3 accepted papers
Causal inference from observational data has attracted considerable attention among researchers. One main obstacle is the handling of confounders. As direct measurement of confounders may not be feasible, recent methods seek to address the confounding bias via proxy variables, i.e., covariates postu…
Retrieval-Augmented Generation (RAG) is introduced to enhance Large Language Models (LLMs) by integrating external knowledge. However, conventional RAG approaches treat retrieved documents as independent units, often overlooking their interdependencies. Hybrid-RAG, a recently proposed paradigm that
Chain-of-Thought (CoT) enhances the performance of Large Language Models (LLMs) on reasoning tasks by encouraging step-by-step solutions. However, the verbosity of CoT reasoning hinders its mass deployment in efficiency-critical applications. Recently, implicit CoT approaches have emerged, which enc…