| Challenge: | Language modeling is a core task in natural language processing. |
| Approach: | They propose to characterize leakage onto the set of infinite sequences by a measure-theoretic approach. |
| Outcome: | The proposed language model families are tight, meaning they will not leak . the proposed language models are based on the 'sequence leakage' hypothesis . |
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| Challenge: | In some pathological situations, such a stochastic process may "leak" probability mass onto the set of infinite strings. |
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| Challenge: | Dissimilarity measures measure the extent to which two model’s internal representations differ . they can identify and locate generalization properties of models that are invisible via in-distribution test set performance. |
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A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations (2024.emnlp-main)
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Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, Mizanur Rahman, Mohammad Abdullah Matin Khan, Haidar Khan, Israt Jahan, Amran Bhuiyan, Chee Wei Tan, Md Rizwan Parvez, Enamul Hoque, Shafiq Joty, Jimmy Huang
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Evaluating Large Language Models on Controlled Generation Tasks (2023.emnlp-main)
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| Challenge: | Large language models (LLMs) have demonstrated impressive capabilities across a wide range of tasks in various domains, but they can be unreliable due to factual errors in their generations. |
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| Challenge: | Despite their wide adoption, the biases and unintended behaviors of language models remain poorly understood. |
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Language Model Evaluation Beyond Perplexity (2021.acl-long)
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| Challenge: | a nascent literature on probing language models has focused on studying linguistic phenomena. |
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