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Found 4 papers, 2 papers with code
Improving Open-Ended Text Generation via Adaptive Decoding
Current language models decode text token by token according to probabilistic distribution, and determining the appropriate candidates for the next token is crucial to ensure generation quality.
Is Cognition and Action Consistent or Not: Investigating Large Language Model's Personality
In this study, we investigate the reliability of Large Language Models (LLMs) in professing human-like personality traits through responses to personality questionnaires.
CLEAN-EVAL: Clean Evaluation on Contaminated Large Language Models
The best candidate is finally selected from this set based on the BLEURT score.
Penalty Decoding: Well Suppress the Self-Reinforcement Effect in Open-Ended Text Generation
This paper investigates the self-reinforcement effect in text generation and the effectiveness of a repetition penalty to mitigate it.
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