Paper Citation Record · LEDGER

Finetuning Pretrained Transformers into RNNs

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2103.13076.

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

pith.paper-citation-record.v1
2103.13076 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:58:51.297853Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:26:56.591321Z

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 e6dcbff5-3c20-484e-b28c-06119112cac0 · inbound

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads cites this paper.

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads Finetuning Pretrained Transformers into RNNs

Reference 242

Resolution: verified exact; arxiv_id, observed 2026-05-13T10:36:18.328367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation db9ec858-602d-451c-9fa5-9eeb85bb7ab9 · inbound

Massive Activations in Large Language Models cites this paper.

Massive Activations in Large Language Models Finetuning Pretrained Transformers into RNNs

Reference 46

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T07:02:53.871604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 454486f0-dc62-4530-a308-9fe3979295f9 · inbound

LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation cites this paper.

LightTransfer: Your Long-Context LLM is Secretly a Hybrid Model with Effortless Adaptation Finetuning Pretrained Transformers into RNNs

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-23T18:33:19.364814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9c07b291-0a01-4b32-97a8-91d25c9f1e2f · inbound

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention cites this paper.

On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention Finetuning Pretrained Transformers into RNNs

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T04:58:51.297853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8517a5f9-d8ad-4990-b8a4-2f1e35d51633 · inbound

Attention to Mamba: A Recipe for Cross-Architecture Distillation cites this paper.

Attention to Mamba: A Recipe for Cross-Architecture Distillation Finetuning Pretrained Transformers into RNNs

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T23:08:24.886705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 019b1c12-c5d0-4474-a37b-7e61c76e7884 · inbound

Pretraining Recurrent Networks without Recurrence cites this paper.

Pretraining Recurrent Networks without Recurrence Finetuning Pretrained Transformers into RNNs

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:26:56.593090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e7296f9d-cba8-4904-9007-bb33cc31e46a · inbound

Pretraining Recurrent Networks without Recurrence cites this paper.

Pretraining Recurrent Networks without Recurrence Finetuning Pretrained Transformers into RNNs

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-02T12:20:55.664977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.