Paper Citation Record · LEDGER

Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2502.14458.

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

pith.paper-citation-record.v1
2502.14458 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 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 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:29.326487Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a9cda434-3e22-4b3e-baa3-d41ef015c255 · inbound

Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism cites this paper.

Understanding the Skill Gap in Recurrent Language Models: The Role of the Gather-and-Aggregate Mechanism Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T11:17:29.326487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e4daf09-9bf0-491f-a2e0-9bc9cc77ec6a · inbound

A Survey on Latent Reasoning cites this paper.

A Survey on Latent Reasoning Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T19:14:22.426273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 800aec82-b73b-4414-b839-fcd4fd96f25c · inbound

SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba cites this paper.

SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:46:12.467820Z

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 2fd88c32-d7b5-4ba0-bdaa-eeb02765e86c · inbound

MAR: Efficient Large Language Models via Module-aware Architecture Refinement cites this paper.

MAR: Efficient Large Language Models via Module-aware Architecture Refinement Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-16T10:12:43.033292Z

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 a9698443-5585-427f-a1f2-fe0528554420 · inbound

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

Attention to Mamba: A Recipe for Cross-Architecture Distillation Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-13T23:08:24.958595Z

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 a8ca6c25-0b43-4ad1-be26-b79114689e71 · inbound

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling cites this paper.

Long-Context Aware Upcycling: A New Frontier for Hybrid LLM Scaling Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T22:01:10.875858Z

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 43ceba5a-1c6b-4f3d-ab50-5ab46c922b4a · inbound

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

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 110

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:32:46.696626Z

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 fe18b65a-dc66-4d42-b0c0-5e322cdb8030 · inbound

Morphing into Hybrid Attention Models cites this paper.

Morphing into Hybrid Attention Models Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-30T08:44:27.964101Z

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 d39b3710-a3e0-4a4b-adc2-27a39eb5882b · inbound

The Key to Going Linear: Analysis-Driven Transformer Linearization cites this paper.

The Key to Going Linear: Analysis-Driven Transformer Linearization Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-07-09T01:45:50.801202Z

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 e6133297-6749-42d7-bb0d-11fb83897860 · inbound

Raven: High-Recall Sequence Modeling with Sparse Memory Routing cites this paper.

Raven: High-Recall Sequence Modeling with Sparse Memory Routing Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-01T02:44:00.629498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.