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Found 6 papers, 4 papers with code
Measuring the Robustness of Reference-Free Dialogue Evaluation Systems
Advancements in dialogue systems powered by large language models (LLMs) have outpaced the development of reliable evaluation metrics, particularly for diverse and creative responses.
CoAM: Corpus of All-Type Multiword Expressions
MWEs in CoAM are tagged with MWE types, such as Noun and Verb, to enable fine-grained error analysis.
Improving Explainability of Sentence-level Metrics via Edit-level Attribution for Grammatical Error Correction
Various evaluation metrics have been proposed for Grammatical Error Correction (GEC), but many, particularly reference-free metrics, lack explainability.
Beyond Film Subtitles: Is YouTube the Best Approximation of Spoken Vocabulary?
Word frequency is a key variable in psycholinguistics, useful for modeling human familiarity with words even in the era of large language models (LLMs).
How to Make the Most of LLMs' Grammatical Knowledge for Acceptability Judgments
The grammatical knowledge of language models (LMs) is often measured using a benchmark of linguistic minimal pairs, where LMs are presented with a pair of acceptable and unacceptable sentences and required to judge which is acceptable.
knn-seq: Efficient, Extensible kNN-MT Framework
We publish our knn-seq as an MIT-licensed open-source project and the code is available on https://github. com/naist-nlp/knn-seq .
