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cs.CL2026

MultiHashFormer: Hash-based Generative Language Models

Huiyin Xue, Atsuki Yamaguchi, Nikolaos Aletras

Language models (LMs) represent tokens using embedding matrices that scale linearly with the vocabulary size. To constrain the parameter footprint, prior work proposes hashing many…

cs.CL2026

Yuvion LLM: An Adversarially-Aware Large Language Model for Content And AI Safety

Ting Ma, Xiufeng Huang, Benlei Cui +43

As large language models are increasingly deployed in real-world systems, safety failures can still lead to harmful outputs and dangerous misuse. We argue that the essence of safet…

cs.CL2025

Lifelong Knowledge Editing for LLMs with Retrieval-Augmented Continuous Prompt Learning

Qizhou Chen, Taolin Zhang, Xiaofeng He +4

Model editing aims to correct outdated or erroneous knowledge in large language models (LLMs) without the need for costly retraining. Lifelong model editing is the most challenging…

cs.CL2024

Towards Rehearsal-Free Multilingual ASR: A LoRA-based Case Study on Whisper

Tianyi Xu, Kaixun Huang, Pengcheng Guo +4

Pre-trained multilingual speech foundation models, like Whisper, have shown impressive performance across different languages. However, adapting these models to new or specific lan…

cs.CL2024

R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models

Taolin Zhang, Dongyang Li, Qizhou Chen +5

Retrieval-augmented large language models (LLMs) leverage relevant content retrieved by information retrieval systems to generate correct responses, aiming to alleviate the halluci…

cs.CL2024

KEHRL: Learning Knowledge-Enhanced Language Representations with Hierarchical Reinforcement Learning

Dongyang Li, Taolin Zhang, Longtao Huang +3

Knowledge-enhanced pre-trained language models (KEPLMs) leverage relation triples from knowledge graphs (KGs) and integrate these external data sources into language models via sel…