4 papers
Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
Yue Zhang, Yafu Li, Leyang Cui +13
While large language models (LLMs) have demonstrated remarkable capabilities across a range of downstream tasks, a significant concern revolves around their propensity to exhibit h…
SeqPE: Transformer with Sequential Position Encoding
Huayang Li, Yahui Liu, Hongyu Sun +5
Since self-attention layers in Transformers are permutation invariant by design, positional encodings must be explicitly incorporated to enable spatial understanding. However, fixe…
Exploring the Reliability of Large Language Models as Customized Evaluators for Diverse NLP Tasks
Qintong Li, Leyang Cui, Lingpeng Kong +1
Previous work adopts large language models (LLMs) as evaluators to evaluate natural language process (NLP) tasks. However, certain shortcomings, e.g., fairness, scope, and accuracy…
Gated Slot Attention for Efficient Linear-Time Sequence Modeling
Yu Zhang, Songlin Yang, Ruijie Zhu +9
Linear attention Transformers and their gated variants, celebrated for enabling parallel training and efficient recurrent inference, still fall short in recall-intensive tasks comp…