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Paper Citation Record · LEDGER

Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2403.04797.

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

pith.paper-citation-record.v1
2403.04797 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:11:06.403368Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:03:51.895801Z

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 bc7f0121-a965-4810-a53c-e745aad73812 · inbound

Breaking the Stage Barrier: A Novel Single-Stage Approach to Long Context Extension for Large Language Models cites this paper.

Breaking the Stage Barrier: A Novel Single-Stage Approach to Long Context Extension for Large Language Models Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-11T19:11:06.403368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:11:06.403368Z digest=sha256:5ad46b82006d1ebd470d4e787b5a543911deab7adb19692e88a04cd656c071c6

Observation 607a29c2-847b-4ce9-ba6f-87528abaa94b · inbound

On the Emergence of Position Bias in Transformers cites this paper.

On the Emergence of Position Bias in Transformers Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-09T14:04:55.511208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:04:55.511208Z digest=sha256:fa479fff93b66a900157ac4b8d11861fbb6b6db57ba39a49efbef31a93af6ff7

Observation a5cddc6b-4d55-445b-b55f-3672afa053fb · inbound

RoToR: Towards More Reliable Responses for Order-Invariant Inputs cites this paper.

RoToR: Towards More Reliable Responses for Order-Invariant Inputs Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-08T16:11:43.273346Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T16:11:43.273346Z digest=sha256:80444337dbc3355a3c735aae021e93d52d08e1bbf7a1cb0608006163bc03077e

Observation f354a70e-b955-49a9-85cb-217324e57405 · inbound

Pause-Tuning for Long-Context Comprehension: A Lightweight Approach to LLM Attention Recalibration cites this paper.

Pause-Tuning for Long-Context Comprehension: A Lightweight Approach to LLM Attention Recalibration Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-09T18:36:36.917030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:36:36.917030Z digest=sha256:2871ca2fc7d61e15d80ea359a07640a39c41572714ab32670c592983a45d2dd4

Observation bc403ef4-d344-488c-89e7-567b10a05016 · inbound

Mitigating Posterior Salience Attenuation in Long-Context LLMs with Positional Contrastive Decoding cites this paper.

Mitigating Posterior Salience Attenuation in Long-Context LLMs with Positional Contrastive Decoding Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T05:20:55.277154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:20:55.277154Z digest=sha256:2097595ff5687d2d622c4fa32b444ee6ed8ab3bdf7b852b732004551510c2f67

Observation dcf6786a-8089-41d5-9b90-7ec6b163766d · inbound

RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably cites this paper.

RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-19T15:37:37.308801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-19T15:34:09.006815Z digest=sha256:c57c47c4f70218fceea0e91f6a3e17c0a478e40c66368635287434479467f04e

Observation 1fb7f565-fb08-48ef-aca3-76cc7fe235b2 · inbound

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling cites this paper.

Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-06-29T19:03:51.897471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-29T04:59:00.304723Z digest=sha256:5dc58d4e61fe1a5b556f7e588fb491621e993c761cbee2ff75c9c4ca6b25a197

Observation 575b8920-cc8e-49b3-8eaf-0ea8be4ce244 · inbound

AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally cites this paper.

AdaRoPE: Not All Attention Heads Should Rotate and Scale Equally Found in the Middle: How Language Models Use Long Contexts Better via Plug-and-Play Positional Encoding

Reference 18

Resolution
malformed identifier
no resolver link, observed 2026-08-02T12:17:16.344609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T12:17:16.344609Z digest=sha256:fe22ac24e1f16617b0d91585600fe93543185abe4c682d1c02ba20f72f7beaca