Pith. sign in

Paper Citation Record · LEDGER

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity

As of 7 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2507.00657.

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

pith.paper-citation-record.v1
2507.00657 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:15:37.989676Z

measured 57 of 57 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 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

57 of 57 outbound references displayed

  • verified exact5
  • verified fuzzy32
  • unresolved19
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 06e2c834-82ed-445a-a770-22b800a5571b · outbound

This paper cites , Zhang , J.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Zhang , J

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.791038Z

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=arxiv_source observed=2026-08-06T21:15:14.011110Z digest=sha256:3af53bc68f3761beccfb5d5d7453a196a488a0531b08c37b261f55264f370449

Observation c214e22a-968d-4bb6-9861-fb74af8694f1 · outbound

This paper cites , Cao , Y.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Cao , Y

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.773311Z

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=arxiv_source observed=2026-08-06T21:15:36.620599Z digest=sha256:bfcb7e950fedf7fb70c64140df8f9ba023678ad78af25efa7feca3376a9759f5

Observation 6722c3b4-4cf8-4669-9cc3-53579e25f45d · outbound

This paper cites , Song , K.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Song , K

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.759174Z

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=arxiv_source observed=2026-08-06T21:15:36.646558Z digest=sha256:dc486306ee2c4a235c9f3bc90aed4a072633c90ee6cf6b08034a28e8711e2480

Observation 455bcd2d-4cab-4e48-b343-707a9663bb66 · outbound

This paper cites , Chu , S.N.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Chu , S.N

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.740498Z

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=arxiv_source observed=2026-08-06T21:15:36.681754Z digest=sha256:4b940cbc5c0da589c00d9274f954d1adfd8bee4e4d65fea851e1fabc649da3df

Observation c7fdb78b-4de8-4096-8d99-4b44e542b6f7 · outbound

This paper cites Bran , A.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Bran , A

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.697213Z

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=arxiv_source observed=2026-08-06T21:15:36.708127Z digest=sha256:bf125ab26f686212b093f4d501ace085472c16d5b2fdd1a7da9cd815ee923913

Observation f127d8d0-19bd-4d24-88cd-e067a1a9fe3a · outbound

This paper cites , Yu , Y.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Yu , Y

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.642825Z

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=arxiv_source observed=2026-08-06T21:15:36.729824Z digest=sha256:f66cf32cc6c23d011435082518a7c6ddf2ed4ad89ce5c0db85ea8c03f363defc

Observation e4e81e9b-1332-4a8d-ad06-47880f4f5e85 · outbound

This paper cites Engagement-Driven Content Generation with Large Language Models.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Engagement-Driven Content Generation with Large Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:36.749154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:36.749154Z digest=sha256:aa20b3116fcbe978b089267d9a9faad44fad1b032b2c28efcaa2d2a5475a73a6

Observation f4970cea-d474-49b5-8081-f9cdeec6f9f6 · outbound

This paper cites , O'Brien , J.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , O'Brien , J

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.603696Z

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=arxiv_source observed=2026-08-06T21:15:36.757671Z digest=sha256:088505b2a1627a9ef3dc6be372d91a584e0cd21d68e63d70c067e735bcd14ccf

Observation 6a61573e-e8f9-4b84-958c-8ebb30ab8716 · outbound

This paper cites , Axtell , R.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Axtell , R

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.572316Z

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=arxiv_source observed=2026-08-06T21:15:36.782671Z digest=sha256:a7bf8d99cd51d900ba1e8fba02d41107ef5019da8a810ee3de62aca179378883

Observation 4c0d47fe-7c9c-4097-98af-ad76089135fe · outbound

This paper cites , Edmonds , B.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Edmonds , B

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.539711Z

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=arxiv_source observed=2026-08-06T21:15:36.798316Z digest=sha256:850b77dc3ac52a58d2eb1a2568536efb00ec64050dadd9475744e1d03bdb00cd

Observation 2cca18a7-d616-47ab-ae10-17bd8b4d656e · outbound

This paper cites The Impact of Generative AI on Social Media: An Experimental Study.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity The Impact of Generative AI on Social Media: An Experimental Study

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:15:38.564187Z

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=arxiv_source observed=2026-08-06T21:15:36.814775Z digest=sha256:41efa87e020c82789984b05098d63476c21919e2fe3c10c056a263715845ec42

Observation b27764ea-260a-4a7a-bc74-1f4e189eb76a · outbound

This paper cites , De Francisci Morales , G.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , De Francisci Morales , G

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.515308Z

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=arxiv_source observed=2026-08-06T21:15:36.825743Z digest=sha256:8b9809c88686c77776252b0fca192252c5555149b14226eb79e87206b5c9b5d8

Observation c0cbcfe8-062c-4857-bc77-01b2b3676e07 · outbound

This paper cites Ideological Fragmentation of the Social Media Ecosystem: From echo chambers to echo platforms.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Ideological Fragmentation of the Social Media Ecosystem: From echo chambers to echo platforms

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:15:38.517851Z

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=arxiv_source observed=2026-08-06T21:15:36.834097Z digest=sha256:a2611b53b16e4c1ef62f07a173668ce9f537eb02f14865fb06ae8af82900bd84

Observation e4d26ee9-e225-4b11-b0c5-e730f1d89ef2 · outbound

This paper cites , Bessi , A.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Bessi , A

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.488986Z

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=arxiv_source observed=2026-08-06T21:15:36.840425Z digest=sha256:37496473b4f13372fef096acbc6d1da6afe388d11a40b97d65d63099dc0aa49d

Observation 3abbcfa7-6af4-4083-ac64-af1a93349733 · outbound

This paper cites , Ziegler , J.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Ziegler , J

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.459696Z

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=arxiv_source observed=2026-08-06T21:15:36.860985Z digest=sha256:189863074f1afbb5312ec93cbb76acb77f9ca4d7eca26c3c5ff0f160f3479b80

Observation 5c29089d-c123-41fb-9d36-e55323cd4c55 · outbound

This paper cites : Salm: A multi-agent framework for language model-driven social network simulation.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity : Salm: A multi-agent framework for language model-driven social network simulation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:36.928314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:36.928314Z digest=sha256:d10042c811b4aeedf2f8e0a74203047883bb1af820d4413f81d1d5ee0c3c2b13

Observation 0c7b3f07-4129-42bc-a710-2fa8ef1cafac · outbound

This paper cites Y Social: an LLM-powered Social Media Digital Twin.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Y Social: an LLM-powered Social Media Digital Twin

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:36.962613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:36.962613Z digest=sha256:c291d10db0338cbbcdd64e17f740c3fe76163bbda29efe07971d8f54b72b016b

Observation 75f6f68a-c979-4369-b0ab-952262de87ed · outbound

This paper cites , Failla , A.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Failla , A

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.416614Z

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=arxiv_source observed=2026-08-06T21:15:37.028041Z digest=sha256:e3856120c2b31c7b4d9c89c6bdee3264c8a5167e05a0a38956d349907cf548ae

Observation a9cffbfe-1dfd-4f9b-9dbc-e7b00153e2f8 · outbound

This paper cites , Assenmacher , D.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Assenmacher , D

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.361812Z

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=arxiv_source observed=2026-08-06T21:15:37.070994Z digest=sha256:8a55cf547aa07f4c1536460387db2388b10d702f12561483f45626db1f50e123

Observation 5752eb3c-ef58-4626-9152-5b4ffdfe4d9a · outbound

This paper cites , Popowski , L.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Popowski , L

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.307666Z

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=arxiv_source observed=2026-08-06T21:15:37.091218Z digest=sha256:0801fc98cbef596fe591d1d8d74a7a84d4c9bd39ca15c26c03c505aa58694eea

Observation 3e58729e-2934-43f9-93b6-62deefec61a0 · outbound

This paper cites , Wurth , E.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Wurth , E

Reference 21

Resolution
verified exact
raw_fallback, observed 2026-08-06T21:15:38.396670Z

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=arxiv_source observed=2026-08-06T21:15:37.101342Z digest=sha256:78d4dcc2f8d020363fc7c20be288f192b89db2841c79f751783bd7400bc9051e

Observation f445678f-a129-45ff-846e-10a87cc51779 · outbound

This paper cites Unmasking Conversational Bias in AI Multiagent Systems.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Unmasking Conversational Bias in AI Multiagent Systems

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.121633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.121633Z digest=sha256:cc49d8199dbeb7fd83224e0c7ddc47efc8eea6e035abf10573ddde2d826eff1d

Observation 6b5c956e-6910-49a5-a321-b040beebd2ca · outbound

This paper cites Systematic Biases in LLM Simulations of Debates.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Systematic Biases in LLM Simulations of Debates

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.148607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.148607Z digest=sha256:a8dd90f46a5883915771122ca0e61bce08414c3c9e81cef9ae0a6f118955d33b

Observation 1ad7019b-02c6-4a27-a685-a06ab959f55b · outbound

This paper cites CoMPosT: Characterizing and Evaluating Caricature in LLM Simulations.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity CoMPosT: Characterizing and Evaluating Caricature in LLM Simulations

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.174356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.174356Z digest=sha256:66b59e6edcd78046c91a74cd3dd83cb0a011af5a947922438039d6792f408ab6

Observation 7393551f-fed3-42b6-91d9-a00f440fa0d4 · outbound

This paper cites , Diab , M.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Diab , M

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.200399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.200399Z digest=sha256:5fc944a5e73b6999c00c022a430fd8b754aab7aaec94c3ccd48af94c97093b74

Observation cf4fc60d-a5e1-426f-ab2c-d482f2b1dade · outbound

This paper cites LLM Generated Persona is a Promise with a Catch.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity LLM Generated Persona is a Promise with a Catch

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.217123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.217123Z digest=sha256:194caa035c57310cb039c6603da316e5d67d14af803d9c8a032f0841f72784ca

Observation 71ef92fa-a66f-446d-bb44-2d0e49c0aba8 · outbound

This paper cites Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Robustness and Confounders in the Demographic Alignment of LLMs with Human Perceptions of Offensiveness

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.225915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.225915Z digest=sha256:2593532dfbe0fb64a8ff63228ac8df36b676901b94154686c3f1a4382028f282

Observation 47b13f1a-9e6a-4369-8130-9f34ef4574b6 · outbound

This paper cites , Kyrychenko , Y.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Kyrychenko , Y

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.255171Z

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=arxiv_source observed=2026-08-06T21:15:37.233795Z digest=sha256:b8f610a52c3c392596a19c46260ba679a509672ee521edabed80d3a15737b3c1

Observation a8aed2a7-4831-40d0-bfcb-9c704d433576 · outbound

This paper cites , Nudo , J.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Nudo , J

Reference 29

Resolution
verified exact
raw_fallback, observed 2026-08-06T21:15:38.262738Z

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=arxiv_source observed=2026-08-06T21:15:37.241108Z digest=sha256:b7eae2314d438e1478bbe5382f3d68fb2f1f3906a2b3496df72e2a461eb66e52

Observation 9e50e678-d343-40a8-a594-73ae26bc9a45 · outbound

This paper cites Large Language Models Reflect the Ideology of their Creators.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Large Language Models Reflect the Ideology of their Creators

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.247707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.247707Z digest=sha256:f56eb59da518c7eff9de2794c874596d94b92a6656325bc7e209aa6b39f0d3fd

Observation 2e2dcaeb-ed74-4b5d-b31d-efab22418ace · outbound

This paper cites What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.256994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.256994Z digest=sha256:ce0916eaf900971bd7ea42b10237fccf162392a4889c96a5d9a7ca8073301608

Observation b822383d-c84f-4703-ba58-705b4cf16ecc · outbound

This paper cites How Susceptible are Large Language Models to Ideological Manipulation?.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity How Susceptible are Large Language Models to Ideological Manipulation?

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.267329Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.267329Z digest=sha256:43aaba2eea58dc820392a7d8b559960c429419d99ca151d17c7aa1c0aa5caa28

Observation 928f4e3b-d958-41dc-bd4c-fa017801468f · outbound

This paper cites , Bernardelle , P.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Bernardelle , P

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.218850Z

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=arxiv_source observed=2026-08-06T21:15:37.274635Z digest=sha256:8dfe253fcc5b3ce967aa7b9ae1493d5d1a5d67fae2515dea3b57bc47540dc401

Observation fb6c1ebc-e9ad-42dc-b2db-a708030362cf · outbound

This paper cites Emergence of human-like polarization among large language model agents.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Emergence of human-like polarization among large language model agents

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.285321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.285321Z digest=sha256:574f2a14beb9c6f4e8b61366c9e70962c12070675966e43c639276217f1e8f10

Observation 8420ebbd-e046-4f8f-bb9b-567d016375e8 · outbound

This paper cites , Liao , Q.V.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Liao , Q.V

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.184756Z

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=arxiv_source observed=2026-08-06T21:15:37.295756Z digest=sha256:e706e7067922b9bd64753a90f4e776bdf28a254dce3b80f89e9037c25e581aeb

Observation db4db388-20ae-47f8-ae76-3d6319546ad7 · outbound

This paper cites : Filter bubbles and affective polarization in user-personalized large language model outputs.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity : Filter bubbles and affective polarization in user-personalized large language model outputs

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.154681Z

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=arxiv_source observed=2026-08-06T21:15:37.307894Z digest=sha256:9c5e5fd954eabc18c4235e7d3174af3052669fccb7f635e1e8f9c4b8e8454d1d

Observation d2dd7a90-709a-4e82-832a-d02a9ef0bbd0 · outbound

This paper cites A Public Dataset Tracking Social Media Discourse about the 2024 U.S. Presidential Election on Twitter/X.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity A Public Dataset Tracking Social Media Discourse about the 2024 U.S. Presidential Election on Twitter/X

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.323252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.323252Z digest=sha256:98d4b0d93d6e179227d27afcc871708abf2284e206fbd7e0f280f12d58e00402

Observation 4be9e8f2-146d-4e44-b72d-c035cbfada1d · outbound

This paper cites , Loru , E.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Loru , E

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.131317Z

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=arxiv_source observed=2026-08-06T21:15:37.356532Z digest=sha256:ac66b8a7abb1cf727356d667b9cb2c2a227e969a6f98319bca80fe51263c4e51

Observation a4c1e9f1-76c8-4b5d-90a0-3a2c732fecf0 · outbound

This paper cites , Baayen , R.H.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Baayen , R.H

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.100981Z

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=arxiv_source observed=2026-08-06T21:15:37.377983Z digest=sha256:2ecb32ce4dcc21a63e5a9660bc964a93d689777e0283f94ff1451d450da9c9d3

Observation 516cc73f-de61-4edb-b8ac-434d5a20512a · outbound

This paper cites , Jarvis , S.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Jarvis , S

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.074006Z

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=arxiv_source observed=2026-08-06T21:15:37.415400Z digest=sha256:cc1d9b54fa9fff85ba7c6e0693ebd01fbb0bb28d03655ef48bda024c58397dc7

Observation ff013971-cb58-449a-ad9d-0974f6a491ff · outbound

This paper cites Entropy and type-token ratio in gigaword corpora.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Entropy and type-token ratio in gigaword corpora

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.426729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.426729Z digest=sha256:be317e55f2b48809739b8f7f9cdeb38aa2d7c4c1a899fca444470b0f9ebad083

Observation 6d6c4cbf-21d6-4472-bf9c-aa7d1bc40d8f · outbound

This paper cites : Type/token ratios: What do they really tell us? Journal of child language 14 ( 2 ), 201 -- 209 ( 1987 ) barticle.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity : Type/token ratios: What do they really tell us? Journal of child language 14 ( 2 ), 201 -- 209 ( 1987 ) barticle

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:39.032636Z

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=arxiv_source observed=2026-08-06T21:15:37.480061Z digest=sha256:a4d526c70e4a86254c8d475c25c4caee56a4aba59c5d7b93152e2ddc2a459bcc

Observation 7df3f147-0c2e-4b5a-9d32-6d54da6aa3ee · outbound

This paper cites : Can type-token ratio be used to show morphological complexity of languages? Journal of Quantitative Linguistics 21 ( 3 ), 223 -- 245 ( 2014 ) barticle.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity : Can type-token ratio be used to show morphological complexity of languages? Journal of Quantitative Linguistics 21 ( 3 ), 223 -- 245 ( 2014 ) barticle

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.997039Z

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=arxiv_source observed=2026-08-06T21:15:37.521922Z digest=sha256:4c21f652de26a6027a3459dc192304286a794301aeae6bfc1cb135c72c92b541

Observation 625ea86c-df6f-460e-a2fa-75fc9d8d9f94 · outbound

This paper cites : Type-token mathematics: A textbook of mathematical linguistics.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity : Type-token mathematics: A textbook of mathematical linguistics

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.961135Z

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=arxiv_source observed=2026-08-06T21:15:37.533944Z digest=sha256:5f729b580465582b2564193db4253e0e5962600bcd5b17485bff41db96f55f6c

Observation 289d4e25-1741-4415-99e1-fc791e101996 · outbound

This paper cites an unresolved cited work.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:15:38.925315Z

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=arxiv_source observed=2026-08-06T21:15:37.598137Z digest=sha256:b237e655998dc921ec581a8ea6cf82f99fdc02857bead9c6aa0b2831c1d9f4c3

Observation d9a2dd33-e6fb-40b3-b7a9-b9b59985c46d · outbound

This paper cites : How useful is the logarithmic type/token ratio? Journal of Linguistics 7 ( 2 ), 237 -- 243 ( 1971 ) 10.1017/S0022226700002930 barticle.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity : How useful is the logarithmic type/token ratio? Journal of Linguistics 7 ( 2 ), 237 -- 243 ( 1971 ) 10.1017/S0022226700002930 barticle

Reference 46

Resolution
verified exact
doi, observed 2026-08-06T21:15:38.056806Z

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=arxiv_source observed=2026-08-06T21:15:37.642702Z digest=sha256:cdb18c41513278d23db87143e0c207672e4eeada6e78997aa7c6c8ae9f281d87

Observation ecf4886a-6c48-41e1-a18c-27a1a8f8ba0c · outbound

This paper cites : The political preferences of llms.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity : The political preferences of llms

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.883701Z

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=arxiv_source observed=2026-08-06T21:15:37.649087Z digest=sha256:201ca3afaa2bcd2f3e5f1589ef424305a51f03d7e3869c561bdbc9c858a13e6c

Observation 78a3d878-78d0-4ba9-a476-9625c8528422 · outbound

This paper cites Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.657360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.657360Z digest=sha256:0c506b4e47f68ed82002481d75bf8740b29fce1fbacc3d23df9466cb66fce96b

Observation 5e65778e-8048-49c6-85f4-41aa7907c035 · outbound

This paper cites Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Text.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Text

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.690427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.690427Z digest=sha256:8750a9d6b3e1c388b1f35515c025a342affd22e0d009bae9a8633bf428762367

Observation 6f0ecfb3-6814-4db8-a95a-16c22d682602 · outbound

This paper cites , Tran , V.Q.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Tran , V.Q

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.846349Z

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=arxiv_source observed=2026-08-06T21:15:37.706693Z digest=sha256:b675115852c028f13a0b13cbcbedcb8b86906e443fed449f4801eff09deb3dbf

Observation ece512ae-cfa1-4676-9723-cf16aa5edfca · outbound

This paper cites , Di Marco , N.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Di Marco , N

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.815728Z

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=arxiv_source observed=2026-08-06T21:15:37.757721Z digest=sha256:a7f740c4b5c3872f4397947a23d3a7f902a494f1b7c2c776eab87e73297fe888

Observation 38eb77a5-e6b2-4111-89f0-f95cbd9af891 · outbound

This paper cites , Hu , Y.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Hu , Y

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.783710Z

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=arxiv_source observed=2026-08-06T21:15:37.798904Z digest=sha256:eefb5214206f27b74cf4f5d3e570138cb036d5410cc246c26f08bebba52765b5

Observation a827264c-883a-4c81-bc29-4af03ebe3ed6 · outbound

This paper cites AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Society

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T21:15:37.843746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.843746Z digest=sha256:525da8d151c4022439caf5952c03a93140014ea57ea94c988c48712a54a39042

Observation 48d72222-15b5-492d-94f9-fd13e6471e7a · outbound

This paper cites , Montani , I.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , Montani , I

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.758383Z

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=arxiv_source observed=2026-08-06T21:15:37.917240Z digest=sha256:1ee9ede86288123c3960299e6be5938a796e38f0e6febf4e78ab8d7d10aef473

Observation 94bdeb29-5c0a-4412-bf02-e8236b09b361 · outbound

This paper cites , : Exploratory Data Analysis vol.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity , : Exploratory Data Analysis vol

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.712028Z

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=arxiv_source observed=2026-08-06T21:15:37.955626Z digest=sha256:e25dbf1f941684ac6a422b6d40a5a31c925187c65a62bfbbb50582c393c63a06

Observation 53ad9e78-f34e-417b-858a-38faf0cd08e5 · outbound

This paper cites Exploratory data analysis, volume 2.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Exploratory data analysis, volume 2

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:15:38.670561Z

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=arxiv_source observed=2026-08-06T21:15:37.973828Z digest=sha256:bc673e6fbfae6a46a6aeda1dab5aa0753ec4a50c405786f27ea3f23fb4cf95f2

Observation 412f2749-93f0-4dc5-a199-2c1a96d05013 · outbound

This paper cites write newline.

Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity write newline

Reference 57

Resolution
malformed identifier
no resolver link, observed 2026-08-06T21:15:37.989676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:15:37.989676Z digest=sha256:507c61f58b509b22fc75a8c0d41259bf8b5061f8233164be15f0659a1f621dcb

Pith citing papers

No inbound Pith citation observations are available.