Papers with human supervision

3 papers
Using Crowd Agreement for Wordnet Localization (L18-1)

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Challenge: Lexical-semantic resources like WordNet are a fundamental resource for many NLP and semantic applications.
Approach: They propose a crowdsourcing workflow that consists of synset localization and validation . they use inter-rater agreement metrics to estimate the precision of the results .
Outcome: The proposed method is cost-effective and provides a good trade-off between quality and speed of progress.
Query-Efficient Black-Box Red Teaming via Bayesian Optimization (2023.acl-long)

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Challenge: Existing methods for generating test cases and querying fail to be query-efficient . generative models can be used for open-domain dialogue, prompt continuation, text-to-image generation .
Approach: They propose a query-efficient method that iteratively finds diverse positive test cases leading to model failures by utilizing user input and past evaluations.
Outcome: The proposed method finds a significantly larger number of diverse positive test cases under limited query budget than baseline methods.
Generative Reward Modeling via Synthetic Criteria Preference Learning (2025.acl-long)

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Challenge: Generative Reward Models (GenRMs) leverage synthesized Chains of Thought (CoT) but this approach introduces risks of overoptimization due to the inability to guarantee the correctness of the CoTs.
Approach: They propose a criteria-based preference tree for GenRMs that uses chain of thought to generate reasoning . they show that synthesized data can be learned using a long CoT format .
Outcome: The proposed model shows significant improvements over baselines on multiple human preference benchmarks.

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