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Paper Citation Record · LEDGER

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions

As of 9 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2608.02491.

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

pith.paper-citation-record.v1
2608.02491 v2

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:11:20.220579Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

13 of 13 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1e68e2aa-a983-42c1-84cb-04d8e84a8282 · outbound

This paper cites Sycophantic AI makes human interaction feel more effortful and less satisfying over time.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions Sycophantic AI makes human interaction feel more effortful and less satisfying over time

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.189349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.189349Z digest=sha256:c3cb0fe81d2c896b7bbecb92087cbeabc9f13847fe55a7f6c4f88a029c0b16bf

Observation 5c291d9b-1d01-43d6-8633-f1a206ca54c5 · outbound

This paper cites Personality Traits in Large Language Models.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions Personality Traits in Large Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.206934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.206934Z digest=sha256:3d2fca84bd3b8aba1fcde8e836ff477486e8f8907bb604d8cca893da59924c9c

Observation 0993544e-3be0-4226-9db3-733bf5c74a91 · outbound

This paper cites $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.215955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.215955Z digest=sha256:cd57c0cf3a885d914398ec4a623957f6fc9871c017fc31c9478015cfab549062

Observation 1b842dd0-a2b6-4266-a43a-46a2118b9baf · outbound

This paper cites The Rise of AI Companions: Interaction with AI Companions and Psychological Well-being.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions The Rise of AI Companions: Interaction with AI Companions and Psychological Well-being

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.220579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.220579Z digest=sha256:f0b7bfe72ea09e218de2a74186c43dba8aa8a45a5a2b412253a38220cd0a2a78

Observation e11b7d78-4cd1-42de-9b2a-ed0f57d0ff5d · outbound

This paper cites Ed Diener, Derrick Wirtz, William Tov, Chu Kim-Prieto, Dong won Choi, Shigehiro Oishi, and Robert Biswas- Diener.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions Ed Diener, Derrick Wirtz, William Tov, Chu Kim-Prieto, Dong won Choi, Shigehiro Oishi, and Robert Biswas- Diener

Reference 1985

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.175198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.175198Z digest=sha256:f51d8ba4011ae7cd22b59b353050aae16efcc8c589388af8e30a284b13474a91

Observation a32a53eb-cb34-4d1c-a044-e7b58995e049 · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions Mechanistic Interpretability for AI Safety -- A Review

Reference 1996

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.163238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.163238Z digest=sha256:393d1991fdd8c926d2371ad1042e4d54867e692d6cbdd9f10096add0b9eb2f4c

Observation 432b5be4-cf3e-45a9-a420-d93609dc875e · outbound

This paper cites Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge

Reference 2007

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.211326Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.211326Z digest=sha256:ecabc53ef03c4140207f06eb03d6b6b859c53ede252c6671e2350b79e29ca6fd

Observation 2ef85d5d-0a90-4dde-9184-504796dcfda4 · outbound

This paper cites was it “stated.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions was it “stated

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.198432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.198432Z digest=sha256:9b27590df2f09b40529991ee5fcbaa0a39ca9f635711c9847744f7a71e62d2f1

Observation b7292df3-84ff-4aaf-a642-0a1a31782e34 · outbound

This paper cites On the limits of agency in agent-based models.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions On the limits of agency in agent-based models

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.170750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.170750Z digest=sha256:3cfcc5e798be322d916e5b8a590c12ebc11e1e5f920b326abdf4fcbaa3846634

Observation fb7e7b60-e3c8-43e3-9d7b-2aee8e0bf8ec · outbound

This paper cites InProceedings of the 2021 Confer- ence on Empirical Methods in Natural Language Processing, pages 298–311, Online and Punta Cana, Dominican Republic.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions InProceedings of the 2021 Confer- ence on Empirical Methods in Natural Language Processing, pages 298–311, Online and Punta Cana, Dominican Republic

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T00:12:20.529912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:11:20.203245Z digest=sha256:35b1ca7cbd81bce7bc5beb5607419d4c66dc3ca6b6cdef84902301291b6124a2

Observation 0aff944a-ec6d-4fbb-8264-2913650bdcd6 · outbound

This paper cites align- ment.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions align- ment

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.193822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.193822Z digest=sha256:f27c8daf329fd27f3b8189c1f1811437c583722720049ad8b575841aad77cc7f

Observation 41b7f1bf-b4a0-4301-82e1-d7f105510b38 · outbound

This paper cites Scaling Synthetic Data Creation with 1,000,000,000 Personas.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions Scaling Synthetic Data Creation with 1,000,000,000 Personas

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.179232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.179232Z digest=sha256:cb087b7b64e6a08c578fa3e8f4939052596c4dc32521e9b9a9be45c3b5f3a4b5

Observation e7b8d513-d17e-4fb0-8b56-b5cc470e0132 · outbound

This paper cites arXiv preprint arXiv:2602.08754.

Long-term Measurements: Towards a Longitudinal Understanding of Human-AI Interactions arXiv preprint arXiv:2602.08754

Reference 2026

Resolution
unresolved
no resolver link, observed 2026-08-07T00:11:20.184102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:11:20.184102Z digest=sha256:9fa24a1e3651d96ffe5e5972bc32a93f90c492b08d5ca09cf359e8824cb33b8a

Pith citing papers

No inbound Pith citation observations are available.