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Paper Citation Record · LEDGER

Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2104.08771.

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

pith.paper-citation-record.v1
2104.08771 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:45:59.384043Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:27:56.869648Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 31b3a4f7-d5e1-4ab3-b6cf-59849bd93974 · inbound

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-13T11:32:36.935383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T11:32:36.738536Z digest=sha256:b4e35ca8022836c55cf3f14a2482b606a8c4c591ae9997683e3946bbe62ccbb0

Observation e6bd5b49-6839-403b-a668-fbdc7677c71d · inbound

Generalizable Radio-Frequency Radiance Fields for Spatial Spectrum Synthesis cites this paper.

Generalizable Radio-Frequency Radiance Fields for Spatial Spectrum Synthesis Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-23T03:52:29.664581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T03:48:06.278544Z digest=sha256:42e3e120dcd69853e08117995e6be46f31ec33c89d728786d5c2ca6542fe7a3d

Observation fb7ef939-5c21-4a1d-af87-bf16968e097a · inbound

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting cites this paper.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:45:59.384043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:45:59.384043Z digest=sha256:1a26e1c91b69978d56359f5e4fc6f07014965d8cc1f21d97d529676f66972ead

Observation ebe0dc82-6d24-47d1-9a7e-10b1ddef8cf9 · inbound

BlastOFormer: Attention and Neural Operator Deep Learning Methods for Explosive Blast Prediction cites this paper.

BlastOFormer: Attention and Neural Operator Deep Learning Methods for Explosive Blast Prediction Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T13:58:18.949329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:58:18.949329Z digest=sha256:fc6ff84bba87993957a94ceea6e38da26320237314c66709d73a4b8c45b75563

Observation 95e8b8db-8584-4b0c-91fa-6b7c367415db · inbound

TALL -- A Trainable Architecture for Enhancing LLM Performance in Low-Resource Languages cites this paper.

TALL -- A Trainable Architecture for Enhancing LLM Performance in Low-Resource Languages Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T10:32:45.330650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:32:45.330650Z digest=sha256:e3e74d59f76fca82b5d41e2d4d4dbddcd5a38034cb24006385fd45ded1291906

Observation 6102ceff-bbf2-45f1-8b94-602a10a7f861 · inbound

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models cites this paper.

PLoP: Precise LoRA Placement for Efficient Finetuning of Large Models Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T22:50:12.706998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:50:12.706998Z digest=sha256:1df4023220e7f24a8843e939e7fa212ae334270f10a7367cb904f4c5bcc7c2ef

Observation 7021283b-f1d0-4f7b-87bf-90266815e3c6 · inbound

Krul: Efficient State Restoration for Multi-turn Conversations with Dynamic Cross-layer KV Sharing cites this paper.

Krul: Efficient State Restoration for Multi-turn Conversations with Dynamic Cross-layer KV Sharing Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T18:46:57.357120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:46:57.357120Z digest=sha256:2f75bf8fd9da882d256c67b53465d3fa36a6c8394158772dae30b6da9221eaf2

Observation ae4eea82-f5f5-4a74-a509-c016a9ae35b1 · inbound

Causal Fingerprints of AI Generative Models cites this paper.

Causal Fingerprints of AI Generative Models Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-18T15:31:33.686903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T15:28:25.607154Z digest=sha256:51523c3263d1610adeb6e7fdfba0ad73767deeafe8aec3712f886affea890c0e

Observation e69a5714-8108-4508-b397-fc032006951f · inbound

One Prompt, Many Sounds: Modeling Listener Variability in LLM-Based Equalization cites this paper.

One Prompt, Many Sounds: Modeling Listener Variability in LLM-Based Equalization Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-16T14:27:59.206139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T14:26:36.236424Z digest=sha256:6897d34525f4dca10829bbd0e05b9c2c68a828d96aa1356c36b9fed48da998a4

Observation 2a755685-540f-4bba-b0c9-afa0df7593ce · inbound

One Prompt, Many Sounds: Modeling Listener Variability in LLM-Based Equalization cites this paper.

One Prompt, Many Sounds: Modeling Listener Variability in LLM-Based Equalization Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-03T10:39:37.529785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T10:39:37.529785Z digest=sha256:58bd2ce2d7f459b21d48c1a6994524d19e543d372394ac0590d1eb37224bc912

Observation c9f8285b-c8b4-4538-ae47-91d3ff49cc94 · inbound

Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations cites this paper.

Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:01:32.349501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-12T01:21:47.109822Z digest=sha256:b8c0298e48d9f035aea14550655ae5beee46fef6a976b3f100c01aad1730d2c1

Observation 7005529e-ca52-432e-bd59-937f572b9022 · inbound

Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations cites this paper.

Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-13T07:17:28.913162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T07:14:59.491808Z digest=sha256:f20df21e44ee963a34f5717d89b057647152473af8a9994d1b3c2981a67a732f

Observation ed6b878f-c4a1-414a-9687-7578f0441b89 · inbound

Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer cites this paper.

Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-07-03T10:27:56.871192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T09:59:19.332545Z digest=sha256:dc3e9b03667cb2ff013f153b4be8e104941a96ae16b4f985c73869435ec24992