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Paper Citation Record · LEDGER

TRAWL: Tensor Reduced and Approximated Weights for Large Language Models

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.17261.

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

pith.paper-citation-record.v1
2406.17261 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:07:07.336593Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:46:26.864121Z

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 77baf5c0-dce4-47ef-8883-8a860bb8dc5a · inbound

TensorLLM: Tensorising Multi-Head Attention for Enhanced Reasoning and Compression in LLMs cites this paper.

TensorLLM: Tensorising Multi-Head Attention for Enhanced Reasoning and Compression in LLMs TRAWL: Tensor Reduced and Approximated Weights for Large Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T14:07:07.336593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:07:07.336593Z digest=sha256:47f247eddd3696a12a9bcee0770aaaa12e59cf9da775112dac8e288640511393

Observation f8792c9b-0f11-4955-9d3b-cd277838d36e · inbound

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression cites this paper.

Rethinking the Role of Tensor Decompositions in Post-Training LLM Compression TRAWL: Tensor Reduced and Approximated Weights for Large Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-02T01:46:26.866190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-28T11:31:25.851340Z digest=sha256:301cc1213bfb845585e301d49bbca84a1c623c5b2645413a522c5c947e352bc2