1 citations · 1 across the 8 of their papers we have counts for
8 papers
RVR: Retrieve-Verify-Retrieve for Comprehensive Question Answering
Deniz Qian, Hung-Ting Chen, Eunsol Choi
Comprehensively retrieving diverse documents is crucial to address queries that admit a wide range of valid answers. We introduce retrieve-verify-retrieve (RVR), a multi-round retr…
Beyond Single Embeddings: Capturing Diverse Targets with Multi-Query Retrieval
Hung-Ting Chen, Xiang Liu, Shauli Ravfogel +1
Most text retrievers generate \emph{one} query vector to retrieve relevant documents. Yet, the conditional distribution of relevant documents for the query may be multimodal, e.g.,…
Open-World Evaluation for Retrieving Diverse Perspectives
Hung-Ting Chen, Eunsol Choi
We study retrieving a set of documents that covers various perspectives on a complex and contentious question (e.g., will ChatGPT do more harm than good?). We curate a Benchmark fo…
CaLMQA: Exploring culturally specific long-form question answering across 23 languages
Shane Arora, Marzena Karpinska, Hung-Ting Chen +3
Despite rising global usage of large language models (LLMs), their ability to generate long-form answers to culturally specific questions remains unexplored in many languages. To f…
Understanding Retrieval Augmentation for Long-Form Question Answering
Hung-Ting Chen, Fangyuan Xu, Shane Arora +1
How retrieved documents are used in language models (LMs) for long-form generation task is understudied. We present two controlled studies on retrieval-augmented LM for long-form q…
Continually Improving Extractive QA via Human Feedback
Ge Gao, Hung-Ting Chen, Yoav Artzi +1
We study continually improving an extractive question answering (QA) system via human user feedback. We design and deploy an iterative approach, where information-seeking users ask…
Rich Knowledge Sources Bring Complex Knowledge Conflicts: Recalibrating Models to Reflect Conflicting Evidence
Hung-Ting Chen, Michael J. Q. Zhang, Eunsol Choi
Question answering models can use rich knowledge sources -- up to one hundred retrieved passages and parametric knowledge in the large-scale language model (LM). Prior work assumes…
Predict and Use Latent Patterns for Short-Text Conversation
Hung-Ting Chen, Yu-Chieh Chao, Ta-Hsuan Chao +1
Many neural network models nowadays have achieved promising performances in Chit-chat settings. The majority of them rely on an encoder for understanding the post and a decoder for…