Paper Citation Record · LEDGER

APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2401.06761.

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

pith.paper-citation-record.v1
2401.06761 v1

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 2026-08-18T06:34:40.430872+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:16:25.458140Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T08:08:08.943732Z

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 fe5c6a1d-3003-45aa-9ab8-0b5b3257331f · inbound

A Survey on Efficient Inference for Large Language Models cites this paper.

A Survey on Efficient Inference for Large Language Models APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:39:33.400827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0213c626-11d8-4b42-8f9b-b32d2e5835fd · inbound

ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools cites this paper.

ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:08:09.750717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b1eecf81-69cf-4976-a80b-7ce097b47384 · inbound

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

Advancing Decoding Strategies: Enhancements in Locally Typical Sampling for LLMs APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T11:16:25.458140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbabbb8a-63ea-4b2f-9bf9-b985b094e807 · inbound

Pipelined Decoder for Efficient Context-Aware Text Generation cites this paper.

Pipelined Decoder for Efficient Context-Aware Text Generation APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T21:49:37.869188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85861b8f-65e1-4bb6-9607-8a27998040e9 · inbound

Breaking the Autoregressive Chain: Hyper-Parallel Decoding for Efficient LLM-Based Attribute Value Extraction cites this paper.

Breaking the Autoregressive Chain: Hyper-Parallel Decoding for Efficient LLM-Based Attribute Value Extraction APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:51:25.714733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f9fbca43-4364-4c65-9125-8dc11a38a7de · inbound

PopPy: Opportunistically Exploiting Parallelism in Python Compound AI Applications cites this paper.

PopPy: Opportunistically Exploiting Parallelism in Python Compound AI Applications APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-20T08:08:08.946569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.