Papers with relational understanding

3 papers
Modelling Analogies and Analogical Reasoning: Connecting Cognitive Science Theory and NLP Research (2026.tacl-1)

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Challenge: Analogical reasoning is an essential aspect of human cognition, says aaron eliotta . eelisa e. sabet: some have argued that analogy is central to the human cognitive experience .
Approach: They summarize key theories about the processes underlying analogical reasoning from the cognitive science literature and relate it to current research in natural language processing.
Outcome: The proposed approaches are relevant for several major challenges in natural language processing, not directly related to analogy solving.
Curriculum Masking in Vision-Language Pretraining to Maximize Cross Modal Interaction (2024.naacl-long)

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Challenge: masked language modeling is widely used as a pretraining component in Vision and language (V+L) but performance on benchmarks has not received the attention it deserves.
Approach: They propose a curriculum masking scheme that uses a parallel mask selection agent to mask tokens at a frequency proportional to the level of cross modal interaction necessary to reconstruct them.
Outcome: The proposed method improves relational understanding on a wide range of V+L tasks.
SciCompanion: Graph-Grounded Reasoning for Structured Evaluation of Scientific Arguments (2025.findings-emnlp)

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Challenge: Existing retrieval-augmented generation (RAG) methods fail to provide deep, relational understanding of scientific literature.
Approach: They propose a graph-grounded reasoning framework for structured scientific evaluation that uses multi-hop reasoning to iteratively construct contextual graphs and generate structured critiques.
Outcome: The proposed framework reduces evaluation error by over 30% compared to baselines and allows smaller models to outperform larger models.

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