29 citations · 41 across the 13 of their papers we have counts for
10 papers · 1 filter
Adapter-based Selective Knowledge Distillation for Federated Multi-domain Meeting Summarization
Xiachong Feng, Xiaocheng Feng, Xiyuan Du +2
Meeting summarization has emerged as a promising technique for providing users with condensed summaries. However, existing work has focused on training models on centralized data,…
Prompter: Zero-shot Adaptive Prefixes for Dialogue State Tracking Domain Adaptation
Taha Aksu, Min-Yen Kan, Nancy F. Chen
A challenge in the Dialogue State Tracking (DST) field is adapting models to new domains without using any supervised data, zero-shot domain adaptation. Parameter-Efficient Transfe…
Songs Across Borders: Singable and Controllable Neural Lyric Translation
Longshen Ou, Xichu Ma, Min-Yen Kan +1
The development of general-domain neural machine translation (NMT) methods has advanced significantly in recent years, but the lack of naturalness and musical constraints in the ou…
The ACL OCL Corpus: Advancing Open Science in Computational Linguistics
Shaurya Rohatgi, Yanxia Qin, Benjamin Aw +2
We present ACL OCL, a scholarly corpus derived from the ACL Anthology to assist Open scientific research in the Computational Linguistics domain. Integrating and enhancing the prev…
Self-Evaluation Guided Beam Search for Reasoning
Yuxi Xie, Kenji Kawaguchi, Yiran Zhao +4
Breaking down a problem into intermediate steps has demonstrated impressive performance in Large Language Model (LLM) reasoning. However, the growth of the reasoning chain introduc…
UDApter -- Efficient Domain Adaptation Using Adapters
Bhavitvya Malik, Abhinav Ramesh Kashyap, Min-Yen Kan +1
We propose two methods to make unsupervised domain adaptation (UDA) more parameter efficient using adapters, small bottleneck layers interspersed with every layer of the large-scal…
MM-Align: Learning Optimal Transport-based Alignment Dynamics for Fast and Accurate Inference on Missing Modality Sequences
Wei Han, Hui Chen, Min-Yen Kan +1
Existing multimodal tasks mostly target at the complete input modality setting, i.e., each modality is either complete or completely missing in both training and test sets. However…
GL-CLeF: A Global-Local Contrastive Learning Framework for Cross-lingual Spoken Language Understanding
Libo Qin, Qiguang Chen, Tianbao Xie +4
Due to high data demands of current methods, attention to zero-shot cross-lingual spoken language understanding (SLU) has grown, as such approaches greatly reduce human annotation…
TraVLR: Now You See It, Now You Don't! A Bimodal Dataset for Evaluating Visio-Linguistic Reasoning
Keng Ji Chow, Samson Tan, Min-Yen Kan
Numerous visio-linguistic (V+L) representation learning methods have been developed, yet existing datasets do not adequately evaluate the extent to which they represent visual and…
A PDTB-Styled End-to-End Discourse Parser
Ziheng Lin, Hwee Tou Ng, Min-Yen Kan
We have developed a full discourse parser in the Penn Discourse Treebank (PDTB) style. Our trained parser first identifies all discourse and non-discourse relations, locates and la…