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pith:CUN64YEZ

pith:2026:CUN64YEZODRN37IIR3JG3DAU6C
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UKP_Psycontrol at SemEval-2026 Task 2: Modeling Valence and Arousal Dynamics from Text

Amaia Zurinaga, Darya Hryhoryeva, Hamidreza Jamalabadi, Iryna Gurevych

LLMs capture current emotions from text well, but recent numeric trajectories explain short-term changes better than text semantics.

arxiv:2604.21534 v2 · 2026-04-23 · cs.CL

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4 Citations open
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Claims

C1strongest claim

Our findings indicate that LLMs effectively capture static affective signals from text, whereas short-term affective variation in this dataset is more strongly explained by recent numeric state trajectories than by textual semantics.

C2weakest assumption

That the SemEval-2026 Task 2 dataset and evaluation metric provide a valid test of real-world affective dynamics modeling, with no major biases in the chronologically ordered texts or labels.

C3one line summary

LLMs capture static affective signals from text effectively, but short-term affective variation is better explained by recent numeric state trajectories than by textual semantics in this dataset.

Receipt and verification
First computed 2026-05-28T01:05:12.375179Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

151bee609970e2ddfd088ed26d8c14f088c60c64e56160f1156a26de111440b1

Aliases

arxiv: 2604.21534 · arxiv_version: 2604.21534v2 · doi: 10.48550/arxiv.2604.21534 · pith_short_12: CUN64YEZODRN · pith_short_16: CUN64YEZODRN37II · pith_short_8: CUN64YEZ
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/CUN64YEZODRN37IIR3JG3DAU6C \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 151bee609970e2ddfd088ed26d8c14f088c60c64e56160f1156a26de111440b1
Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-04-23T10:55:27Z",
    "title_canon_sha256": "4b2c5cdc610a24350bd6c9d10057f271aef8175aa1c582ff704c29be0199c293"
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