Paper Citation Record · LEDGER

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models

As of 10 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2502.02074.

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

pith.paper-citation-record.v1
2502.02074 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:29:21.002737Z

measured 15 of 15 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 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

15 of 15 outbound references displayed

verified exact5
verified fuzzy3
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b1aa4cae-f201-4f9c-87bc-f92a36553a7b · outbound

This paper cites Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T13:29:20.929756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 560c1295-14ea-4e0b-82ca-f3a4433ddb66 · outbound

This paper cites Whose Side Are You On? Investigating the Political Stance of Large Language Models.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Whose Side Are You On? Investigating the Political Stance of Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T13:29:20.957017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b34b5b85-e051-411c-b524-0981b9a6a4e9 · outbound

This paper cites The Political Preferences of LLMs.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models The Political Preferences of LLMs

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T13:29:20.962575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76a1d59f-70c2-4959-9c46-ebb08f19ffcc · outbound

This paper cites A Logically Consistent Chain-of-Thought Approach for Stance Detection.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models A Logically Consistent Chain-of-Thought Approach for Stance Detection

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-09T13:29:21.063221Z

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.

Observation 8589fd60-bd5d-4428-a638-4deadc400f91 · outbound

This paper cites From traces to measures: Large language models as a tool for psychological measurement from text.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models From traces to measures: Large language models as a tool for psychological measurement from text

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-08-09T13:29:21.100841Z

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.

Observation 37b79091-4e35-454a-9d04-5afd218840f9 · outbound

This paper cites an unresolved cited work.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-09T13:29:21.253522Z

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.

Observation 8db2b485-5365-4a7a-862b-6929b2f0afdc · outbound

This paper cites IEEE Transactions on Computational Social Systems Zhang et al.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models IEEE Transactions on Computational Social Systems Zhang et al

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:29:21.237674Z

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.

Observation 3833022d-fa0f-4fdb-8f92-08c85f1e2124 · outbound

This paper cites By stance we mean the lexical and grammatical expression of attitudes, feelings, judgments, or commitment concerning the propositional content of a message.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models By stance we mean the lexical and grammatical expression of attitudes, feelings, judgments, or commitment concerning the propositional content of a message

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:29:21.283757Z

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.

Observation 2e2d19da-839a-4ec9-9b95-6a8427bbe8bf · outbound

This paper cites Stance Detection on Social Media with Fine-Tuned Large Language Models.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Stance Detection on Social Media with Fine-Tuned Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T13:29:20.946328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8c33e50-0490-4923-b9d4-b11c63dc68f3 · outbound

This paper cites Bryndza at ClimateActivism 2024: Stance, Target and Hate Event Detection via Retrieval-Augmented GPT-4 and LLaMA.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Bryndza at ClimateActivism 2024: Stance, Target and Hate Event Detection via Retrieval-Augmented GPT-4 and LLaMA

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-09T13:29:20.972793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08137d4c-13fc-41fa-ac31-bcd9a1d83830 · outbound

This paper cites Tweets2Stance: Users stance detection exploiting Zero-Shot Learning Algorithms on Tweets.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Tweets2Stance: Users stance detection exploiting Zero-Shot Learning Algorithms on Tweets

Reference 1663

Resolution: verified exact; local_arxiv, observed 2026-08-09T13:29:21.187344Z

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.

Observation b0c992eb-e3f5-41f2-872b-4bf896d18070 · outbound

This paper cites …a person’s expression of their relationship to their interlocutors (their interpersonal stance—e.g., friendly or dominating).

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models …a person’s expression of their relationship to their interlocutors (their interpersonal stance—e.g., friendly or dominating)

Reference 2004

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T13:29:21.269000Z

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.

Observation 55a1b5ab-fe63-4f16-bd27-29fe5d459df5 · outbound

This paper cites A Survey of Large Language Models.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models A Survey of Large Language Models

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-09T13:29:20.982491Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91fc497a-48e2-46f4-a220-28dcad9cc02f · outbound

This paper cites Predicting User Stances from Target-Agnostic Information using Large Language Models.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Predicting User Stances from Target-Agnostic Information using Large Language Models

Reference 2024

Resolution: verified exact; local_arxiv, observed 2026-08-09T13:29:21.150991Z

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.

Observation 7e1f9f73-2f77-4710-bae6-ac9adff43c81 · outbound

This paper cites Do Language Models Understand Morality? Towards a Robust Detection of Moral Content.

Rethinking stance detection: A theoretically-informed research agenda for user-level inference using language models Do Language Models Understand Morality? Towards a Robust Detection of Moral Content

Reference 2332

Resolution: verified exact; local_arxiv, observed 2026-08-09T13:29:21.208035Z

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.

Pith citing papers

No inbound Pith citation observations are available.