Papers with abstraction
Humans and transformer LMs: Abstraction drives language learning (2026.eacl-long)
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| Challenge: | lexical semantic and syntactic categories emerge using novel divergence-based metrics . |
| Approach: | They compare transformer-based language model's linguistic categories learning to exemplar-based accounts of human language acquisition. |
| Outcome: | The proposed model can be used as an existence proof for human language acquisition. |
Draw Me a Flower: Processing and Grounding Abstraction in Natural Language (2022.tacl-1)
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| Challenge: | Abstraction is a core tenet of human cognition and communication. yet, interpreting and grounding abstraction expressed in natural language (NL) has not been systematically studied in NLP. |
| Approach: | They propose a 2D instruction-following game that elicits abstract instructions from 4k natural language instructions. |
| Outcome: | The proposed method elicits 4k natural language instructions rich with diverse types of abstractions and assesses neural models. |
Scoring Sentence Singletons and Pairs for Abstractive Summarization (P19-1)
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Logan Lebanoff, Kaiqiang Song, Franck Dernoncourt, Doo Soon Kim, Seokhwan Kim, Walter Chang, Fei Liu
| Challenge: | Existing methods for summarizing content from single sentences are inadequately understood. |
| Approach: | They propose to combine singletons and pairs to create a summarizing sentence . they use a dataset of human-written abstracts to examine human-writing methods . |
| Outcome: | The proposed framework is based on human-written abstracts from three large datasets. |
Life is a Circus and We are the Clowns: Automatically Finding Analogies between Situations and Processes (2022.emnlp-main)
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| Challenge: | Analogy-making gives rise to reasoning, abstraction, flexible categorization and counterfactual inference – abilities that current AI systems lack. |
| Approach: | They propose an interpretable, scalable algorithm that extracts analogies from a pair of natural language procedural texts and finds a mapping between the different domains based on relational similarity. |
| Outcome: | The proposed algorithm can extract analogies from a large dataset and achieve 79% precision. |
Emergence of Hierarchical Reference Systems in Multi-agent Communication (2022.coling-1)
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| Challenge: | a hierarchical reference system allows the selection of the most appropriate level of specificity for a given context. |
| Approach: | They propose a hierarchical reference game to study the emergence of hierarchic reference systems in artificial agents. |
| Outcome: | The proposed game shows that agents can generalize to new concepts . the hierarchical reference game is based on a simplified world . |
Transformer-based Speech Model Learns Well as Infants and Encodes Abstractions through Exemplars in the Poverty of the Stimulus Environment (2025.coling-main)
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| Challenge: | Existing theories of language learning for infants are inadequate, according to Chomsky . infants learn language in impoverished environments, according a new study . |
| Approach: | They designed a series of tasks, scenarios, and metrics to simulate the POS . they found that the emerging speech model wav2vec2.0 can learn well in noisy Mandarin environments. |
| Outcome: | The proposed model can learn in noisy and sparse Mandarin environments. |
POLARIS: A Gödel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair (2026.findings-acl)
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| Challenge: | Gödel agent Polaris makes policy level changes with small, auditable patches that persist in the policy and are reused on unseen instances within each benchmark. |
| Approach: | They propose a Gödel agent that performs policy repair via experience abstraction . Polaris makes policy level changes with small, auditable patches that persist in the policy . |
| Outcome: | The proposed agent improves on MGSM, DROP, GPQA, and LitBench models over the base policy and competitive baselines. |