Paper Citation Record · LEDGER

Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2406.16008.

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

pith.paper-citation-record.v1
2406.16008 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:11:43.150444Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T19:03:51.861337Z

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 20482803-7ae3-4de3-8af2-e4ec0590e16c · 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: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-08T16:11:43.150444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3c009de-85da-41f0-958d-642967c03868 · inbound

Seed-Coder: Let the Code Model Curate Data for Itself cites this paper.

Seed-Coder: Let the Code Model Curate Data for Itself Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:56.761018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22837b0d-2bab-4f31-b0af-1c45807672f9 · 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: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:55.216298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eac51094-3220-4400-93b1-6146dc042c35 · inbound

FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation cites this paper.

FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:06.878537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c0bacf0-8143-4d41-aa1c-0ab6beed13a1 · inbound

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions cites this paper.

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T05:42:30.968525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ad5c4ee-c0c0-4af9-a099-3504c9e9c4eb · inbound

Small Encoders Can Rival Large Decoders in Detecting Groundedness cites this paper.

Small Encoders Can Rival Large Decoders in Detecting Groundedness Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T22:33:28.186857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcc089ca-24e8-4f62-97ff-4b0d2bceee05 · inbound

MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts cites this paper.

MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:49.542794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1ec6dfa-d253-41e6-b1d4-5227cc94aacd · inbound

Mitigating Coordinate Prediction Bias from Positional Encoding Failures cites this paper.

Mitigating Coordinate Prediction Bias from Positional Encoding Failures Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T05:12:23.560342Z

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.

Observation 21c82d53-59e7-43c9-a39a-3390bc96ea58 · inbound

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure cites this paper.

The PICCO Framework for Large Language Model Prompting: A Taxonomy and Reference Architecture for Prompt Structure Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:03:12.523162Z

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.

Observation 47836dd8-1377-408f-8913-f5508b1c07f3 · 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: Calibrating Positional Attention Bias Improves Long Context Utilization

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:03:51.862903Z

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.