Pith. sign in

Paper Citation Record · LEDGER

TesseraQ: Ultra Low-Bit LLM Post-Training Quantization with Block Reconstruction

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.19103.

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

pith.paper-citation-record.v1
2410.19103 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:50:07.266451Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T19:32:34.752274Z

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 047a11fe-1364-4898-85c9-f4d066823795 · inbound

NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs cites this paper.

NeUQI: Near-Optimal Uniform Quantization Parameter Initialization for Low-Bit LLMs TesseraQ: Ultra Low-Bit LLM Post-Training Quantization with Block Reconstruction

Reference 1989

Resolution
unresolved
no resolver link, observed 2026-08-07T14:50:07.266451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:50:07.266451Z digest=sha256:a59bc122aab0a852ef7c6240e047d460fc1e3affecebaf05fa7ddc10b0d2e6f9

Observation cf0ce28b-93f8-4ae0-bd95-7dff8629a7f6 · inbound

Edge-ASR: Towards Low-Bit Quantization of Automatic Speech Recognition Models cites this paper.

Edge-ASR: Towards Low-Bit Quantization of Automatic Speech Recognition Models TesseraQ: Ultra Low-Bit LLM Post-Training Quantization with Block Reconstruction

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T18:33:17.842506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:33:17.842506Z digest=sha256:b8461868b19c7a9c0f5cc189a525f346082e8661f945f17c4d3ba4d025684357

Observation 3fa0cdd8-72b5-45d3-ac84-c2e7b4f1cca8 · inbound

SPARQLe: Sub-Precision Activation Representation for Quantized LLM Inference cites this paper.

SPARQLe: Sub-Precision Activation Representation for Quantized LLM Inference TesseraQ: Ultra Low-Bit LLM Post-Training Quantization with Block Reconstruction

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-28T19:32:34.753674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-28T19:31:28.053090Z digest=sha256:e7f268d9b2d5b629b31410ff48cc35be0f824ca23c6e7c4a54c47942000df790