Papers with small-scale LMs
MCTS-RAG: Enhancing Retrieval-Augmented Generation with Monte Carlo Tree Search (2025.findings-emnlp)
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| Challenge: | MCTS-RAG combines structured reasoning with adaptive retrieval . compared to conventional MCTLs, MCTR-RAg relies on internal model knowledge without external facts . |
| Approach: | a new approach integrates retrieval-augmented generation and Monte Carlo Tree Search to enhance reasoning capabilities of small language models. |
| Outcome: | MCTS-RAG integrates retrieval-augmented generation and Monte Carlo Tree Search to improve reasoning paths. |
Modeling Overregularization in Children with Small Language Models (2024.findings-acl)
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| Challenge: | Existing research has analyzed regularization in language acquisition only by modeling word inflection directly, which is unnatural in light of human language acquisition. |
| Approach: | They hypothesize that language models that imitate errors children make during language acquisition have a learning process more similar to humans. |
| Outcome: | The proposed model shows child-like U-shaped learning curves clearly for certain verbs, but the preferences for types of overgeneralization did not fully match the observations in children. |