Paper Citation Record · LEDGER

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection

As of 7 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2505.16460.

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

pith.paper-citation-record.v1
2505.16460 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:04:43.101367Z

measured 17 of 17 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

17 of 17 outbound references displayed

verified exact0
verified fuzzy6
unresolved11
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0d7adc11-f297-449a-ae09-a9ae78ed1021 · outbound

This paper cites Unsupervised Cross-lingual Representation Learning at Scale.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection Unsupervised Cross-lingual Representation Learning at Scale

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.041773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd265a3c-f388-4a0a-8b28-a0aee5e255a4 · outbound

This paper cites Preprint, arXiv:2502.13595.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection Preprint, arXiv:2502.13595

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.056158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8cf9682-177f-431b-aeb3-0b4ce5bf2192 · outbound

This paper cites The Llama 3 Herd of Models.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection The Llama 3 Herd of Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.060151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d178eeaa-bc5f-4fbc-8169-4539f2e457bc · outbound

This paper cites In Proceedings of the 18th International Workshop on Semantic Evalua- tion (SemEval-2024), pages 1405–1411, Mexico City, Mexico.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection In Proceedings of the 18th International Workshop on Semantic Evalua- tion (SemEval-2024), pages 1405–1411, Mexico City, Mexico

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:43.345529Z

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.

Observation 98ecceda-ed29-4997-a610-3efacf91e2fd · outbound

This paper cites In Findings of the Asso- ciation for Computational Linguistics: EACL 2023, pages 1825–1836, Dubrovnik, Croatia.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection In Findings of the Asso- ciation for Computational Linguistics: EACL 2023, pages 1825–1836, Dubrovnik, Croatia

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:43.323992Z

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.

Observation 3909f768-4d22-4fac-a28f-d04b062b1132 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection MTEB: Massive Text Embedding Benchmark

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.079943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e55bd6f7-8e54-4ce2-a4d2-6fb29c486d6d · outbound

This paper cites GPT-4 Technical Report.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection GPT-4 Technical Report

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.084520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19b1578c-66a4-4ff6-9362-e3b91855210c · outbound

This paper cites jina-embeddings-v3: Multilingual Embeddings With Task LoRA.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection jina-embeddings-v3: Multilingual Embeddings With Task LoRA

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.088561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 60c2b7d2-3b7c-4f3c-946b-22d6da63265b · outbound

This paper cites Multilingual E5 Text Embeddings: A Technical Report.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection Multilingual E5 Text Embeddings: A Technical Report

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.093166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec5db9c1-bdb0-40ea-a57c-148adebb7a63 · outbound

This paper cites Qwen2 Technical Report.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection Qwen2 Technical Report

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.097537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4c47ee9-d17e-4960-af6d-750ddcac1bd0 · outbound

This paper cites In Proceed- ings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection In Proceed- ings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:43.313115Z

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.

Observation 3402952f-0b3a-4436-b081-a1e9a313942d · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.051932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efe5f840-4bb1-449f-a3ae-65734b3ff411 · outbound

This paper cites Language Models are Few-Shot Learners.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection Language Models are Few-Shot Learners

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.032041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1555e75b-d241-40e7-bb41-6ad73ce5b51f · outbound

This paper cites In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1190–1200, Online.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 1190–1200, Online

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:43.301175Z

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.

Observation 1f239356-9d55-42b5-9064-5d0b84aeece7 · outbound

This paper cites In Findings of the Association for Computational Linguistics: ACL 2023, pages 5828–5843, Toronto, Canada.

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:43.334992Z

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.

Observation e4317fda-fed7-48cb-a69e-d0517046b707 · outbound

This paper cites In Findings of the Associa- tion for Computational Linguistics ACL 2024, pages 2318–2335.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection In Findings of the Associa- tion for Computational Linguistics ACL 2024, pages 2318–2335

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:04:43.356928Z

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.

Observation b9cc9055-69ef-43d7-a621-aa26de57d29a · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

University of Indonesia at SemEval-2025 Task 11: Evaluating State-of-the-Art Encoders for Multi-Label Emotion Detection DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T15:04:43.047327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.