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Paper Citation Record · LEDGER

Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2405.06105.

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

pith.paper-citation-record.v1
2405.06105 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:51:00.793164Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T23:30:46.049292Z

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 459d0420-8193-4470-a6eb-4f2b72623d19 · inbound

When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training cites this paper.

When Precision Meets Position: BFloat16 Breaks Down RoPE in Long-Context Training Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-12T16:30:21.179131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T16:30:21.179131Z digest=sha256:ef7ad832edc3d5635bde5062a2d2af8e2d14a15d94a72f1ebfe465523243306c

Observation 64acd883-d19e-43df-9eed-19ea2a63dc3f · inbound

GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs cites this paper.

GenBFA: An Evolutionary Optimization Approach to Bit-Flip Attacks on LLMs Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T16:16:01.139702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:16:01.139702Z digest=sha256:065200dc393591ca9435fcd1da019b4fc3b1049461a2518ebd6645cb6d0053cd

Observation ad02b212-88c4-430e-8010-61dea17a81b0 · inbound

Theoretical Benefit and Limitation of Diffusion Language Model cites this paper.

Theoretical Benefit and Limitation of Diffusion Language Model Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T20:56:22.933369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T20:56:22.933369Z digest=sha256:b41d36fee38c87b0e65caa57254683c5d37f4901da59e937d12dc07b34e667ef

Observation 1068b97d-4b75-47bb-8c0a-079e69f51d92 · inbound

Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model cites this paper.

Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:18:28.108508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:18:28.108508Z digest=sha256:edc9ade4ebf1b2cd3cf3aa3812388414b26c4f12de9af740b3b7dfb4c0cb8135

Observation 2fbec718-33e2-4357-a576-971245cd44d9 · inbound

Estimating the Effects of Sample Training Orders for Large Language Models without Retraining cites this paper.

Estimating the Effects of Sample Training Orders for Large Language Models without Retraining Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:12.498757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:23:12.498757Z digest=sha256:9df9dc41fc01d48004b07a8f0e9e134e947ceb97847af2896fc190e1b1368e0b

Observation 0153c90e-717d-4cc3-9e0b-cd75b9cada56 · inbound

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training cites this paper.

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T10:30:12.908080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:30:12.908080Z digest=sha256:28c829f44b7dd89c5dbae66ba7f52ddfdef68eef2ed074c0f08fb64a3db3d7ec

Observation fe6af2f7-9267-4082-a24d-1990f785a5a3 · inbound

A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement cites this paper.

A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:30:46.051398Z

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.

source=arxiv_source observed=2026-05-21T23:26:38.457193Z digest=sha256:4b99dee08f9056eaba8cdeed2f204165d2b50c8e81295bc4b93fe9cab17c4f67

Observation 30828e66-4cda-4974-9dca-b0ea4200d69c · inbound

Towards Faster Language Model Inference Using Mixture-of-Experts Flow Matching cites this paper.

Towards Faster Language Model Inference Using Mixture-of-Experts Flow Matching Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:29:24.659495Z

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.

source=pdf_text observed=2026-05-10T10:28:00.424341Z digest=sha256:e98e398c45f80f1f0509fd20463683be61ec05670983bec3765531cae63fb293

Observation e33c4f3c-7b9f-478c-b274-04dfa54c9775 · inbound

Group Perspective Matters: Regulating Debate Relationships Can Mitigate Blind Conformity in Multi-Agent Debate cites this paper.

Group Perspective Matters: Regulating Debate Relationships Can Mitigate Blind Conformity in Multi-Agent Debate Can Perplexity Reflect Large Language Model's Ability in Long Text Understanding?

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T14:51:00.793164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:51:00.793164Z digest=sha256:d929bb96b5287e1a8a1555725137401380bcd9b3d85427d74381b8156002e074