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Paper Citation Record · LEDGER

Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2410.13835.

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

pith.paper-citation-record.v1
2410.13835 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:54:22.643035Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 262c214b-3e81-412f-81c8-1d78c7c0890b · inbound

When Attention Sink Emerges in Language Models: An Empirical View cites this paper.

When Attention Sink Emerges in Language Models: An Empirical View Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-16T17:41:03.853766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-16T17:41:03.674759Z digest=sha256:715df18df55f3383a20e23510f78a2a93c9be92578dbfd04ec5791ab96ea5962

Observation ca337ddb-00d4-49cc-a2a2-caf5602bebf9 · inbound

RotateKV: Accurate and Robust 2-Bit KV Cache Quantization for LLMs via Outlier-Aware Adaptive Rotations cites this paper.

RotateKV: Accurate and Robust 2-Bit KV Cache Quantization for LLMs via Outlier-Aware Adaptive Rotations Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-10T14:54:22.643035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:54:22.643035Z digest=sha256:ee9476b4594279f1ffb7fda4fd67a8d224ba4547a25312c31dedfdc420e7f69a

Observation 567a46fb-426a-49f0-86f3-762340c2edb4 · inbound

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse cites this paper.

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-16T08:47:37.184210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-16T08:47:29.236561Z digest=sha256:ee6d8b9856241ba9765854d84232f77eadd51c04b07f0d25fa09798c99589276

Observation 003e22ec-6a54-4df1-87fe-80dfe421c7c1 · inbound

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse cites this paper.

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-03T05:50:23.598961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:50:23.598961Z digest=sha256:0654ef96be996ff4e818d604f4ea74c14779076dd282e8df2be09c34fbe07063

Observation eff0441d-5568-494d-851a-bcb9b289c353 · inbound

A Structural Theory of Position Bias in Transformers cites this paper.

A Structural Theory of Position Bias in Transformers Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-02T22:32:01.495636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T22:32:01.495636Z digest=sha256:89e8bbf69dcd7083cda5478a8dd7f097f936c00faf2a81c9d887ff6568a9c6cd

Observation 8a71185b-c6a3-4de8-ab81-2353bb781396 · inbound

Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation cites this paper.

Attention Sink in Transformers: A Survey on Utilization, Interpretation, and Mitigation Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 163

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:05:58.291708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T16:17:09.834609Z digest=sha256:2bb1a82fcb6919035f5c1827605aadf4f688a841d21b2027f89ec6d415d9ae81

Observation 3cf4f915-e0c0-4841-b2c1-d644b29341ab · inbound

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning cites this paper.

LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:20:10.524206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-05-10T11:17:43.769244Z digest=sha256:86b598dcf853b33e91b6f37e3d6f6b77e0cd839c7aea0e6a30cd9ee5fa8dd526

Observation 5bcaaeb4-84f8-49a7-a303-44f426b2c0d2 · inbound

OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond cites this paper.

OScaR: The Occam's Razor for Extreme KV Cache Quantization in LLMs and Beyond Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:58:07.507093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-20T07:57:51.032025Z digest=sha256:99c370f9485d1a70c5c7ebeb33a45af2584829d33f68667dd0f518536de3d34f

Observation a72ce87c-b991-4e11-994c-9c6b4559bf25 · inbound

Transformers Provably Learn to Internalize Chain-of-Thought cites this paper.

Transformers Provably Learn to Internalize Chain-of-Thought Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:33:30.533348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-29T14:29:10.010212Z digest=sha256:2e4587794a3aab751faa6e73bb96d6581068ab2a85cf1f8eaf18cc6bada6aa0f

Observation 699ccffe-1720-44be-b526-6b78a08d266b · inbound

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 87

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T23:32:46.644793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-28T23:29:02.457697Z digest=sha256:35ff3a10de19632a972139cf4edf3e63128f9d17d10173cf94f3f1b370bec342

Observation cb0bc544-4789-4ac4-b9c9-c1dda6bd2890 · inbound

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers Active-Dormant Attention Heads: Mechanistically Demystifying Extreme-Token Phenomena in LLMs

Reference 160

Resolution
verified exact
arxiv_id, observed 2026-06-28T23:32:47.274391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-28T23:29:02.457697Z digest=sha256:608d9a509984700018abadef4044d6025401a19c8b0c24186a243f0b20cbb554