Paper Citation Record · LEDGER

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling

As of 8 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2505.24199.

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

pith.paper-citation-record.v1
2505.24199 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:37:28.844630Z

measured 20 of 20 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

20 of 20 outbound references displayed

verified exact0
verified fuzzy12
unresolved8
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b43d1644-207b-4558-b596-4262dcb7cbaa · outbound

This paper cites Ouyang et al., ”Training language models to follow ins tructions with human feedback,” in Proc.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Ouyang et al., ”Training language models to follow ins tructions with human feedback,” in Proc

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:32.382184Z

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.

Observation 79b36c65-79ac-4c75-97dc-d90bf943d8ea · outbound

This paper cites Rafailov et al., ”Direct preference optimization: Y o ur language model is secretly a reward model,” arXiv preprint arXiv:2305.182 90, 2023.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Rafailov et al., ”Direct preference optimization: Y o ur language model is secretly a reward model,” arXiv preprint arXiv:2305.182 90, 2023

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:32.104500Z

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.

Observation a4b0f2e9-59f8-49fc-8940-fda9b2a8acdc · outbound

This paper cites an unresolved cited work.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:37:31.855023Z

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.

Observation 6a95aa98-67e8-4913-9d7f-6427323c719b · outbound

This paper cites Can Neural Machine Translation be Improved with User Feedback?.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Can Neural Machine Translation be Improved with User Feedback?

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T12:37:27.553834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d495648-b221-4c8f-b183-130582deb9f9 · outbound

This paper cites Ethayarajh et al., ”Understanding dataset difﬁculty with V-usable information,” in Proc.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Ethayarajh et al., ”Understanding dataset difﬁculty with V-usable information,” in Proc

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:31.654543Z

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.

Observation a128c53d-dc0e-4b5c-b2e9-1d1af02ce6f4 · outbound

This paper cites Clark et al., ”All that’s ’human’ is not gold: Evaluati ng human evaluation of generated text,” in Proc.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Clark et al., ”All that’s ’human’ is not gold: Evaluati ng human evaluation of generated text,” in Proc

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:31.476976Z

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.

Observation c7879c9e-d175-49ab-8309-718de3141ca1 · outbound

This paper cites RewardBench: Evaluating Reward Models for Language Modeling.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling RewardBench: Evaluating Reward Models for Language Modeling

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:37:27.821274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 520eca08-0c0e-45db-8dd5-b68122c4cd22 · outbound

This paper cites an unresolved cited work.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:37:31.299066Z

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.

Observation dd5d2ee3-bf56-427f-84ca-2577166f32db · outbound

This paper cites Plank et al., ”Learning part-of-speech taggers with i nter-annotator agreement loss,” in Proc.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Plank et al., ”Learning part-of-speech taggers with i nter-annotator agreement loss,” in Proc

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:30.997342Z

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.

Observation 1ebd8f4f-0b00-467b-a66d-e3220bda813b · outbound

This paper cites Dubois et al., ”AlpacaFarm: A simulation framework f or methods that learn from human feedback,” in Proc.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Dubois et al., ”AlpacaFarm: A simulation framework f or methods that learn from human feedback,” in Proc

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:30.755906Z

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.

Observation 77a74a76-cac4-4829-9c53-0420b17cea5f · outbound

This paper cites Constitutional AI: Harmlessness from AI Feedback.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Constitutional AI: Harmlessness from AI Feedback

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:37:28.129798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2e6eddf-5da3-4edf-9115-a1af7253a984 · outbound

This paper cites an unresolved cited work.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:37:30.451201Z

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.

Observation 4be2d518-ff8e-4775-9bec-e524d21f0a59 · outbound

This paper cites Zhang et al., ”Fuzzy sentiment analysis based on intu itionistic fuzzy sets,” Expert Systems with Applications, vol.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Zhang et al., ”Fuzzy sentiment analysis based on intu itionistic fuzzy sets,” Expert Systems with Applications, vol

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:30.172087Z

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.

Observation dbba2d25-6885-48c4-82ef-624bfbfa8b52 · outbound

This paper cites Li et al., ”Fuzzy text classiﬁcation based on intuiti onistic fuzzy cross entropy,” Journal of Intelligent & Fuzzy Systems, vol.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Li et al., ”Fuzzy text classiﬁcation based on intuiti onistic fuzzy cross entropy,” Journal of Intelligent & Fuzzy Systems, vol

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:30.015125Z

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.

Observation c40d9f03-b03b-4116-8d50-32751badb8a6 · outbound

This paper cites Bordogna and G.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Bordogna and G

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:29.827323Z

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.

Observation 2af39d8f-1c96-448a-b594-037d6ff31514 · outbound

This paper cites Xu, ”Intuitionistic fuzzy aggregation operators,” IEEE Transactions on Fuzzy Systems, vol.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Xu, ”Intuitionistic fuzzy aggregation operators,” IEEE Transactions on Fuzzy Systems, vol

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:29.657042Z

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.

Observation 0f0b27c9-c3a7-4d78-a88b-475951f833a3 · outbound

This paper cites an unresolved cited work.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:37:29.532313Z

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.

Observation f9811f8b-913a-4fad-8bd1-2c5971f544ad · outbound

This paper cites Szmidt and J.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Szmidt and J

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:29.391264Z

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.

Observation a0411021-a70c-41d1-a597-23f9286cb68b · outbound

This paper cites an unresolved cited work.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Unresolved cited work

Reference 19

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:37:29.237510Z

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.

Observation 9779b603-1625-40ef-8390-53884e72ba49 · outbound

This paper cites Liu and F.

Intuitionistic Fuzzy Sets for Large Language Model Data Annotation: A Novel Approach to Side-by-Side Preference Labeling Liu and F

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:37:29.091408Z

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.

Pith citing papers

No inbound Pith citation observations are available.