Paper Citation Record · LEDGER

When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2406.07368.

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

pith.paper-citation-record.v1
2406.07368 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:54:31.027136Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T23:52:49.120111Z

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 320b531b-7454-44da-b713-e61df6029348 · inbound

CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up cites this paper.

CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T10:54:31.027136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c94554d6-a974-4217-8e4f-1c17264422d3 · inbound

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs cites this paper.

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T11:16:25.744942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c00f209-f76d-45a7-af3a-176649b03151 · inbound

DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models cites this paper.

DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

Reference 109

Resolution: unresolved; no resolver link, observed 2026-08-06T17:47:40.284010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b144df7-8c9a-4500-ba33-d383d03d7bc4 · inbound

DistrAttention: An Efficient and Flexible Self-Attention Mechanism on Modern GPUs cites this paper.

DistrAttention: An Efficient and Flexible Self-Attention Mechanism on Modern GPUs When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T14:59:21.394850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4334fd61-d186-4da1-97b9-d008cb97a82a · inbound

Continuous Latent Diffusion Language Model cites this paper.

Continuous Latent Diffusion Language Model When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:10.904962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6c185146-0e92-4076-ac44-43551f7269fc · inbound

RTP-LLM: High-Performance Alibaba LLM Inference Engine cites this paper.

RTP-LLM: High-Performance Alibaba LLM Inference Engine When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:52:49.121631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.