31 citations · 38 across the 9 of their papers we have counts for
9 papers
ConvMix: A Mixed-Criteria Data Augmentation Framework for Conversational Dense Retrieval
Fengran Mo, Jinghan Zhang, Yuchen Hui +4
Conversational search aims to satisfy users' complex information needs via multiple-turn interactions. The key challenge lies in revealing real users' search intent from the contex…
Exploring Sparse Adapters for Scalable Merging of Parameter Efficient Experts
Samin Yeasar Arnob, Zhan Su, Minseon Kim +6
Merging parameter-efficient task experts has recently gained growing attention as a way to build modular architectures that can be rapidly adapted on the fly for specific downstrea…
Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search
Fengran Mo, Chen Qu, Kelong Mao +4
Conversational search supports multi-turn user-system interactions to solve complex information needs. Different from the traditional single-turn ad-hoc search, conversational sear…
Towards Modular LLMs by Building and Reusing a Library of LoRAs
Oleksiy Ostapenko, Zhan Su, Edoardo Maria Ponti +5
The growing number of parameter-efficient adaptations of a base large language model (LLM) calls for studying whether we can reuse such trained adapters to improve performance for…
Mixture of Latent Experts Using Tensor Products
Zhan Su, Fengran Mo, Prayag Tiwari +3
In multi-task learning, the conventional approach involves training a model on multiple tasks simultaneously. However, the training signals from different tasks can interfere with…
History-Aware Conversational Dense Retrieval
Fengran Mo, Chen Qu, Kelong Mao +4
Conversational search facilitates complex information retrieval by enabling multi-turn interactions between users and the system. Supporting such interactions requires a comprehens…
Multi-Head Adapter Routing for Cross-Task Generalization
Lucas Caccia, Edoardo Ponti, Zhan Su +3
Parameter-efficient fine-tuning (PEFT) for cross-task generalization consists in pre-training adapters on a multi-task training set before few-shot adaptation to test tasks. Polytr…
A Generalized Language Model in Tensor Space
Lipeng Zhang, Peng Zhang, Xindian Ma +3
In the literature, tensors have been effectively used for capturing the context information in language models. However, the existing methods usually adopt relatively-low order ten…
A Quantum Many-body Wave Function Inspired Language Modeling Approach
Peng Zhang, Zhan Su, Lipeng Zhang +2
The recently proposed quantum language model (QLM) aimed at a principled approach to modeling term dependency by applying the quantum probability theory. The latest development for…