Paper Citation Record · LEDGER

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs

As of 17 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2505.22548.

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

pith.paper-citation-record.v1
2505.22548 v2

Coverage vector

measured 44 of 44 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:11:44.230612Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:06:43.252559Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

44 of 44 outbound references displayed

verified exact2
verified fuzzy22
unresolved20
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e4aaf5f-5993-4cc7-8750-28d2605e5d44 · outbound

This paper cites Will affective computing emerge from foun- dation models and general artificial intelligence? a first evaluation of chatgpt.IEEE Intelligent Systems, 38(2):15–23, 2023.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Will affective computing emerge from foun- dation models and general artificial intelligence? a first evaluation of chatgpt.IEEE Intelligent Systems, 38(2):15–23, 2023

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:50.287686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 31a1cd20-13e9-467a-9ad9-0252260c575c · outbound

This paper cites Graph of thoughts: Solving elaborate problems with large language models.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Graph of thoughts: Solving elaborate problems with large language models

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:50.093626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 99906b90-7b9c-4a40-94b0-bd357fe6ae57 · outbound

This paper cites Language models are few-shot learn- ers.Advances in neural information processing sys- tems, 33:1877–1901, 2020.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Language models are few-shot learn- ers.Advances in neural information processing sys- tems, 33:1877–1901, 2020

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:39.326078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a0691a4e-fb0d-4de2-88e8-caffe2c12f64 · outbound

This paper cites Sentiment and emotion help sarcasm? a multi-task learning framework for multi-modal sarcasm, sentiment and emotion analysis.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Sentiment and emotion help sarcasm? a multi-task learning framework for multi-modal sarcasm, sentiment and emotion analysis

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:49.925683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c958bc49-48c7-4c71-b60d-88035d3572a8 · outbound

This paper cites A sentiment and emotion aware multimodal multiparty humor recognition in multilingual conversational set- ting.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs A sentiment and emotion aware multimodal multiparty humor recognition in multilingual conversational set- ting

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:49.788759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e8928faf-1b94-4345-acb6-75af253f3890 · outbound

This paper cites an unresolved cited work.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:11:49.563456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 14f27472-8671-4e33-8160-b2971ef3fb07 · outbound

This paper cites Clancey.Transfer of Rule-Based Exper- tise through a Tutorial Dialogue.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Clancey.Transfer of Rule-Based Exper- tise through a Tutorial Dialogue

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:49.384098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b37fe634-a96d-48e1-92e7-744cfa3c323a · outbound

This paper cites an unresolved cited work.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:11:49.215394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 358b9748-5eff-4da9-8a27-3ba361ba5042 · outbound

This paper cites an unresolved cited work.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:11:49.060816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 6295f9de-8092-4954-9487-8ac561ed9447 · outbound

This paper cites an unresolved cited work.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:11:48.907228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d00a4935-4ddb-4286-80e8-99745ba4899f · outbound

This paper cites an unresolved cited work.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:11:48.764682Z

Source-reported events for the cited work

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Observation 330a8962-6d36-4b38-af96-62b27e36e2b9 · outbound

This paper cites Bert: Pre-training of deep bidi- rectional transformers for language understanding.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Bert: Pre-training of deep bidi- rectional transformers for language understanding

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:40.254306Z

Source-reported events for the cited work

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Observation 8cba0906-79ca-45f2-99c5-752b0cc7e889 · outbound

This paper cites Blackboard Systems.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Blackboard Systems

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:48.556881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation dfa9b205-b331-4c7f-8cca-7591e5c644b5 · outbound

This paper cites Ox- ford University Press, USA, 2002.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Ox- ford University Press, USA, 2002

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:48.343120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation be97dbf5-6ada-4dae-8e56-ad7aebeae298 · outbound

This paper cites Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:40.514628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 864100f9-5caf-4781-bb76-c56868246f23 · outbound

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

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:40.687540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6ba15a7-26f2-4a5a-8082-5ba2103202f4 · outbound

This paper cites Clancey, and Glenn Rennels.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Clancey, and Glenn Rennels

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:48.147419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation eddff1c3-d4f8-49a9-9058-90029a492a97 · outbound

This paper cites Clancey, Glenn R.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Clancey, Glenn R

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:47.957150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ce3a5573-ef54-42a1-a2e4-11fce5108ed4 · outbound

This paper cites OpenAI o1 System Card.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs OpenAI o1 System Card

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:41.064935Z

Source-reported events for the cited work

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Observation ccfb7277-d21d-40ae-89be-c5316b333732 · outbound

This paper cites an unresolved cited work.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:11:47.762244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 642a122f-c2c1-42c1-9c29-82f0dcce6e91 · outbound

This paper cites GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:41.424406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2bee089c-67a5-4e70-bffb-8fc735205df2 · outbound

This paper cites Pluto: The ’other’ red planet.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Pluto: The ’other’ red planet

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:47.587148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c3fda148-d88f-49c8-94a7-7ad275857a2f · outbound

This paper cites A Review of Affective Generation Models.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs A Review of Affective Generation Models

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:11:44.834843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4cdf0f8f-5b22-4324-b8c1-113ef5bedfe5 · outbound

This paper cites an unresolved cited work.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:11:47.393001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d1f5e67a-f1e2-4c56-86d1-63aa8804bcc2 · outbound

This paper cites Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:41.947432Z

Source-reported events for the cited work

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Observation a6438338-9160-4df3-8fb1-5a03a1a83373 · outbound

This paper cites MIT press, 2000.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs MIT press, 2000

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:42.127494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68fb445d-6e54-401c-9cb8-cca0d63f89d6 · outbound

This paper cites MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:42.287535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77bbfd71-28b3-40a9-a3f7-b19b1ec733c8 · outbound

This paper cites Poligon: A System for Parallel Problem Solving.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Poligon: A System for Parallel Problem Solving

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:47.169674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d9f69f41-fb2d-4aa5-aa31-362b48c4b07a · outbound

This paper cites Robinson.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Robinson

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:46.975267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 570684ae-5244-429f-b495-bd8a1cf32b81 · outbound

This paper cites Robinson.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Robinson

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:46.808753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0c516447-98c3-476d-83a6-1dea4cfc78df · outbound

This paper cites Instruction tuning for large language models: A survey.arXiv preprint arXiv:2308.10792, 2023.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Instruction tuning for large language models: A survey.arXiv preprint arXiv:2308.10792, 2023

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:42.819686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5077f970-5530-406e-a98c-c254dd2f654a · outbound

This paper cites A survey of sentiment analysis: Approaches, datasets, and future research.Applied Sciences, 13(7):4550, 2023.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs A survey of sentiment analysis: Approaches, datasets, and future research.Applied Sciences, 13(7):4550, 2023

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:46.640322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bac5bacd-007e-4b0a-b644-ed46533848af · outbound

This paper cites Qwq-32b: Embracing the power of rein- forcement learning, March 2025.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Qwq-32b: Embracing the power of rein- forcement learning, March 2025

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:46.377543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0bd572b9-6768-4233-b61f-831ce16dd3f6 · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:43.214868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b06a696-8b8d-4f12-9b1a-0d68b60a973f · outbound

This paper cites Tech- niques of sarcasm detection: A review.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Tech- niques of sarcasm detection: A review

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:46.109228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ead67ed9-6ffd-4d26-b98f-69aa445a7349 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advances in neural informa- tion processing systems, 35:24824–24837, 2022.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Chain-of-thought prompting elicits reasoning in large language models.Advances in neural informa- tion processing systems, 35:24824–24837, 2022

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:45.926260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2c3baebf-602e-499d-8e68-454891a77778 · outbound

This paper cites Humor detection: A transformer gets the last laugh.”Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing”, November 2019.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Humor detection: A transformer gets the last laugh.”Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing”, November 2019

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:45.761855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d13fb2b8-4264-440b-8284-04716257e292 · outbound

This paper cites Tokenskip: Controllable chain-of- thought compression in llms, 2025.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Tokenskip: Controllable chain-of- thought compression in llms, 2025

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:45.594953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ac62ba94-0690-4a9e-a719-413106237e59 · outbound

This paper cites Is sarcasm detection a step-by-step reasoning process in large language models? InProceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 25651–25659, 2025.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Is sarcasm detection a step-by-step reasoning process in large language models? InProceedings of the AAAI Conference on Artificial Intelligence, volume 39, pages 25651–25659, 2025

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:45.490448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c6b17fa7-70c1-46b1-8ee7-bf371b9042a3 · outbound

This paper cites Tree of Thoughts: Deliberate Problem Solving with Large Language Models.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Tree of Thoughts: Deliberate Problem Solving with Large Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:43.842902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6869966-56f3-44d5-8971-b168b6a7522e · outbound

This paper cites Cmma: benchmarking multi- affection detection in chinese multi-modal conversa- tions.Advances in Neural Information Processing Sys- tems, 36:18794–18805, 2023.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Cmma: benchmarking multi- affection detection in chinese multi-modal conversa- tions.Advances in Neural Information Processing Sys- tems, 36:18794–18805, 2023

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:45.354309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 52ef022d-0fac-4a0e-a7d1-43be1d38dc87 · outbound

This paper cites Sarcasmbench: Towards evaluat- ing large language models on sarcasm understanding, 2024.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Sarcasmbench: Towards evaluat- ing large language models on sarcasm understanding, 2024

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:11:45.177434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 68ebb27c-2156-474e-9ec1-9777c9ed5bcb · outbound

This paper cites Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General Intelligence.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General Intelligence

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:11:44.454390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2226a87d-1d33-4c0d-800a-980f0645ba91 · outbound

This paper cites Large language models are human-level prompt engineers.

Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs Large language models are human-level prompt engineers

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T13:11:44.230612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation efdde13d-893a-4e6c-b58a-89e3e260d98f · inbound

Towards High-Level Semantic Intelligence cites this paper.

Towards High-Level Semantic Intelligence Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMs

Reference 260

Resolution: unresolved; no resolver link, observed 2026-07-31T23:06:43.252559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.