Papers with conceptual abstraction

2 papers
Concept-Reversed Winograd Schema Challenge: Evaluating and Improving Robust Reasoning in Large Language Models via Abstraction (2025.naacl-short)

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Challenge: Recent research has revealed that Large Language Models (LLMs) often experience issues with hallucinations and unreliable reasoning due to semantic associations and superficial logical chains.
Approach: They propose a concept-reversed Winograd Schema Challenge dataset to evaluate the robustness of Large Language Models (LLMs) they propose Abstraction-of-Thought (AoT) method for recovering adversarial cases to normal cases using conceptual abstraction to improve LLMs’ robustness and consistency in reasoning.
Outcome: The proposed method improves LLMs’ robustness and consistency in reasoning under adversarial and long-tail scenarios.
The Contextual Variability of English Nouns: The Impact of Categorical Specificity beyond Conceptual Concreteness (2024.lrec-main)

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Challenge: Empirical studies on conceptual abstraction have examined differences in contextual distributions of abstract and concrete concept words.
Approach: They propose to use a model to investigate the interplay between contextual variability and specificity of abstract and concrete concepts.
Outcome: The proposed models show that more specific words have closer contexts than generic terms.

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