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@@ -21,10 +21,13 @@ metrics:
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  # Human Value Detection – DeBERTa + LIWC-22
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- This model is the **DeBERTa + LIWC-22 feature-augmented 19-way value detector** from the paper:
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  > *Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum*
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- > Víctor Yeste, Paolo Rosso (2026)
 
 
 
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  It is a **multi-label classifier** over the **19 refined Schwartz basic values**, trained on the **English, machine-translated** portion of the ValueEval'24 / ValuesML corpus, and **augmented with LIWC-22 sentence-level features**.
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@@ -229,10 +232,13 @@ On the English ValueEval’24 sentence-level splits, the paper compares:
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  - Instruction-tuned LLM baselines (7–9B)
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  - A small soft-voting ensemble of DeBERTa-based models
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- The LIWC-22–augmented model improves over the text-only baseline; for exact macro–F₁ scores and per-label results, please refer to the paper:
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  Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum
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- Víctor Yeste, Paolo Rosso (2026)
 
 
 
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  ---
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@@ -279,6 +285,16 @@ If you use this model or the associated code in your research, please cite:
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  primaryClass={cs.CL},
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  url={https://arxiv.org/abs/2601.14172},
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  }
 
 
 
 
 
 
 
 
 
 
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  ```
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  You may also want to cite the ValueEval / ValuesML dataset:
 
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  # Human Value Detection – DeBERTa + LIWC-22
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+ This model is the **DeBERTa + LIWC-22 feature-augmented 19-way value detector** from the papers:
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  > *Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum*
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+ > Víctor Yeste, Paolo Rosso (2026), arXiv:2601.14172
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+
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+ > *Do Schwartz Higher-Order Values Help Sentence-Level Human Value Detection? When Hard Gating Hurts*
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+ > Víctor Yeste, Paolo Rosso (2026), arXiv:2602.00913
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  It is a **multi-label classifier** over the **19 refined Schwartz basic values**, trained on the **English, machine-translated** portion of the ValueEval'24 / ValuesML corpus, and **augmented with LIWC-22 sentence-level features**.
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  - Instruction-tuned LLM baselines (7–9B)
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  - A small soft-voting ensemble of DeBERTa-based models
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+ The LIWC-22–augmented model improves over the text-only baseline; for exact macro–F₁ scores and per-label results, please refer to the papers:
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  Human Values in a Single Sentence: Moral Presence, Hierarchies, and Transformer Ensembles on the Schwartz Continuum
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+ Víctor Yeste, Paolo Rosso (2026), arXiv:2601.14172
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+
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+ Do Schwartz Higher-Order Values Help Sentence-Level Human Value Detection? When Hard Gating Hurts
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+ Víctor Yeste, Paolo Rosso (2026), arXiv:2602.00913
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  ---
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  primaryClass={cs.CL},
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  url={https://arxiv.org/abs/2601.14172},
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  }
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+
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+ @misc{yeste2026schwartzhigherordervalueshelp,
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+ title={Do Schwartz Higher-Order Values Help Sentence-Level Human Value Detection? When Hard Gating Hurts},
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+ author={Víctor Yeste and Paolo Rosso},
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+ year={2026},
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+ eprint={2602.00913},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2602.00913},
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+ }
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  ```
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  You may also want to cite the ValueEval / ValuesML dataset: