Paper Citation Record · LEDGER

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers

As of 9 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2607.17696.

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

pith.paper-citation-record.v1
2607.17696 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T17:20:57.487573Z

measured 21 of 21 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 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

21 of 21 outbound references displayed

verified exact1
verified fuzzy0
unresolved19
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e88259f3-3696-4d86-87a1-0c2dd1265edd · outbound

This paper cites Quantifying attention flow in Transformers.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Quantifying attention flow in Transformers

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:54.900207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 776759ae-0f1e-48d2-b0ec-719e19ef29a7 · outbound

This paper cites Zico Kolter.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Zico Kolter

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:55.007416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f3b9f5e-f44e-4af2-bc01-cfc82c0eaf6c · outbound

This paper cites A theory of first order mean field type control problems and their equations.Journal of the European Mathematical Society, published online first, 2026.doi:10.4171/JEMS/1781.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers A theory of first order mean field type control problems and their equations.Journal of the European Mathematical Society, published online first, 2026.doi:10.4171/JEMS/1781

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:55.133168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29ca33ba-a9f5-4e72-b6c5-89d93651f7f4 · outbound

This paper cites Kovachki, Matthew E.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Kovachki, Matthew E

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:55.215812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa23238d-0d7d-4fc3-92b0-3613aa60e0bb · outbound

This paper cites an unresolved cited work.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:55.392035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5158a561-4b8c-4fe2-8172-4df728432cfa · outbound

This paper cites Chowdhury.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Chowdhury

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:55.684113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 776145bd-0a57-4cb9-8941-a4867dbbeef3 · outbound

This paper cites A mean-field optimal control formulation of deep learning.Research in the Mathematical Sciences, 6:10, 2019.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers A mean-field optimal control formulation of deep learning.Research in the Mathematical Sciences, 6:10, 2019

Reference 7

Resolution: malformed identifier; no resolver link, observed 2026-08-01T17:20:55.832662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 15faec76-6ade-4886-af12-b398f4a36505 · outbound

This paper cites an unresolved cited work.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:55.982658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 002eb128-9ed0-4f4e-a124-55673da6c26d · outbound

This paper cites Deep residual learning for image recognition.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Deep residual learning for image recognition

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:56.130675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 098ac963-1e0d-4bc9-9bac-a4a18b75d13e · outbound

This paper cites Robust Learning with Jacobian Regularization.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Robust Learning with Jacobian Regularization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:56.239727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 054af153-8253-412e-80ba-1e8af106f57c · outbound

This paper cites Found in the middle: Calibrating positional attention bias improves long context utilization.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Found in the middle: Calibrating positional attention bias improves long context utilization

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:56.354880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4278341f-db5f-440d-9233-edf5378a04ed · outbound

This paper cites A First-Order Mean Field Control Analysis of Transformer Layers under Cross-Entropy Training.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers A First-Order Mean Field Control Analysis of Transformer Layers under Cross-Entropy Training

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-01T17:23:25.978116Z

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 81510874-97ac-4e6e-ae0a-c372c23e9411 · outbound

This paper cites A Mean-Field Analysis of Multi-Head Self-Attention under Cross-Entropy Training.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers A Mean-Field Analysis of Multi-Head Self-Attention under Cross-Entropy Training

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:56.635916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbb6b0c5-7d8f-41e0-a2da-ba27f7a71589 · outbound

This paper cites On uniform-in-time diffusion approximation for stochastic gradient descent.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers On uniform-in-time diffusion approximation for stochastic gradient descent

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:56.747106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38ebb004-04ab-45c7-998d-434a610b667d · outbound

This paper cites Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:56.866046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c7ddb95-aba9-46d3-9556-beaf411fb8e7 · outbound

This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:57.042332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e11e30e7-0386-42c6-a8d4-f89784c12202 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:57.135984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2a49e68-85fa-45c5-9732-f89cc182108c · outbound

This paper cites Axiomatic attribution for deep networks.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Axiomatic attribution for deep networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:57.251361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ca088ae-83f0-4712-8f71-a94d28f4cd8c · outbound

This paper cites Attention Is All You Need.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Attention Is All You Need

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:57.338293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 987fa90e-45bf-442d-af2b-cd939766aacc · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Efficient Streaming Language Models with Attention Sinks

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:57.487573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9ddb53a-6122-4ab2-bd0d-536ab390af50 · outbound

This paper cites Neural Ordinary Differential Equations.

An Adjoint-Sensitivity Framework for Lost-in-the-Middle Phenomena in Causal Residual Transformers Neural Ordinary Differential Equations

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-01T17:20:55.540688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.