Systematicity in GPT-3’s Interpretation of Novel English Noun Compounds (2022.findings-emnlp)
Copied to clipboard
| Challenge: | e.g., stew skillet, swamp squash) are not fully compositional, but highly predictable based on whether the modifier and head refer to artifacts or natural kinds. |
| Approach: | They propose to compare the interpretations of novel English noun compounds with the large language model GPT-3, which is governed by interpretive principles. |
| Outcome: | The results show that the large language model GPT-3 reasoning only about specific lexical items is consistent with the Levin et al.'s theory. |
Similar Papers
Can Large Language Models Interpret Noun-Noun Compounds? A Linguistically-Motivated Study on Lexicalized and Novel Compounds (2024.acl-long)
Copied to clipboard
| Challenge: | Noun-noun compounds represent an important challenge for Natural Language Understanding . correct interpretation of noun-nomin compounds is essential for many applications . |
| Approach: | They test whether Large Language Models can interpret the semantic relation between nouns . they also test whether they can abstract from such knowledge to predict the relation . |
| Outcome: | The proposed models can interpret the semantic relation between nouns and compounds using analogical comparisons. |
From chocolate bunny to chocolate crocodile: Do Language Models Understand Noun Compounds? (2023.findings-acl)
Copied to clipboard
| Challenge: | Noun compound interpretation is the task of expressing a noun compound in a free-text paraphrase that makes the relationship between the constituent nouns explicit. |
| Approach: | They propose modifications to the standard task and propose a new task that solves it. |
| Outcome: | The proposed task solves the standard task of paraphrasing a noun compound in a free-text paraphrase that makes the relationship between the constituent nouns explicit. |
Modeling the Evolution of English Noun Compounds with Feature-Rich Diachronic Compositionality Prediction (2025.acl-long)
Copied to clipboard
| Challenge: | Empirical research directly addressing these issues is limited to a small number of studies suggesting that compounding is a highly productive process. |
| Approach: | They represent English noun compounds as vectors of time-specific values and implement a set of features to classify them for present-day compositionality and assess the informativeness of the corresponding linguistic patterns. |
| Outcome: | The proposed method captures relevant and complementary information across approaches and shows that low-compositional meanings are reflected by a parallel drop in compositionality and sustained semantic change. |
Analyzing the Understanding of Morphologically Complex Words in Large Language Models (2024.lrec-main)
Copied to clipboard
| Challenge: | Morphologically complex languages are challenging for NLP as a large amount of information is condensed into a single word, unlike in analytical languages where separate words make it easier to derive meaning. |
| Approach: | They use a Large Language Model to analyse compositional word formation and derivation to find ill-formed word forms. |
| Outcome: | The proposed model is capable of solving most tasks except identifying ill-formed word forms. |
Compositional Networks Enable Systematic Generalization for Grounded Language Understanding (2021.findings-emnlp)
Copied to clipboard
| Challenge: | a recent study shows that deep networks can mimic some human language abilities when presented with novel sentences . a general-purpose mechanism that enables agents to generalize their language understanding to compositional domains is critical to building safe and fair robots, says a new study. |
| Approach: | They build a general-purpose mechanism that enables agents to generalize their language understanding to compositional domains. |
| Outcome: | a new network generalizes its language understanding to compositional domains while generalizing its knowledge when prior work does not. |
COGS: A Compositional Generalization Challenge Based on Semantic Interpretation (2020.emnlp-main)
Copied to clipboard
| Challenge: | Natural language is characterized by compositionality: meaning of complex expressions is constructed from the meanings of its constituent parts. |
| Approach: | They propose a semantic parsing dataset based on a fragment of English to assess compositional generalization abilities. |
| Outcome: | The proposed model can generalize meanings in a given sentence in 96–99% of the tests, but generalization accuracy is lower and the generalization sensitivity is higher. |
A Couch Potato is not a Potato on a Couch: Prompting Strategies, Image Generation, and Compositionality Prediction for Noun Compounds (2025.findings-acl)
Copied to clipboard
| Challenge: | a new method to predict the compositionality of English noun compounds is proposed . |
| Approach: | They propose a visual modality and vision transformers to predict the compositionality of English noun compounds. |
| Outcome: | The proposed method compared with a state-of-the-art text-based approach reveals complementary contributions regarding features and degrees of abstractness in English noun compounds. |
Do Neural Language Models Inferentially Compose Concepts the Way Humans Can? (2024.lrec-main)
Copied to clipboard
| Challenge: | a new study shows that language models and humans may rely on different approaches to represent and compose lexical items across sentence structure. |
| Approach: | They propose to use a dataset to test the performance of neural language models and humans on inferentially driven conceptual compositions. |
| Outcome: | The proposed model elicits probability estimates for a noun in a minimally composed phrase . RoBERTa, BERT-large, and GPT-2 exhibited the closest resemblance to human responses . |
Towards a Standardized Dataset for Noun Compound Interpretation (L18-1)
Copied to clipboard
| Challenge: | Noun compounds are interesting constructs in Natural Language Processing . lack of standardized set of relation inventories and annotated datasets hinders interpretation . |
| Approach: | They propose a dataset that uses FrameNet as its semantic relation inventory to examine noun compounds. |
| Outcome: | The proposed dataset is linguistically grounded and uses FrameNet as its semantic relation inventory. |
On Evaluating Multilingual Compositional Generalization with Translated Datasets (2023.acl-long)
Copied to clipboard
| Challenge: | a growing amount of research investigating compositional generalization in NLP is done on English . a critical semantic distortion is a limitation of the translation of datasets . |
| Approach: | They propose to translate a dataset for evaluating compositional generalization in semantic parsing. |
| Outcome: | The proposed benchmarks show that the translation of the MCWQ dataset suffers from semantic distortion. |