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cs.AI2026
PRIME: Evaluating Prompt Resolution Under Incompatible Instructions in LLMs
Tehreem Javed, Shumaim Fatimah, Masooma Bakhtiari +2
Large language models (LLMs) often encounter conflicting prompts, although current instruction following benchmarks assess those meta-instructions in isolation, limiting the insigh…
cs.AI2026
From Affect Prediction to Affect Forecasting: Evidence for Distinct Information Sources in Longitudinal Text
Sadia Noor, Seemab Latif, Raja Khurram Shahzad +1
Modeling dimensional affect in longitudinal text requires distinguishing current affect estimation from future affective change forecasting. Existing approaches often treat each te…