11 papers · 1 filter
MiLorE-SSL: Scaling Multilingual Capabilities in Self-Supervised Models without Forgetting
Jing Xu, Minglin Wu, Xueyuan Chen +2
Self-supervised learning (SSL) has greatly advanced speech representation learning, but multilingual SSL models remain constrained to languages encountered during pretraining. Retr…
TreePS-RAG: Tree-based Process Supervision for Reinforcement Learning in Agentic RAG
Tianhua Zhang, Kun Li, Junan Li +5
Agentic retrieval-augmented generation (RAG) formulates question answering as a multi-step interaction between reasoning and information retrieval, and has recently been advanced b…
Seamless Language Expansion: Enhancing Multilingual Mastery in Self-Supervised Models
Jing Xu, Minglin Wu, Xixin Wu +1
Self-supervised (SSL) models have shown great performance in various downstream tasks. However, they are typically developed for limited languages, and may encounter new languages…
Naturalistic Language-related Movie-Watching fMRI Task for Detecting Neurocognitive Decline and Disorder
Yuejiao Wang, Xianmin Gong, Xixin Wu +4
Early detection is crucial for timely intervention aimed at preventing and slowing the progression of neurocognitive disorder (NCD), a common and significant health problem among t…
RAG-Zeval: Towards Robust and Interpretable Evaluation on RAG Responses through End-to-End Rule-Guided Reasoning
Kun Li, Yunxiang Li, Tianhua Zhang +4
Robust evaluation is critical for deploying trustworthy retrieval-augmented generation (RAG) systems. However, current LLM-based evaluation frameworks predominantly rely on directl…
Generate, Discriminate, Evolve: Enhancing Context Faithfulness via Fine-Grained Sentence-Level Self-Evolution
Kun Li, Tianhua Zhang, Yunxiang Li +5
Improving context faithfulness in large language models is essential for developing trustworthy retrieval augmented generation systems and mitigating hallucinations, especially in…