Pith. sign in

Paper Citation Record · LEDGER

Understanding User Experience in Large Language Model Interactions

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2401.08329.

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

pith.paper-citation-record.v1
2401.08329 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:14:06.593473Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, 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

18
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2222c7e1-75b6-4fb9-8b96-ac490fd46f2c · inbound

An Empirical Characterization of Outages and Incidents in Public Services for Large Language Models cites this paper.

An Empirical Characterization of Outages and Incidents in Public Services for Large Language Models Understanding User Experience in Large Language Model Interactions

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-10T17:14:06.593473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:14:06.593473Z digest=sha256:c4b6fbb17a9ff52b1ef742990dbb8f8645c9b19e2024bf3853ae27a6445eac1f

Observation f8bc1cd4-0c31-45db-9df1-ed1758693d4f · inbound

CollabLLM: From Passive Responders to Active Collaborators cites this paper.

CollabLLM: From Passive Responders to Active Collaborators Understanding User Experience in Large Language Model Interactions

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-09T18:18:09.314615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T18:18:09.314615Z digest=sha256:ec4bd916a30afbb6df4388e9b5581d2e4a33be9e517b79f3de1750ba6362e6b1

Observation f28fe09b-3172-44a5-9822-5ad57a5eae80 · inbound

PACT: A Contract-Theoretic Framework for Pricing Agentic AI Services Powered by Large Language Models cites this paper.

PACT: A Contract-Theoretic Framework for Pricing Agentic AI Services Powered by Large Language Models Understanding User Experience in Large Language Model Interactions

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T13:41:43.601149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:41:43.601149Z digest=sha256:14fb90340ee80060e8a780a8f7a3487696984d2a8c800483c09e92956dad8758

Observation 5ef050cd-aab0-46a7-9916-ad72627c61da · inbound

OSS-UAgent: An Agent-based Usability Evaluation Framework for Open Source Software cites this paper.

OSS-UAgent: An Agent-based Usability Evaluation Framework for Open Source Software Understanding User Experience in Large Language Model Interactions

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T12:52:39.233046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:52:39.233046Z digest=sha256:56c5633eb9aeb4d481c3dcce175f5bab51fb259d48f53bb878731b508ea282bd

Observation 3cd33f9e-3be1-49e6-be08-4964a977aa32 · inbound

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face cites this paper.

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face Understanding User Experience in Large Language Model Interactions

Reference 77

Resolution
verified exact
arxiv_id, observed 2026-05-10T23:20:54.524878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T19:11:27.071800Z digest=sha256:fdf22294971b55cb7f737200086a3a7075891158a123577d4a378fce7a473836

Observation 3d678f8f-2b28-4c93-8a1b-964f5fbae675 · inbound

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face cites this paper.

When Models Meet Users: An Empirical Study of Perceptions of General LLMs and Multimodal LLMs on Hugging Face Understanding User Experience in Large Language Model Interactions

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-02T16:43:13.946507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T16:43:13.946507Z digest=sha256:2ad65cf83a7e90ceb34cd70910be8f85b1e42c1e8ba29866fa1885386466295f

Observation 3ed069f4-18fb-471d-b872-d9fd9e8a7e0c · inbound

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance cites this paper.

Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance Understanding User Experience in Large Language Model Interactions

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:56:47.907370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-10T05:27:50.049798Z digest=sha256:88d10383fb423cb1c6790fee2886159a1222d6360dcfdc911487786c59011f39

Observation 3c30d5d9-f7d8-43b4-a02f-6f7c8abe691a · inbound

Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments cites this paper.

Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments Understanding User Experience in Large Language Model Interactions

Reference 72

Resolution
verified exact
arxiv_id, observed 2026-06-29T16:53:40.627476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T16:51:36.524194Z digest=sha256:db9df127d07e05fcfc1c8597f176903473a33da28af6ecfa71e86ccd10bd5c3a

Observation 6b84d7aa-22c5-457d-a637-a1df78ecf6c5 · inbound

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings cites this paper.

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings Understanding User Experience in Large Language Model Interactions

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-07-01T05:45:25.663019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-01T05:37:01.380178Z digest=sha256:f1116594a75e44de20020e15a29d6b5a784cac805e79f8e0084045356d164f59

Observation ac4cd364-1bf3-411f-b717-462e7ad700e9 · inbound

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings cites this paper.

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings Understanding User Experience in Large Language Model Interactions

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:57:18.882337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-02T19:48:09.205371Z digest=sha256:59605b11c94a0dbba12bb0236b99061b78e0f27e0079db0c3c00beddf34e4b2f

Observation 60b607d3-ac27-4ff5-96b5-4c9e34c6e7ec · inbound

Understanding Fortunetelling with Large Language Models in China: User Practices, Perceptions, and Impacts on Beliefs and Decisions cites this paper.

Understanding Fortunetelling with Large Language Models in China: User Practices, Perceptions, and Impacts on Beliefs and Decisions Understanding User Experience in Large Language Model Interactions

Reference 121

Resolution
unresolved
no resolver link, observed 2026-08-01T22:47:24.644471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T22:47:24.644471Z digest=sha256:4400f5e6815a751ca048b37377552d997e30463682560160e1d2d7068f2e63f8

Observation ee98a24f-0d45-43f4-b8dd-1e72b59ba853 · inbound

Reflections and Recommendations on AI Adoption Practice from a Mixed-Ability Research Group cites this paper.

Reflections and Recommendations on AI Adoption Practice from a Mixed-Ability Research Group Understanding User Experience in Large Language Model Interactions

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-01T04:17:43.340031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T04:17:43.340031Z digest=sha256:51ad86ddb926ab6961926a8e20a4244f81f4167670de41ceb268255bac6b418d

Observation fe0a5809-6866-4f94-a79c-1da3448024a0 · inbound

What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations) cites this paper.

What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations) Understanding User Experience in Large Language Model Interactions

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T12:44:33.653851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:44:33.653851Z digest=sha256:d62c28ca99260e4f9e2bb6e725c3f0f261a0b4c16b70247f0715d7697b3b78ed