66 citations · 93 across the 6 of their papers we have counts for
6 papers
Using Natural Language Explanations to Rescale Human Judgments
Manya Wadhwa, Jifan Chen, Junyi Jessy Li +1
The rise of large language models (LLMs) has brought a critical need for high-quality human-labeled data, particularly for processes like human feedback and evaluation. A common pr…
Improving Cross-task Generalization of Unified Table-to-text Models with Compositional Task Configurations
Jifan Chen, Yuhao Zhang, Lan Liu +5
There has been great progress in unifying various table-to-text tasks using a single encoder-decoder model trained via multi-task learning (Xie et al., 2022). However, existing met…
Multi-hop Question Answering via Reasoning Chains
Jifan Chen, Shih-ting Lin, Greg Durrett
Multi-hop question answering requires models to gather information from different parts of a text to answer a question. Most current approaches learn to address this task in an end…
Understanding Dataset Design Choices for Multi-hop Reasoning
Jifan Chen, Greg Durrett
Learning multi-hop reasoning has been a key challenge for reading comprehension models, leading to the design of datasets that explicitly focus on it. Ideally, a model should not b…
Learning Word Embeddings from Intrinsic and Extrinsic Views
Jifan Chen, Kan Chen, Xipeng Qiu +3
While word embeddings are currently predominant for natural language processing, most of existing models learn them solely from their contexts. However, these context-based word em…
Modelling Interaction of Sentence Pair with coupled-LSTMs
Pengfei Liu, Xipeng Qiu, Xuanjing Huang
Recently, there is rising interest in modelling the interactions of two sentences with deep neural networks. However, most of the existing methods encode two sequences with separat…