Papers by Begoña Altuna

2 papers
This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models (2023.emnlp-main)

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Challenge: Large language models (LLMs) have grammatical knowledge but fail to interpret negation . a recent study shows that LLMs struggle with negative sentences .
Approach: They propose to use a dataset to grasp LLMs' generalization and inference capability . they also fine-tuned models to assess whether the understanding of negation can be trained .
Outcome: The proposed model is able to generalize and infer negation in 400,000 sentences . but it is suboptimal when it comes to negation, a key step in natural language processing .
A Multi-layered Approach to Physical Commonsense Understanding: Creation and Evaluation of an Italian Dataset (2024.lrec-main)

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Challenge: Using a multilingual model, we examine the ability of large language models to perform reasoning tasks.
Approach: They propose to use a multilingual model to analyze commonsense reasoning in large language models for Italian and to provide a semi-automated system to complete the annotation.
Outcome: The proposed model performs at high-level classification tasks but its easoning is inconsistent and unverifiable, since it does not capture intermediate evidence.

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