Causal inference has emerged as a promising paradigm for recommendation systems, moving beyond correlation-based learning to uncover the causal mechanisms behind user–item interactions. Conventional models assume observed interactions directly reflect users’ true preferences, but this assumption often fails in practice...
Si-Rui Huang, Qing Li· Journal of Algorithms in Com...· 0 citations
InterTab is a structure-aware framework for CoT reasoning over table images that interleaves chain-of-thought with tool calls that crop structure-aligned table regions, and improves the average accuracy of its backbone from 68.28% to 73.17% and achieves the best average performance among all compared methods.
Hanqian Li, Si-Rui Huang, Chen Ling et al.· 0 citations
A dual-view approach that connects clinical practice with computational methods is presented, establishing a five-level competency scheme following Miller’s Pyramid and linking deductive, inductive, and abductive reasoning patterns to common medical goals and tasks.
