Browse State-of-the-Art › Emotional Intelligence
Emotional Intelligence
19 papers with code · 1 benchmark · 2 datasets archive 2025-07-28
Emotional Intelligence (EI) is a measure of "The ability to monitor one’s own and others’ feelings, to discriminate among them, and to use this information to guide one’s thinking and action." (Salovey and Mayer, 1990). EI is further broken down into four branches: perceiving, using, understanding and managing emotions (Mayer & Salovey, 1997). Of particular relevance to language models that operate exclusively in the text modality is emotional understanding (EU). This is defined as the ability to interpret and analyse the language of emotions, to comprehend complex emotional states, and understand how these emotions can influence behaviour and decision-making.
Description from the archive archive 2025-07-28.
Benchmarks archive 2025-07-28
1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.
| Dataset | Best model (first row in archive order) | Paper | Code | Syntology | Compare |
|---|---|---|---|---|---|
| EQ-Bench (24 rows) | OpenAI gpt-4-0613 | EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models | code | Syntology ran 1 of 1 samples · 0 unverified | Compare |
Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
2 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
3 subtasks in the archive's task tree.
Most implemented papers archive 2025-07-28
19 shown of 19 papers with code (77 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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8 Dec 2021 3 repositories listedLanguage modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.
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3 Jul 2025 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)Large language models (LLMs) excel at logical and algorithmic reasoning, yet their emotional intelligence (EQ) still lags far behind their cognitive prowess.
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12 May 2025 1 repository listedThe advent of multimodal data and widespread communication has led to a proliferation of multimodal metaphors, amplifying the complexity of emotion classification compared to single-mode scenarios.
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4 Mar 2025 1 repository listedRecent advances in large language models have demonstrated impressive capabilities in task-oriented applications, yet building emotionally intelligent chatbots that can engage in natural, strategic conversations remains…
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18 Feb 2025 1 repository listedBuilding on these insights, we introduce two benchmark tasks: (1) persona simulation where a model continues a conversation on behalf of a specific user given prior dialogue context; and (2) memory probing where a model…
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9 Dec 2024 1 repository listed Syntology ran 0 of 9 samples · 9 unverifiedIn this work, we propose Skills Scaling Laws (SSLaws, pronounced as Sloth), a novel scaling law that leverages publicly available benchmark data and assumes LLM performance is driven by low-dimensional latent skills,…
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1 Jul 2024 1 repository listedWe introduce the concept of "empathic grounding" in conversational agents as an extension of Clark's conceptualization of grounding in conversation in which the grounding criterion includes listener empathy for the…
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24 Jun 2024 1 repository listedExperimental results demonstrate that EmoLLM significantly elevates multimodal emotional understanding performance, with an average improvement of 12.
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12 Jun 2024 1 repository listedHowever, using a single LLM judge is prone to intra-model bias, and many tasks - such as those related to emotional intelligence, creative writing, and persuasiveness - may be too subjective for a single model to judge…
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5 May 2024 1 repository listed Syntology ran 3 of 5 samples · 2 unverified · 5 pointer-only (licence)The results are revealing: NegativePrompt markedly enhances the performance of LLMs, evidenced by relative improvements of 12.
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19 Feb 2024 1 repository listedRecent advances in Large Language Models (LLMs) have highlighted the need for robust, comprehensive, and challenging benchmarks.
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15 Feb 2024 1 repository listedEmotional Intelligence (EI), consisting of emotion perception, emotion cognition and emotion expression, plays the critical roles in improving user interaction experience for the current large language model (LLM) based…
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11 Dec 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverifiedWe introduce EQ-Bench, a novel benchmark designed to evaluate aspects of emotional intelligence in Large Language Models (LLMs).
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15 Nov 2023 1 repository listedDo machines and humans process language in similar ways?
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19 Oct 2023 1 repository listedRecognizing that emotional intelligence encompasses a comprehension of worldly knowledge, we propose an innovative approach that integrates commonsense information with dialogue context to facilitate a deeper…
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5 Oct 2022 1 repository listedThis paper presents a web-based demonstration of Emotion Twenty Questions (EMO20Q), a dialog game whose purpose is to study how people describe emotions.
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25 Feb 2021 1 repository listedThe proposed RECS is capable of classifying emotions in real-time by training the model in an online fashion using an EEG signal stream.
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22 Nov 2020 1 repository listedThe representations learned by deep neural networks can indeed show an emotion-color association 2.
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12 Mar 2015 1 repository listedThis paper introduces a new computing model based on the cooperation among Turing machines called orchestrated machines.
Syntology lines on 4 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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