Paper Citation Record · LEDGER

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models

As of 24 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2606.18114.

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

pith.paper-citation-record.v1
2606.18114 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T00:55:02.737906Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

verified exact9
verified fuzzy0
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f611d35b-5f50-499b-bbd8-c6b22728ce4f · outbound

This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-07-03T21:08:58.134569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3d393755-890e-4f75-adf9-1320e6b7d938 · outbound

This paper cites Quamba2: Robust and efficient post-training quantization for selective state space models.arXiv preprint arXiv:2503.22879, 2025.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Quamba2: Robust and efficient post-training quantization for selective state space models.arXiv preprint arXiv:2503.22879, 2025

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:08:58.137668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0ca5276f-7a83-4f85-a44d-142a10cf8474 · outbound

This paper cites Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Transformers are SSMs: Generalized models and efficient algorithms through structured state space duality

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-27T00:55:02.737906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ef94bb7-6a23-4f8f-8e7a-76502c651650 · outbound

This paper cites Quamba: A Post-Training Quantization Recipe for Selective State Space Models.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Quamba: A Post-Training Quantization Recipe for Selective State Space Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:08:58.140324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 0c09194e-df38-4e4d-beff-79f0e8a1c210 · outbound

This paper cites ParetoQ: Scaling laws in extremely low-bit LLM quantization.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models ParetoQ: Scaling laws in extremely low-bit LLM quantization

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:08:58.112131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7307537a-d093-49da-9e9f-bd165c4c21ea · outbound

This paper cites Estimation with quadratic loss.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Estimation with quadratic loss

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T00:55:02.737906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 628ff740-8484-4faa-892e-2a81f40ca016 · outbound

This paper cites On Erlang Queue with Multiple Arrivals and its Time-changed Variant.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models On Erlang Queue with Multiple Arrivals and its Time-changed Variant

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:08:58.114708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e55d1df0-8d41-44e2-a0da-7f3b9b77cf55 · outbound

This paper cites Distributed Space Resource Logistics Architecture Optimization under Economies of Scale.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Distributed Space Resource Logistics Architecture Optimization under Economies of Scale

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:08:58.129488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2dc1e227-54ff-473f-9b83-ca43f32b3fee · outbound

This paper cites The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-07-03T21:08:58.131885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 050a148f-50cc-4bb9-b7ec-3c98fe7fe157 · outbound

This paper cites Mamba-PTQ: Outlier Channels in Recurrent Large Language Models.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Mamba-PTQ: Outlier Channels in Recurrent Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:08:58.137818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation ffaa125f-a98b-4c6c-a323-07b78bbdc24c · outbound

This paper cites an unresolved cited work.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-27T00:55:02.737906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7684e2fa-871d-46b5-bb4d-03cf81e37375 · outbound

This paper cites Spike-temporal latent representation for energy-efficient event-to-video reconstruction.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Spike-temporal latent representation for energy-efficient event-to-video reconstruction

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T21:08:58.123841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation b35dfd0b-d5da-4961-825b-600638904be1 · outbound

This paper cites TernaryLLM: Ternarized Large Language Model.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models TernaryLLM: Ternarized Large Language Model

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T21:08:58.133340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f5d199d6-8a34-4132-a737-626e8c682771 · outbound

This paper cites Slender-mamba: Fully quantized mamba in 1.58 bits from head to toe.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models Slender-mamba: Fully quantized mamba in 1.58 bits from head to toe

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T00:55:02.737906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee12d588-9828-4da3-9ee1-062b7ce71b89 · outbound

This paper cites LREC: Low-rank error correction for quantized LLMs.arXiv preprint arXiv:2405.14673, 2024.

Ternary Mamba: Grouped Quantization-Aware Training of W1.58A16 State Space Models LREC: Low-rank error correction for quantized LLMs.arXiv preprint arXiv:2405.14673, 2024

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:08:58.117751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.