Paper Citation Record · LEDGER

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression

As of 13 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:2412.16642.

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

pith.paper-citation-record.v1
2412.16642 v2

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:27:43.244031Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:53:40.575460Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T11:53:40.721059Z

Reference resolution

21 of 21 outbound references displayed

verified exact0
verified fuzzy6
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation df95277d-80a4-4d91-a0ea-320ca6af8b25 · outbound

This paper cites Compression Represents Intelligence Linearly.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Compression Represents Intelligence Linearly

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.188827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b23d894d-9ad1-4b35-a56e-6f0a8a8fb56d · outbound

This paper cites Training LLMs over Neurally Compressed Text.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Training LLMs over Neurally Compressed Text

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.196823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b13ba405-83cd-43e8-98a6-f4b1e15a97b5 · outbound

This paper cites Decoupled Weight Decay Regularization.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Decoupled Weight Decay Regularization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.201033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5bdfea5-b1b3-4450-a838-e90c83b15968 · outbound

This paper cites Tokenization Is More Than Compression.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Tokenization Is More Than Compression

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.216274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1d11021-7384-424a-980f-341beec7394d · outbound

This paper cites LLMZip: Lossless Text Compression using Large Language Models.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression LLMZip: Lossless Text Compression using Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.228319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af8d2de1-729e-4cc4-913d-2a87bd538d98 · outbound

This paper cites HiRA is configured with a single bypass branch and a rank set to four times the main branch’s dimension, which has been proved as the optimal configuration in the main paper.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression HiRA is configured with a single bypass branch and a rank set to four times the main branch’s dimension, which has been proved as the optimal configuration in the main paper

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:27:43.437685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0e8dc3ba-9355-463a-9134-437be4a77efd · outbound

This paper cites However, these models typically involve excessive computational complex- ity.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression However, these models typically involve excessive computational complex- ity

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:27:43.423612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c30d724f-1152-4c47-984f-6cf9e2cfe3af · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression LLaMA: Open and Efficient Foundation Language Models

Reference 1948

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.224343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f2435fc-7ee8-4298-b614-07ff5bdb99c2 · outbound

This paper cites https://xiph.org/flac/.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression https://xiph.org/flac/

Reference 2001

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:27:43.448697Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 88e97eb5-eb70-423f-983b-63a9f0fae2f8 · outbound

This paper cites Cambridge University Press.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Cambridge University Press

Reference 2003

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:27:43.471081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 88ad349e-2fdc-4fae-a78f-4f45bdfce480 · outbound

This paper cites In 2009 IEEE conference on computer vision and pattern recognition, 248–255.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression In 2009 IEEE conference on computer vision and pattern recognition, 248–255

Reference 2009

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:27:43.483500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9b7ffd01-e992-4901-8236-a3d4abbaef16 · outbound

This paper cites Asymmetric numeral systems: entropy coding combining speed of Huffman coding with compression rate of arithmetic coding.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Asymmetric numeral systems: entropy coding combining speed of Huffman coding with compression rate of arithmetic coding

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.172829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85f99ebc-2ce3-463c-8383-21ca209df313 · outbound

This paper cites In 2015 IEEE international conference on acoustics, speech and signal processing (ICASSP), 5206–5210.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression In 2015 IEEE international conference on acoustics, speech and signal processing (ICASSP), 5206–5210

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:27:43.459912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5e38163e-5a17-4ebe-84df-1e707a02d8da · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Neural Machine Translation of Rare Words with Subword Units

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.220306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af97930e-e8a5-4550-a5d5-63d11dfd9152 · outbound

This paper cites Attention Is All You Need.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Attention Is All You Need

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.231973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6e7f81b-11fc-4bfa-9e11-d14954e80f45 · outbound

This paper cites Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.164297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fdd98e8-8c4b-47c1-8297-3162041e66c3 · outbound

This paper cites Scaling Laws for Neural Language Models.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Scaling Laws for Neural Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.192827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d2ad5bb-5338-4734-977d-386f3cdc1aaf · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression LoRA: Low-Rank Adaptation of Large Language Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.185037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a31ecf3e-7112-4151-8e2b-fae314bb27ca · outbound

This paper cites Training Compute-Optimal Large Language Models.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Training Compute-Optimal Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.181213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebad80f3-de69-426c-b1b9-ea113b076162 · outbound

This paper cites RWKV: Reinventing RNNs for the Transformer Era.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression RWKV: Reinventing RNNs for the Transformer Era

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.212408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf385d6d-6b11-48ed-b578-cfeab89f0e9c · outbound

This paper cites Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance.

L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression Unpacking Tokenization: Evaluating Text Compression and its Correlation with Model Performance

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T10:27:43.177121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 639576fa-76c9-4b77-abe9-40f11599dda2 · inbound

A Survey of RWKV cites this paper.

A Survey of RWKV L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text Compression

Reference 263

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:53:40.726782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.