35 citations · 205 across the 32 of their papers we have counts for
32 papers
MEFT: Memory-Efficient Fine-Tuning through Sparse Adapter
Jitai Hao, WeiWei Sun, Xin Xin +4
Parameter-Efficient Fine-tuning (PEFT) facilitates the fine-tuning of Large Language Models (LLMs) under limited resources. However, the fine-tuning performance with PEFT on comple…
ExcluIR: Exclusionary Neural Information Retrieval
Wenhao Zhang, Mengqi Zhang, Shiguang Wu +5
Exclusion is an important and universal linguistic skill that humans use to express what they do not want. However, in information retrieval community, there is little research on…
Disentangling ID and Modality Effects for Session-based Recommendation
Xiaokun Zhang, Bo Xu, Zhaochun Ren +3
Session-based recommendation aims to predict intents of anonymous users based on their limited behaviors. Modeling user behaviors involves two distinct rationales: co-occurrence pa…
Generative Retrieval as Multi-Vector Dense Retrieval
Shiguang Wu, Wenda Wei, Mengqi Zhang +5
Generative retrieval generates identifiers of relevant documents in an end-to-end manner using a sequence-to-sequence architecture for a given query. The relation between generativ…
Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation
Jiyuan Yang, Yuanzi Li, Jingyu Zhao +8
Sequential Recommenders have been widely applied in various online services, aiming to model users' dynamic interests from their sequential interactions. With users increasingly en…
Improving the Robustness of Large Language Models via Consistency Alignment
Yukun Zhao, Lingyong Yan, Weiwei Sun +6
Large language models (LLMs) have shown tremendous success in following user instructions and generating helpful responses. Nevertheless, their robustness is still far from optimal…