interim.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation chargé d'affaires ad interim

Reference 14

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source=pdf_text observed=2026-08-03T10:03:45.731071Z digest=sha256:ebf6aa0f6ec155a468b9f86e0fe6543a7b5ba2eadea24023a71ec5ce312978f4

Observation 2c750159-f622-4e37-9db5-529466094b81 · outbound

This paper cites solemnly stated.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation solemnly stated

Reference 15

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source=pdf_text observed=2026-08-03T10:03:45.903909Z digest=sha256:3ed860b7cec17ba5fb4fcf6cdfa96edf6c4ec2f5ac3d05b49be01e046f35f03a

Observation 35058c63-b336-48bb-9c86-d75210558eec · outbound

This paper cites Vietnamese data.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Vietnamese data

Reference 16

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source=pdf_text observed=2026-08-03T10:03:45.974928Z digest=sha256:3a60e3f00a495a7dbf8f26624cd078e4a6e2dde26f78698106311719e57f94cf

Observation e765c44e-d828-4e2c-a234-c485da0f44e9 · outbound

This paper cites Acting Director.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Acting Director

Reference 17

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source=pdf_text observed=2026-08-03T10:03:46.077535Z digest=sha256:837b1b47c03ac008f4019a36735d6672cf1a57f6a4902e2e8122f3c8a4b9946f

Observation cd869a7a-e188-4e73-a52d-ad45d2199cdf · outbound

This paper cites Song Dynasty.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Song Dynasty

Reference 18

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source=pdf_text observed=2026-08-03T10:03:46.282736Z digest=sha256:2d71d2348ae53a296a4ec13cce9d2b6affa235e2f79197d523310e085b37c029

Observation 5da0cce7-9a49-4784-8a8c-40e11e1e097d · outbound

This paper cites chargé d'affaires ad interim.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation chargé d'affaires ad interim

Reference 19

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source=pdf_text observed=2026-08-03T10:03:46.418765Z digest=sha256:580d2952701615bb83b34cce81eeec14669ad233c02c65cfdec3bd40caa77bb1

Observation 579b5ae7-7dd8-4add-b4ce-aa90bc95d0c5 · outbound

This paper cites During a meeting ... on 15 June 1956.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation During a meeting ... on 15 June 1956

Reference 20

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source=pdf_text observed=2026-08-03T10:03:46.533421Z digest=sha256:88445393ee398df62774592fe4b6f014e1b6db44e6846ca675b09afd44ac5cb1

Observation 54b47ea3-ba6f-4148-b170-fcef9a2d2bc6 · outbound

This paper cites Vietnamese data.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Vietnamese data

Reference 21

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source=pdf_text observed=2026-08-03T10:03:46.627615Z digest=sha256:ee54d65d7c04823c82ba8b0351f7ec16baa54959e922880fe31b6404cc0dd42d

Observation ab174485-dfcc-49b2-9b0a-42bb371e88f8 · outbound

This paper cites acting director.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation acting director

Reference 22

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source=pdf_text observed=2026-08-03T10:03:46.712472Z digest=sha256:d23c3de971665efc351153e01f561b726bfa767c152687c944f36a486a49037e

Observation b05f8faa-9b10-4448-a9fc-849c321abd20 · outbound

This paper cites judging from history.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation judging from history

Reference 23

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source=pdf_text observed=2026-08-03T10:03:46.818546Z digest=sha256:d5df2430c5ec05ccba07c0a8934934931d0a545773b9a9f1bd62ed7f3332ce2c

Observation 390d5ecd-f38e-4676-9b76-7c387541fe69 · outbound

This paper cites Evaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis.

Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation Evaluating o1-Like LLMs: Unlocking Reasoning for Translation through Comprehensive Analysis

Reference 2025

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source=pdf_text observed=2026-08-03T10:03:44.412092Z digest=sha256:28a9ebedefe095676477fe372ad764f76fbdec0459a45b7660795b05fde925f7

Pith citing papers

No inbound Pith citation observations are available.