164 citations · 483 across the 35 of their papers we have counts for
9 papers · 1 filter
Bridging The Gap: Entailment Fused-T5 for Open-retrieval Conversational Machine Reading Comprehension
Xiao Zhang, Heyan Huang, Zewen Chi +1
Open-retrieval conversational machine reading comprehension (OCMRC) simulates real-life conversational interaction scenes. Machines are required to make a decision of "Yes/No/Inqui…
Optimizing Prompts for Text-to-Image Generation
Yaru Hao, Zewen Chi, Li Dong +1
Well-designed prompts can guide text-to-image models to generate amazing images. However, the performant prompts are often model-specific and misaligned with user input. Instead of…
TorchScale: Transformers at Scale
Shuming Ma, Hongyu Wang, Shaohan Huang +8
Large Transformers have achieved state-of-the-art performance across many tasks. Most open-source libraries on scaling Transformers focus on improving training or inference with be…
Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning
Barun Patra, Saksham Singhal, Shaohan Huang +5
In this paper, we elaborate upon recipes for building multilingual representation models that are not only competitive with existing state-of-the-art models but are also more param…
ET5: A Novel End-to-end Framework for Conversational Machine Reading Comprehension
Xiao Zhang, Heyan Huang, Zewen Chi +1
Conversational machine reading comprehension (CMRC) aims to assist computers to understand an natural language text and thereafter engage in a multi-turn conversation to answer que…
Unsupervised Question Answering via Answer Diversifying
Yuxiang Nie, Heyan Huang, Zewen Chi +1
Unsupervised question answering is an attractive task due to its independence on labeled data. Previous works usually make use of heuristic rules as well as pre-trained models to c…
Language Models are General-Purpose Interfaces
Yaru Hao, Haoyu Song, Li Dong +5
Foundation models have received much attention due to their effectiveness across a broad range of downstream applications. Though there is a big convergence in terms of architectur…
Cross-Lingual Phrase Retrieval
Heqi Zheng, Xiao Zhang, Zewen Chi +5
Cross-lingual retrieval aims to retrieve relevant text across languages. Current methods typically achieve cross-lingual retrieval by learning language-agnostic text representation…
On the Representation Collapse of Sparse Mixture of Experts
Zewen Chi, Li Dong, Shaohan Huang +9
Sparse mixture of experts provides larger model capacity while requiring a constant computational overhead. It employs the routing mechanism to distribute input tokens to the best-…